how to make a robot that can do your homework

How to Build Your Own Robot Friend: Making AI Education More Accessible

Usc researchers develop new open-source platform to help students build their own low-cost robot companion from scratch.

USC researchers have created a low-cost, accessible learning kit to help college and high school students build their own “robot friend.” Photo/James Kim.

From smart virtual assistants and self-driving cars to digital health and fraud prevention systems, AI technology is transforming almost every aspect of our daily lives—and education is no different. For all its promise, the rise of AI, like any new technology, raises some pressing ethical and equity questions.

How can we ensure that such a powerful tool can be accessed by all students regardless of background? 

Inspired by this call to action, USC researchers have created a low-cost, accessible learning kit to help college and high school students build their own “robot friend.” Students can personalize the robot’s “body,” program the robot to mimic their head posture, and learn about AI ethics and fairness in an engaging, accessible way.

The system is outlined in a new study, titled “ Build Your Own Robot Friend: An Open-Source Learning Module for Accessible and Engaging AI Education ,” presented this week at the AAAI Conference on Artificial Intelligence , education symposium track.   

“We believe it is important for students to learn about fairness and ethics in AI in the same way that we learned about math and physics in K-12,” said co-lead author Zhonghao Shi, a doctoral student in computer science who conducts his research in the USC Interaction Lab led by Professor Maja Matarić . “We may not use these subjects every day, but having a basic understanding of these concepts helps us do better work and be mindful of new technologies.”    

Supported by the National Science Foundation, the paper is co-lead-authored by Amy O’Connell, a USC computer science doctoral student and Shi’s labmate, and Zongjian Li, a software engineer working with   Mohammad Soleymani, a research associate professor at the USC Institute for Creative Technologies. Soleymani and Matarić are co-authors, in addition to Guy Hoffman from Cornell University, and USC computer science undergraduate students Siqi Liu and Jennifer Ayissi. 

Members of the USC Interaction Lab and Professor Maja Matarić with customized versions of Blossom the robot. Photo/James Kim.

Hands-on experience

The three-part open-source learning module provides students with hands-on experience and introductory instruction about various aspects of AI, including robotics, machine learning, software engineering, and mechanical engineering. It helps to address a gap in the market for AI education, said Shi and O’Connell.  

Currently, pre-built robots, such as the NAO, are unaffordable for schools with limited resources, while educational robot kits, such as LEGO Mindstorms, though affordable, do not adapt to students at different levels.     

The NAO robot, while commonly found in research labs, is costly, running at around $15,000.

“We’re proposing this open-source model to not only improve education in AI for all students but also to make human-interaction research more affordable for labs and research institutions,” said Shi. “Ultimately, we want to increase access to human-centered AI education for college students and create a pathway to more accessible research.”

To reduce costs and development time for learners, the team customized and simplified Blossom, a small, open-source robot originally developed by Hoffman at Cornell University. Blossom is a common fixture in USC’s Interaction Lab—Shi previously used the robot to design better AI voices for mindfulness exercises, while O’Connell programmed it to act as a “study buddy” for students with ADHD symptoms.      

Last year, the duo began to devise ways to use the robot for educational purposes and set to work creating a low-cost, customizable and “human-focused” module that could mirror some of the ways that students will interact with technology in their everyday lives. 

USC computer science doctoral student Amy O’Connell and undergraduate student Jennifer Ayissi customize Blossom the robot. Photo/James Kim.

To make the robot more affordable, they developed strategies to subsidize its cost. In the version of Blossom presented in the study, the materials are created using 3D printers, instead of more costly laser printing.  Currently, one of the team’s customizable robots costs around $250 to make. In comparison, a NAO robot runs at around $15,000.  

O’Connell, who learned to crochet during the pandemic, designed five new Blossom exteriors and created detailed, easy-to-follow patterns and tutorials for each version, including a baby onesie, knitted and crocheted options, which are all low-cost and customizable. 

“We want to increase access to human-centered AI education for students.” Zhonghao Shi. 

After constructing their robot friend, students are encouraged to further customize Blossom with, for instance, mechanical eyebrows, color-changing lights, or even an expressive face screen. For O’Connell, creativity has been a crucial part of her own engineering journey.   

“Crafting and engineering require similar strengths like counting, planning, and spatial reasoning,” said O’Connell. “By incorporating crafting into this project, we hope to draw in creative students who might not have considered how their skills align with robotics and engineering.”  

Understanding ethics and fairness   

The system was piloted in a 2-day workshop in May 2023 with 15 undergraduate college students from a local minority-serving institution. Four teams of students constructed Blossom robots following the learning module assembly guide with blank knitted exterior to personalize with accessories. On the second day, the students used pre-trained head pose tracking and gesture recognition models to detect and mimic nodding behaviors from the user.

In part one of the module, study participants (anonymized) construct a simplified version of the Blossom open-source robot platform.

From post-workshop surveys, they found that 92% of the participants believed that the workshop helped them learn more about the topics covered and all the participants believed that the workshop encouraged them to study more about robotics and AI in the future.    

“Equipping users with AI literacy, including an understanding of AI ethics and fairness, is crucial to avoid unintended discrimination against marginalized groups,” said Shi.   

In continued work, the team plans to further evaluate and improve the module for high school students and K-12 students. Ultimately, the researchers hope to expand access for students at different educational levels.  

“We’re excited to share more about our project with people from around the world,” Shi said. “We want to make sure that people from different kinds of socioeconomic backgrounds have the opportunity to gain an education on AI and participate in the process of improving AI for future use.”  

Published on February 22nd, 2024

Last updated on May 16th, 2024

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Robots are infiltrating our daily lives. They are cleaning our floors, driving us around on campus or the golf course, operating on people, flipping hamburgers, and they’re teaching children in Asia. There are even robots like mBot that teaches kids about robotics.

Robots are meant to automate repetitive tasks, leaving humans free for more creative and rewarding endeavors. And what is more repetitive than having to copy text from a book several times?

The writing robot that can copy texts for students

Enter a very enterprising young Chinese teen. She used the money she received over Chinese New Year to buy a so-called copying robot to do her homework for her. In all fairness, the homework, in this case, was to copy passages from a textbook. Chinese teachers give this kind of homework, even during the Lunar Year holidays, so students can practice the thousands of Chinese characters that make up Mandarin Chinese.

The device, a metal frame, and pen comes with the marketing message that it could “imitate all sorts of handwriting”. In her case, the device performed perfectly, finishing all her homework in record time and in her handwriting. The incident was reported , including the destruction of the device by the girl’s mother. Far from being criticized for her dishonesty, the girl was praised by netizens for her initiative and the company that manufactures the writing robot has been inundated with inquiries ever since.

In an investigation, the South China Morning Post found several entries for a so-called “copying robot” on the e-commerce platform Taobao. It seems like a good idea to let a robot do something for you that is boring and repetitive, but you have to ask yourself if that’s a sensible thing to do. Surely you miss out on a learning opportunity if you let a robot do your work for you.

That doesn’t mean that robots cannot be useful when it comes to school homework. Rather than doing the work for you, your robot can help you to do the work and master the concepts in the curriculum. 

The robot that can do math homework

For kids who might feel burdened by too much homework, the future holds much promise. Christopher Yan and Derek He have come up with a concept of a homework-solving robot. Their prototype can solve math homework. What’s more, when it’s completed, the robot will be able to write the answers according to the user’s handwriting, so a teacher won’t suspect that the work was not done by the student. Their project known as Homework Help , picked up the top honors at this year’s PennApps, one of the largest student hackathons in the world, held at University of Pennsylvania.

It seems there is a need for robots that can help students with their homework. Scientists have noticed that children form close emotional bonds with social robots. It is not yet clear why this is so, but educators can exploit this to help students with their studies. Robots can, and do, add a fun aspect to learning. They can also add a fun aspect to homework.

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Do your homework

Are your students using AI bots to do theirs? After all, AI is readily available and capable as we found out

We gave ChatGPT a prompt to ‘write an editorial (300 words) for a readership of teachers on the danger of students using AI bots to do their homework for them’. This what it produced:

Source: © Shutterstock

Could you spot a chemistry homework written by an AI bot?

As teachers, we have all seen the impact that technology can have on the classroom. From smartphones and tablets to educational software and online resources, there are countless tools that can help our students learn and grow. However, there is also a dark side to technology in education, and it is something that we need to be aware of and address.

One of the biggest concerns is the use of AI bots to do students’ homework for them. With the rise of artificial intelligence and the increasing availability of AI-powered tools, it is becoming easier and easier for students to use these bots to complete their assignments without actually learning the material.

We need to make it clear that cheating is unacceptable

On the surface, this may seem like a harmless way for students to save time and effort, but it is actually a serious problem for several reasons. First and foremost, using AI bots to do homework undermines the entire purpose of education. The goal of homework is to reinforce the concepts that students are learning in class, not to simply churn out answers without understanding them. By using AI bots to do their homework, students are cheating themselves out of a valuable learning opportunity.

Furthermore, using AI bots to do homework sets a dangerous precedent. It teaches students that they can take shortcuts and cheat their way through school, rather than putting in the hard work and effort that are necessary for success. This attitude can carry over into other areas of their lives, leading to a lack of motivation and a lack of real-world skills.

As teachers, it is our responsibility to educate our students about the dangers of using AI bots to do their homework. We need to make it clear that cheating is unacceptable and that the only way to truly learn and grow is through hard work and dedication. By taking a strong stance on this issue, we can help our students develop the skills and values that will serve them well throughout their lives. 

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How to Build a Bot and Automate your Everyday Work

Most jobs have repetitive tasks that you can automate, which frees up some of your valuable time. This makes automation a key skill to acquire.

A small group of skilled automation engineers and domain experts may be able to automate many of the most tedious tasks of entire teams.

In this article, we'll explore the basics of workflow automation using Python – a powerful and easy to learn programming language. We will use Python to write an easy and helpful little automation script that will clean up a given folder and put each file into its according folder.

Our goal won't be to write perfect code or create ideal architectures in the beginning. We also won't build anything "illegal". Instead we'll look at how to create a script that automatically cleans up a given folder and all of its files.

Table of contents

• Simple Automation
• Public API Automation

API Reverse Engineering

• Ethical Considerations of Automation

Creating a Directory Clean-Up Script

A complete guide to bot creation and automating your everyday work, areas of automation and where to start.

Let's start with defining what kind of automations there are.

The art of automation applies to most sectors. For starters, it helps with tasks like extracting email addresses from a bunch of documents so you can do an email blast. Or more complex approaches like optimizing workflows and processes inside of large corporations.

Of course, going from small personal scripts to large automation infrastructure that replaces actual people involves a process of learning and improving. So let's see where you can start your journey.

Simple Automations

Simple automations allow for a quick and straightforward entry point. This can cover small independent processes like project clean-ups and re-structuring of files inside of directories, or parts of a workflow like automatically resizing already saved files.

Public API Automations

Public API automations are the most common form of automation since we can access most functionality using HTTP requests to APIs nowadays. For example, if you want to automate the watering of your self-made smart garden at home.

To do that, you want to check the weather of the current day to see whether you need to water or if there is rain incoming.

API reverse engineering-based automation is more common in actual bots and the "Bot Imposter" section of the chart in the "Ethical Considerations" section below.

By reverse-engineering an API, we understand the user flow of applications. One example could be the login into an online browser game.

By understanding the login and authentication process, we can duplicate that behaviour with our own script. Then we can create our own interface to work with the application even though they don't provide it themselves.

Whatever approach you're aiming at, always consider whether it's legal or not.

You don't want to get yourself into trouble, do you? ?

Ethical Considerations

Some guy on GitHub once contacted me and told me this:

“Likes and engagement are digital currency and you are devaluing them.”

This stuck with me and made me question the tool I've built for exactly that purpose.

The fact that these interactions and the engagement can be automated and “faked” more and more leads to a distorted and broken social media system.

People who produce valuable and good content are invisible to other users and advertisement companies if they don’t use bots and other engagement systems. A friend of mine came up with the following association with Dante’s “Nine Circles of Hell” where with each step closer to becoming a social influencer you get less and less aware of how broken this whole system actually is.

I want to share this with you here since I think it's an extremely accurate representation of what I witnessed while actively working with Influencers with InstaPy.

Level 1: Limbo - If you don’t bot at all Level 2: Flirtation - When you manually like and follow as many people as you can to get them to follow you back / like your posts Level 3: Conspiracy - when you join a Telegram group to like and comment on 10 photos so the next 10 people will like and comment on your photo Level 4: Infidelity - When you use a low-cost Virtual Assistant to like and follow on your behalf Level 5: Lust - When you use a bot to give likes, and don’t receive any likes back in return (but you don’t pay for it - for example, a Chrome extension) Level 6: Promiscuity - When you use a bot to Give 50+ likes to Get 50+ likes, but you don’t pay for it - for example, a Chrome extension Level 7: Avarice or Extreme Greed - When you use a bot to Like / Follow / Comment on between 200–700 photos, ignoring the chance of getting banned Level 8: Prostitution - When you pay an unknown 3rd party service to engage in automated reciprocal likes / follows for you, but they use your account to like / follow back Level 9: Fraud / Heresy - When you buy followers and likes and try to sell yourself to brands as an influencer

The level of botting on social media is so prevalent that if you don’t bot, you will be stuck in Level 1, Limbo , with no follower growth and low engagement relative to your peers.

In economic theory, this is known as a prisoner's dilemma and zero-sum game . If I don’t bot and you bot, you win. If you don’t bot and I bot, I win. If no one bots, everyone wins. But since there is no incentive for everyone not to bot, everyone bots, so no one wins.

Be aware of this and never forget the implications this whole tooling has on social media.

We want to avoid dealing with ethical implications and still work on an automation project here. This is why we will create a simple directory clean-up script that helps you organise your messy folders.

We now want to look at a quite simple script. It automatically cleans up a given directory by moving those files into according folders based on the file extension.

So all we want to do is this:

Setting up the Argument Parser

Since we are working with operating system functionality like moving files, we need to import the os library. In addition to that, we want to give the user some control over what folder is cleaned up. We will use the argparse library for this.

After importing the two libraries, let's first set up the argument parser. Make sure to give a description and a help text to each added argument to give valuable help to the user when they type --help .

Our argument will be named --path . The double dashes in front of the name tell the library that this is an optional argument. By default we want to use the current directory, so set the default value to be "." .

This already finishes the argument parsing section – it's quite simple and readable, right?

Let's execute our script and check for errors.

Once executed, we can see the directory name being printed to the console, perfect. Let's now use the os library to get the files of the given path.

Getting a list of files from the folder

By using the os.listdir(path) method and providing it a valid path, we get a list of all the files and folders inside of that directory.

After listing all elements in the folder, we want to differentiate between files and folders since we don't want to clean up the folders, only the files.

In this case, we use a Python list comprehension to iterate through all the elements and put them into the new lists if they meet the given requirement of being a file or folder.

As always, let's make sure that our users get feedback. So add a print statement that gives the user an indication about how many files will be moved.

After re-executing the python script, we can now see that the /test folder I created contains 60 files that will be moved.

Creating a folder for every file extension

The next and more important step now is to create the folder for each of the file extensions. We want to do this by going through all of our filtered files and if they have an extension for which there is no folder already, create one.

The os library helps us with more nice functionality like the splitting of the filetype and path of a given document, extracting the path itself and name of the document.  

The break statement at the end of the code above makes sure that our terminal does not get spammed if our directory contains dozens of files.

Once we've set this up, let's execute our script to see an output similar to this:

We can now see that the implementation above splits off the filetype and then extracts the parts from the full path.

Since we have the filetype now, we can check if a folder with the name of this type already exists.

Before we do that, we want to make sure to skip a few files. If we use the current directory "." as the path, we need to avoid moving the python script itself. A simple if condition takes care of that.

In addition to that, we don't want to move Hidden Files , so let's also include all files that start with a dot. The .DS_Store file on macOS is an example of a hidden file.

Once we've taken care of the python script and hidden files, we can now move on to creating the folders on the system.

In addition to our check, if the folder already was there when we read the content of the directory, in the beginning, we need a way to track the folders we've already created. That was the reason we declared the created_folders = [] list. It will serve as the memory to track the names of folders.

To create a new folder, the os library provides a method called os.mkdir(folder_path) that takes a path and creates a folder with the given name there.

This method may throw an exception, telling us that the folder already exists. So let's also make sure to catch that error.

After setting up the folder creation, let's re-execute our script.

On the first run of execution, we can see a list of logs telling us that the folders with the given types of file extensions have been created.

Moving each file into the right subfolder

The last step now is to actually move the files into their new parent folders.

An important thing to understand when working with os operations is that sometimes operations can not be undone. This is, for example, the case with deletion. So it makes sense to first only log out the behavior our script would achieve if we execute it.

This is why the os.rename(...) method has been commented here.

After executing our script and seeing the correct logging, we can now remove the comment hash before our os.rename() method and give it a final go.

This final execution will now move all the files into their appropriate folders and our directory will be nicely cleaned up without the need for manual actions.

In the next step, we could now use the script we created above and, for example, schedule it to execute every Monday to clean up our Downloads folder for more structure.

That is exactly what we are creating as a follow-up inside of our Bot Creation and Workflow Automation Udemy course .

Felix and I built an online video course to teach you how to create your own bots based on what we've learned building InstaPy and his Travian-Bot . In fact, he was even forced to take down since it was too effective.

Join right in and start learning .

If you have any questions or feedback, feel free to reach out to us on Twitter or directly in the discussion section of the course ?

Passionate learner and developer interested in automation. Uses Scratch to teach coding to kids in workshops at a local city library. Open Source enthusiast. Creator of InstaPy.

If you read this far, thank the author to show them you care. Say Thanks

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A new AI chatbot might do your homework for you. But it's still not an A+ student

Why do your homework when a chatbot can do it for you? A new artificial intelligence tool called ChatGPT has thrilled the internet with its superhuman abilities to solve math problems, churn out college essays and write research papers.

After the developer OpenAI released the text-based system to the public last month, some educators have been sounding the alarm about the potential that such AI systems have to transform academia, for better and worse.

"AI has basically ruined homework," said Ethan Mollick, a professor at the University of Pennsylvania's Wharton School of Business, on Twitter.

The tool has been an instant hit among many of his students, he told NPR in an interview on Morning Edition , with its most immediately obvious use being a way to cheat by plagiarizing the AI-written work, he said.

Academic fraud aside, Mollick also sees its benefits as a learning companion.

He's used it as his own teacher's assistant, for help with crafting a syllabus, lecture, an assignment and a grading rubric for MBA students.

"You can paste in entire academic papers and ask it to summarize it. You can ask it to find an error in your code and correct it and tell you why you got it wrong," he said. "It's this multiplier of ability, that I think we are not quite getting our heads around, that is absolutely stunning," he said.

A convincing — yet untrustworthy — bot

But the superhuman virtual assistant — like any emerging AI tech — has its limitations. ChatGPT was created by humans, after all. OpenAI has trained the tool using a large dataset of real human conversations.

"The best way to think about this is you are chatting with an omniscient, eager-to-please intern who sometimes lies to you," Mollick said.

It lies with confidence, too. Despite its authoritative tone, there have been instances in which ChatGPT won't tell you when it doesn't have the answer.

That's what Teresa Kubacka, a data scientist based in Zurich, Switzerland, found when she experimented with the language model. Kubacka, who studied physics for her Ph.D., tested the tool by asking it about a made-up physical phenomenon.

"I deliberately asked it about something that I thought that I know doesn't exist so that they can judge whether it actually also has the notion of what exists and what doesn't exist," she said.

ChatGPT produced an answer so specific and plausible sounding, backed with citations, she said, that she had to investigate whether the fake phenomenon, "a cycloidal inverted electromagnon," was actually real.

When she looked closer, the alleged source material was also bogus, she said. There were names of well-known physics experts listed – the titles of the publications they supposedly authored, however, were non-existent, she said.

"This is where it becomes kind of dangerous," Kubacka said. "The moment that you cannot trust the references, it also kind of erodes the trust in citing science whatsoever," she said.

Scientists call these fake generations "hallucinations."

"There are still many cases where you ask it a question and it'll give you a very impressive-sounding answer that's just dead wrong," said Oren Etzioni, the founding CEO of the Allen Institute for AI , who ran the research nonprofit until recently. "And, of course, that's a problem if you don't carefully verify or corroborate its facts."

An opportunity to scrutinize AI language tools

Users experimenting with the free preview of the chatbot are warned before testing the tool that ChatGPT "may occasionally generate incorrect or misleading information," harmful instructions or biased content.

Sam Altman, OpenAI's CEO, said earlier this month it would be a mistake to rely on the tool for anything "important" in its current iteration. "It's a preview of progress," he tweeted .

The failings of another AI language model unveiled by Meta last month led to its shutdown. The company withdrew its demo for Galactica, a tool designed to help scientists, just three days after it encouraged the public to test it out, following criticism that it spewed biased and nonsensical text.

Similarly, Etzioni says ChatGPT doesn't produce good science. For all its flaws, though, he sees ChatGPT's public debut as a positive. He sees this as a moment for peer review.

"ChatGPT is just a few days old, I like to say," said Etzioni, who remains at the AI institute as a board member and adviser. It's "giving us a chance to understand what he can and cannot do and to begin in earnest the conversation of 'What are we going to do about it?' "

The alternative, which he describes as "security by obscurity," won't help improve fallible AI, he said. "What if we hide the problems? Will that be a recipe for solving them? Typically — not in the world of software — that has not worked out." Copyright 2022 NPR. To see more, visit https://www.npr.org.

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Will Knight

Toyota's Robots Are Learning to Do Housework—By Copying Humans

As someone who quite enjoys the Zen of tidying up, I was only too happy to grab a dustpan and brush and sweep up some beans spilled on a tabletop while visiting the Toyota Research Lab in Cambridge, Massachusetts last year. The chore was more challenging than usual because I had to do it using a teleoperated pair of robotic arms with two-fingered pincers for hands.

Courtesy of Toyota Research Institute

As I sat before the table, using a pair of controllers like bike handles with extra buttons and levers, I could feel the sensation of grabbing solid items, and also sense their heft as I lifted them, but it still took some getting used to.

After several minutes tidying, I continued my tour of the lab and forgot about my brief stint as a teacher of robots. A few days later, Toyota sent me a video of the robot I’d operated sweeping up a similar mess on its own, using what it had learned from my demonstrations combined with a few more demos and several more hours of practice sweeping inside a simulated world.

Autonomous sweeping behavior. Courtesy of Toyota Research Institute

By Angela Watercutter

By Julian Chokkattu

By Medea Giordano

By Eric Ravenscraft

Most robots—and especially those doing valuable labor in warehouses or factories—can only follow preprogrammed routines that require technical expertise to plan out. This makes them very precise and reliable but wholly unsuited to handling work that requires adaptation, improvisation, and flexibility—like sweeping or most other chores in the home. Having robots learn to do things for themselves has proven challenging because of the complexity and variability of the physical world and human environments, and the difficulty of obtaining enough training data to teach them to cope with all eventualities.

There are signs that this could be changing. The dramatic improvements we’ve seen in AI chatbots over the past year or so have prompted many roboticists to wonder if similar leaps might be attainable in their own field. The algorithms that have given us impressive chatbots and image generators are also already helping robots learn more efficiently.

The sweeping robot I trained uses a machine-learning system called a diffusion policy, similar to the ones that power some AI image generators , to come up with the right action to take next in a fraction of a second, based on the many possibilities and multiple sources of data. The technique was developed by Toyota in collaboration with researchers led by Shuran Song , a professor at Columbia University who now leads a robot lab at Stanford.

Toyota is trying to combine that approach with the kind of language models that underpin ChatGPT and its rivals. The goal is to make it possible to have robots learn how to perform tasks by watching videos, potentially turning resources like YouTube into powerful robot training resources. Presumably they will be shown clips of people doing sensible things, not the dubious or dangerous stunts often found on social media.

“If you've never touched anything in the real world, it's hard to get that understanding from just watching YouTube videos,” Russ Tedrake, vice president of Robotics Research at Toyota Research Institute and a professor at MIT, says. The hope, Tedrake says, is that some basic understanding of the physical world combined with data generated in simulation, will enable robots to learn physical actions from watching YouTube clips. The diffusion approach “is able to absorb the data in a much more scalable way,” he says.

Toyota announced its Cambridge robotics institute back in 2015 along with a second institute and headquarters in Palo Alto, California. In its home country of Japan—as in the US and other rich nations—the population is aging fast. The company hopes to build robots that can help people continue living independent lives as they age.

The lab in Cambridge has dozens of robots working away on chores including peeling vegetables, using hand mixers, preparing snacks, and flipping pancakes. Language models are proving helpful because they contain information about the physical world, helping the robots make sense of the objects in front of them and how they can be used.

It’s important to note that despite many demos slick enough to impress a casual visitor, the robots still make lots of errors. Like earlier versions of the model behind ChatGPT, they can veer between seeming humanlike and making strange errors. I saw one robot effortlessly operating a manual hand mixer and another struggling to grasp a bottletop.

Toyota is not the only big tech company hoping to use language models to advance robotics research. Last week, for example, a team at Google DeepMind recently revealed Auto-R , software that uses a large language model to help robots determine the tasks that they could realistically—and safely—do in the real world.

Progress is also being made on the hardware needed to advance robot learning. Last week a group at Stanford University led by Chelsea Finn posted videos of a low-cost mobile teleoperated robotics system called ALOHA. They say the fact that it is mobile allows the robot to tackle a wider range of tasks, giving it a wider range of experiences to learn from than a system locked in one place.

And while it’s easy to be dazzled by robot demo videos, the ALOHA team was good enough to post a highlight reel of failure modes showing the robot fumbling, breaking, and spilling things. Hopefully another robot will learn how to clean up after it.

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How to use AI to help with Homework

Homework is meant to reinforce classroom lessons and develop critical thinking skills. Yet stacked assignments with confusing concepts and tight deadlines often leave students overwhelmed and lacking deeply understood foundations.

This is where AI homework helper apps come in - your personalized tutor available 24/7 to explain challenging material conversationally until clarity clicks. AI capabilities transform homework from isolated frustration to engaging progression.

Let's explore top techniques for responsibly leveraging AI to master tricky homework across academic subjects. Say goodbye to late nights guessing answers alone!

Why Students Struggle Through Homework Alone

Attempting to power through homework solo often backfires due to:

1. Ambiguous Instructions - Remembering exact formatting needs or creative constraints can be tough. And complex academic language leaves guesswork for what a question is even asking.

2. Foundational Knowledge Gaps - New lessons build on assumed comprehended concepts from past courses. When fundamentals remain foggy, new material confuses further.

3. Fixed Resources - Attempting to teach yourself new material with just a textbook or sparse online searching provides limited perspectives. Some learning styles need alternate explanations.

4. Tight Deadlines - Getting stuck on one aspect delays completing further questions. And grading pressures magnify anxiety attempting new skills without sample applications.

"The assigned readings felt almost like a foreign language. I understood the overall topic but couldn't grasp key theories well enough to answer homework prompts correctly."

Thankfully AI advancement now provides students customizable support previously unavailable.

Why AI is a Game Changer for Personalized Academic Help

AI homework assistants excel by:

Explaining Concepts Conversationally - Using natural language interactions, AI helps break down confusing aspects into digestible steps while allowing iterative follow-up questions.

Meeting You At Your Level - AI assessment of knowledge gaps lets its explanations start basic before advancing to higher complexity tailored to you.

Providing Visual Examples - Rendering study aid graphics, idea maps, charts and more to suit different learning preferences with visuals assisting memory retention.

Recommending Related Resources - Suggesting complementary videos, textbook sections, online sources to dive deeper across diverse media.

Unlike one-size-fits-all paper textbooks, AI tutors adapt to individuals' pacing and trouble spots for true personalization. Students gain both autonomy and support exactly when needed.

AI technology has been a game changer for understanding the more complex concepts covered in my courses. Asking follow-up questions until a light bulb moment occurs with the AI tutor has led to huge academic confidence boosts and submitting homework on time without guesswork.

Now let's see step-by-step how leading homework helper platforms enable transformative assistance...

A Walkthrough of AI Homework Helpers in Action

Tools like Just Think make it simple to tap into AI knowledge without any app downloads. Here's how students can get homework clarity:

1. Submit Your Homework Question

Snap a photo of the question, copy/paste long-form text prompts into the app interface, or dictate queries aloud via voice notes. This initial input captures the assignment details to be solved.

2. Receive Detailed AI Explanations

The AI homework assistant then gets to work analyzing the question and your knowledge gaps before delivering personalized explanations to teach you step-by-step techniques for solving problems successfully.

Visual elements are incorporated where helpful to simplify complex processes through relationship mappings. Diagrams enhance memory and application for tricky concepts.

3. Ask Iterative Follow-Up Questions

Confused still? The AI allows back and forth dialogue through additional questions from you, then answering conversationally with tweaked vocabulary and examples tailored to the obstacles in your comprehension.

This interactivity removes feelings of being stuck on your own, instead building momentum towards that satisfied "aha!" moment.

Subjects Where AI Homework Help Excels

Here are academic areas where students gain the most from AI writing and comprehension support:

• Algebra, calculus, statistics concepts explained conversationally
• Step-by-step guidance on solving equations
• Personalized approaches if gaps in foundations
• Breaking down complex physics, chemistry, biology theories through diagrams
• Supplemental readings for enhanced understanding
• Math foundations refreshers relevant to scientific formulas
• Timeline visualizations for context around key events, people
• Primary source analyses
• Comparing biases and angles across historians

English Literature

• Summarizing themes across lengthy assigned readings
• Essay starter frameworks tuned to paper requirements
• Grammar and syntax error flagging for polished prose
• Real-time fixes for improving logic flow and efficiency
• Debugging assistance
• Code readability assessments

And many additional academic subjects are supported and expanding further as AI models continuously advance.

Responsible AI Usage for Optimizing Homework

With great power comes great responsibility. While collaborating with an AI homework helper unlocks huge efficiency gains, students should:

1. Use AI Explanations as Learning Springboards

The goal remains deeply comprehending material yourself, not just copying answers. Treat AI guidance as a tutor for unlocking clarity - master concepts explained to cement foundations.

2. Customize Guidance Around Your Strengths/Weaknesses

AI allows playbooks personalized for each student. Be transparent on knowledge gaps needing work so its approach targets areas precisely needing reinforcement.

3. Double Check AI Recommendations

As robust as underlying models may be, the chance of inaccuracies exists. Verify suggestions and fact check against other reputable sources when uncertain.

Following these best practices keeps your growth as the focus while responsibly optimizing academics.

Additional Homework Help Applications

While tackling challenging assignments takes prime advantage of AI powered homework assistance , students can utilize these personalized benefits for:

Studying & Exam Prep - Using conversational questioning to solidify understanding of core curriculum concepts across every subject.

Paper Proofreading & Editing - Getting objective feedback on draft coherence, grammar issues, and areas needing deeper analysis.

1-on-1 Lesson Support - Getting personalized tutoring from AI on topics you struggle most with via ongoing dialogue tailored to the obstacles blocking you.

Interactive Coding Environments - AI suggests tweaks for improving coding project efficiency, structure and offers industry best practice guidance relative to experience level.

The Future of AI & Education

As artificial intelligence research continues steadily improving machine learning models in areas like natural language processing, virtually every academic field will transform.

We're already seeing homework helper platforms acceleration due to capabilities like:

• Answering open-ended questions, not just formulas
• Lifelike dialogue vs rigid responses
• Faster processing of handwritten work
• Personalize guidance around dynamic knowledge

And in the coming years, increasing accountability around model transparency and ethical development will further cement AI assistants as trusted tutors. Soon getting stuck on assignments even in advanced courses will feel like a relic of the past.

Homework that once overwhelmed students attempting to teach themselves now has a personalized AI tutor reachable 24/7. Platforms like Just Think enable moving from confusion to clarity through natural dialogue tailored exactly to individual needs - no matter the academic subject.

With iterative Q&A sessions unlocking foundational comprehension at your own pace plus visual aids accelerating practical applications, homework levels up from isolated frustration to rewarding skill progression thanks to AI's expanded support.

So next time an assignment has you questioning abilities alone late into the night, empower yourself instead with an AI study buddy right by your side until that grades-boosting "aha!" moment. The future of learning looks abundantly bright.

This Robot Learns How to Fight and Play Piano Just By Watching

Robot see, robot do.

Instead of designing a humanoid robot with AI reasoning and neural networks, you can just teach it yourself.

Researchers at Stanford University developed a robot that can imitate what you’re doing in real-time thanks to a simple webcam setup. Called HumanPlus , the team’s robot can learn how to box, play piano, return a ping pong ball, and type, all by shadowing what a human does.

This method of educating a robot is much simpler than what we’ve seen with more popular models, like Figure 01 or 1X’s Eve robot which both run off natural language understanding. However, once you teach the HumanPlus enough movements, it develops a deep knowledge base that lets it eventually handle tasks autonomously. The level of HumanPlus’s autonomy seems rather simple, like folding clothes or picking things off a shelf, so we don’t expect to see the HumanPlus on a factory floor anytime soon.

Robots Made Easier

Unlike other options we’ve seen, like the Boston Dynamics’ Atlas or Tesla’s Optimus bot , the HumanPlus represents more of a DIY way of getting an autonomous robot in your home. Looking at the bill of materials, the HumanPlus isn’t cheap either, with a total price tag of more than $100,000 if you’re following the exact specs from the researchers. The robot was built using Unitree’s H1 robot as a base, adding on hands from Inspire-Robots and wrists from Robotis, and a Razer webcam for seeing. That means the HumanPlus stands five feet nine inches tall and has 33 degrees of freedom.

The HumanPlus’ design is open source, so nothing is stopping you from adjusting the it as you see fit, so long as you have the technical know-how to do so. One of the researchers, Zipeng Fu, noted that the hardware required to remote control the HumanPlus only costs $50, which is much cheaper compared to the more popular option of using a Meta Quest headset.

Build It Yourself

Since the HumanPlus was the result of a research paper, don’t expect it to be commercially available anytime soon. Instead, you can build your own version using this GitHub repository that’s available to anyone.

If you want to replicate exactly what the Stanford University researchers made, you’ll have to shell out at least $90,000 for Unitree’s H1 robot to serve as the hardware platform. However, the robotics company also recently released a much more affordable version called the G1 that starts at $16,000. Instead of dropping upwards of $25,000 for Tesla’s upcoming Optimus bot, designing your own HumanPlus seems like the cheaper way to get your own autonomous robot at home.

Homework Q&A

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HIX Tutor AI Homework Helper

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Why Rely On HIX Tutor to Get AI Answers for Your Homework

How does HIX Tutor provide help with homework?

HIX Tutor offers step-by-step solutions and detailed explanations to help you understand and solve homework questions. It can assist with your study in various subjects including math, physics, chemistry, biology, and more.

Is HIX Tutor a homework AI for both high school and college students?

Yes, HIX Tutor is designed to cater to the academic needs of both high school and college students, adjusting the complexity of explanations and solutions to match the level of the student.

As an AI question answerer, can HIX Tutor help me prepare for exams?

Absolutely. HIX Tutor can provide AI answers to practice questions and explain complex concepts to help you prepare effectively for your exams.

How accurate is HIX Tutor as a homework AI helper?

HIX Tutor is built with advanced algorithms and is regularly updated to ensure about 98% accuracy in solving problems and providing explanations. However, as with any tool, it's recommended to cross-check solutions when possible.

Will using HIX Tutor be considered cheating?

HIX Tutor is intended as a study aid to enhance learning and understanding. It's important to use it responsibly and abide by your school or institution's academic integrity policies.

Can HIX Tutor help with understanding textbook material?

Yes, HIX Tutor can help explain concepts presented in textbooks, clarify difficult ideas, and solve practice problems to enhance your comprehension of the material.

Does HIX Tutor offer personalized learning experiences?

Yes, HIX Tutor adapts to your own learning requirements, offering personalized feedback and solutions based on your specific needs and progress.

Discover Accurate Answers to Frequently Asked Homework Questions

• Is the kidney an endocrine gland?
• What is the name of the specialist who treats any liver problems?
• How are the mind and body related?
• What process creates somatic cells?
• Is the common bile duct the same as the bile duct?
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• Is hearing controlled by the somatic or autonomic nervous system?
• Why is peripheral vision important?
• How do they diagnose placenta accreta?
• What is a disease of the bone in which bone reabsorption outpaces bone deposit, leaving the person thin and fragile?
• How do we know the expansion of the universe is accelerating?
• What evidence shows that the universe is expanding?
• What makes a black hole black?
• What is the difference between a red giant star and our sun?
• How is a nebula related to star formation?
• How is the Cepheid yardstick validated?
• What is earth composed of?
• What is a progenitor star?
• How fast does the earth orbit the sun?
• How do we know what the earth interior is made of?
• How do masers work compared to a laser?
• With no nuclear reaction occurring, are brown dwarfs visually observable?
• Are there any brown dwarfs optically visible from Earth?
• Can you see a pulsar from earth?
• How is helioseismology used to model the sun?
• What are the units of a photometer?
• What forces keep a planet in orbit and how does each one work on the planet?
• How was the presumed age of the Universe determined?
• At what point in a star's life are they classified as AGB?
• A space-based telescope can achieve a diffraction-limited angular resolution of 0.14 for red light (wavelength 650 nm). What would the resolution of the instrument be in the ultraviolet, at 150nm ?
• How does vinblastin act on cancer?
• How does xylem affect turgor pressure?
• Do animal cells use endocytosis?
• What are common mistakes students make with endocytosis and exocytosis?
• What is the Australopithecus?
• Is Osmosis a simple diffusion or a facilitated diffusion?
• Will glucose be able to move across a cell membrane by simple diffusion?
• How do eukaryotic cells reproduce?
• The start codon is the same for prokaryotes and eukaryotes. What is the start codon?
• What is a signal transduction pathway?
• What is a negative ion is known as?
• Which transition emits photons of the minimum wavelength? #n = 4->1# or #n = 2->1#?
• What is the wavelength of a photon that has a frequency of #"89 MHz"# ?
• What kinds of bonds does the #d_(x^2-y^2)# orbital form in transition metal complexes?
• What is the unabbreviated electron configuration for argon?
• What is the electron configuration of a sodium ion?
• What is the electron configuration for oxygen?
• What is the relationship between the group number of the representative elements and the number of valence electrons?
• How can I balance this equation? ___ AlBr3 + ____ K2SO4 ---> ____ KBr + ____ Al2(SO4)3
• How do you write a balanced equation for the complete combustion of #C_4H_8#?
• How does air pollution lead to acid rain?
• What happens at a continent-oceanic convergent boundary?
• What is responsible for the saltiness of ocean water?
• How has the composition of the earth's atmosphere changed over time?
• How can stars burn without oxygen?
• How do winds form on the earth's surface?
• Why are fossils formed in sedimentary rocks?
• How can the government force or incentivize large companies to reduce air pollution?
• What are the lunar regolith?
• Why igneous rocks are hard?
• Does pollution change the rate of evaporation?
• How does the water cycle change, based on what biome we're talking about?
• Can you please describe the major steps involved in the mining process?
• Today, how many people living on the earth?
• Where in the world is geothermal energy being used the most?
• What is the movement of energy from a geothermal source of energy to produce energy which can be used?
• How do humans harm the oceans, rivers, and other waters?
• What are some ways to prevent or reverse the occurrence of acid rain?
• What are the steps in converting nuclear energy to electrical energy?
• What is an energy pyramid?
• What are single and double covalent bonds?
• How can I determine whether an E or an SN reaction will occur?
• What are the isomers of C4H8?
• Ethylamine is more basic than acetanilide.explain?
• What is the formal charge on each atom in #CO_2#?
• What are vitamins made of?
• What is sigma bond connectivity?
• Why does dehydration of 1-butanol, a primary alcohol, yield 3 products? ]
• How would you find the appropriate buffer with given pKa's and a given pH?
• How do you calculate the electronegativity of a compound?
• What is the recoil velocity of the gun?
• A model train with a mass of #2 kg# is moving along a track at #6 (cm)/s#. If the curvature of the track changes from a radius of #3 cm# to #8 cm#, by how much must the centripetal force applied by the tracks change?
• What is the speed of a rocket that travels 9000 meters in 12.12 seconds?
• An object with a mass of #4 kg# is revolving around a point at a distance of #5 m#. If the object is revolving at a rate of #3 Hz#, what is the centripetal force on the object?
• An object with a mass of #15 kg# is hanging from an axle with a radius of #30 m#. If the wheel attached to the axle has a radius of #9 m#, how much force must be applied to the wheel to keep the object from falling?
• A skateboarder descends on a ramp from 172 feet to 67 feet in 15 seconds. What is the average change in height per second?
• In 2016, scientists confirmed which phenomenon first predicted by Einstein exactly 100 years earlier?
• What units is torque measured in?
• An object with a mass of # 2 kg# is traveling in a circular path of a radius of #4 m#. If the object's angular velocity changes from # 3 Hz# to # 4 Hz# in # 2 s#, what torque was applied to the object?
• A ball with a mass of #4 kg # and velocity of #2 m/s# collides with a second ball with a mass of #2 kg# and velocity of #- 4 m/s#. If #20%# of the kinetic energy is lost, what are the final velocities of the balls?
• What is the value of #1.875# in fractional form?
• If the circumference of a circle is 25cm, what is its Diameter?
• How do you find the x and y-intercept given #y=-2x+5#?
• How do you plot the points in a coordinate plane; A(9, -2)?
• How do you find the intercepts for #y=8x-3#?
• In a standard coordinate plane, what is the y-intercept of a line that passes through the points (3,17) and (5, 29)?
• Points A(1,2), B(2,3), and C (3,6) lie in the coordinate plane. What is the ratio of the slope of line AB to the slope of line AC?
• How do you graph #y = |x - 1|# by plotting points?
• How do you graph #-4x+5y=-20# by plotting points?
• How do you solve for y in #18x-2y=26#?
• What is a solution to the differential equation #dy/dx=x+y#?
• How do you solve #y'=-xy+sqrty# given y(0)=1?
• What is the general solution of the differential equation #(x+y)dx-xdy = 0#?
• What is the general solution of the differential equation #y' - (2xy)/(x^2+1) = 1#?
• What is the general solution of the differential equation # dy/dx = 8sin2x #?
• How can I solve this differential equation? : # xy \ dx-(x^2+1) \ dy = 0 #
• How do you find the length of a curve in calculus?
• How do you find the interval of convergence #Sigma x^(2n)/(n*5^n)# from #n=[1,oo)#?
• Using the integral test, how do you show whether #sum 1/sqrt(n+1)# diverges or converges from n=1 to infinity?
• How do you show whether the improper integral #int dx / [(lnx)^2]# converges or diverges from e to infinity?
• A line segment has endpoints at #(7 ,4 )# and #(2 ,6)#. If the line segment is rotated about the origin by #(3pi )/2 #, translated vertically by #3 #, and reflected about the x-axis, what will the line segment's new endpoints be?
• Two corners of an isosceles triangle are at #(6 ,6 )# and #(2 ,7 )#. If the triangle's area is #36 #, what are the lengths of the triangle's sides?
• Two opposite sides of a parallelogram each have a length of #9 #. If one corner of the parallelogram has an angle of #(3pi)/8 # and the parallelogram's area is #72 #, how long are the other two sides?
• A triangle has two corners with angles of # ( pi ) / 2 # and # ( 5 pi )/ 12 #. If one side of the triangle has a length of #14 #, what is the largest possible area of the triangle?
• An isosceles triangle has a base of 12 cm with equal sides of 20 cm each. How do you determine the area of this triangle accurate to the nearest square centimeter?
• Two opposite sides of a parallelogram each have a length of #16 #. If one corner of the parallelogram has an angle of #(5 pi)/8 # and the parallelogram's area is #12 #, how long are the other two sides?
• Two opposite sides of a parallelogram each have a length of #1 #. If one corner of the parallelogram has an angle of #(3 pi)/4 # and the parallelogram's area is #5 #, how long are the other two sides?
• In a triangle ABC, if angle B is obtuse, what types of angles can angles A and C be?
• A parallelogram has sides with lengths of #15 # and #8 #. If the parallelogram's area is #24 #, what is the length of its longest diagonal?
• The sides AB,BC,CA of a triangle ABC have 3,4,5 interior points respectively on them. Find the total number of triangles that can be constructed by using these points as vertices ?
• How do you evaluate #abs(-18)/2timesabs32/abs4#?
• What is the lowest common multiple of #5, 7 and 10#?
• How do you find the GCF of 66, 90, and 150?
• How do you find the GCF of #24t^2, 32#?
• How do you write the expression #(-t)(-t)(-t)# using exponents?
• How do you multiply and simplify #(- 3x ^ { 3} y ^ { 4} z ^ { 3} ) ^ { 3} ( 2y z ^ { 2} )#?
• Find the value of #216^(-1/15)#?
• The teacher gave 4 sandwiches to 9 students to share . if the students share the sandwiches equally. How many sandwiches would each student get?
• Is -6.7 a rational number?
• What is the GCF of 35 and 49?
• How do you determine if #x-sin(x)# is an even or odd function?
• How do you determine if #f(x) = sin2x# is an even or odd function?
• How do you solve #2^x= 4^(x+1)#?
• How do you find the vertical, horizontal or slant asymptotes for #x/(1-x)^2#?
• How do you find the vertical, horizontal or slant asymptotes for #f(x)=(2x)/sqrt (9x^2-4)#?
• How do you find the range of #y = 1 + (x/(x^2+1))#?
• What is #(80x^4 + 48x^3 + 80x^2) -: 8x#?
• How can I determine whether a given graph represents a function?
• How do you find the inverse of #f(x)=x^2 - 1# and is it a function?
• How do you solve #ln (x – 2) + ln (x + 2) = ln 5#?
• What is a pooled variance?
• What is the z-score of sample X, if #n = 81, mu= 43, St. Dev. =90, and E[X] =57#?
• How high can a p value be?
• Suppose that the temperature is normally distributed with expectation 50℃ and variance 4℃.What is the probability that the temperature T will be between 48℃ and 53℃?What is the probability that T≥52℃?
• The camera club has five members, and the mathematics club has eight. There is only one member common to both clubs. In how many ways could a committee of four people be formed with at least one member from each club?
• On a spinner, #P(3) = 2/5# and the #P(4) = 3/8#, what is the probability of getting 3 or 4?
• What is the mean, mode median and range of 11, 12, 13, 12, 14, 11, 12?
• When a event is reported, the probability that is a negative event is 30%. What is the probability that 3 out of 5 reported events are negative?
• How many permutations are there of the letter in the word baseball?
• A lottery has a $100 000 first prize, a $25 000 second prize, and five $500 third prizes. A total of 50000 tickets are sold. What is the probability of winning a prize in this lottery?
• How do you find the period of #sin 4x#?
• Can somebody help me solve this please? Thanks in advance!
• What is y=3sinx+4cosx in arccos?
• How do I make an equation for a cosine function with an amplitude of 0.5 and a period of 0.2pie?
• What is the length of the hypotenuse of a right triangle whose legs have lengths of 5 and 12?
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Training interactive robots may one day be an easy job for everyone, even those without programming expertise. Roboticists are developing automated robots that can learn new tasks solely by observing humans. At home, you might someday show a domestic robot how to do routine chores. In the workplace, you could train robots like new employees, showing them how to perform many duties.

Making progress on that vision, MIT researchers have designed a system that lets these types of robots learn complicated tasks that would otherwise stymie them with too many confusing rules. One such task is setting a dinner table under certain conditions.  

At its core, the researchers’ “Planning with Uncertain Specifications” (PUnS) system gives robots the humanlike planning ability to simultaneously weigh many ambiguous — and potentially contradictory — requirements to reach an end goal. In doing so, the system always chooses the most likely action to take, based on a “belief” about some probable specifications for the task it is supposed to perform.

In their work, the researchers compiled a dataset with information about how eight objects — a mug, glass, spoon, fork, knife, dinner plate, small plate, and bowl — could be placed on a table in various configurations. A robotic arm first observed randomly selected human demonstrations of setting the table with the objects. Then, the researchers tasked the arm with automatically setting a table in a specific configuration, in real-world experiments and in simulation, based on what it had seen.

To succeed, the robot had to weigh many possible placement orderings, even when items were purposely removed, stacked, or hidden. Normally, all of that would confuse robots too much. But the researchers’ robot made no mistakes over several real-world experiments, and only a handful of mistakes over tens of thousands of simulated test runs.  

“The vision is to put programming in the hands of domain experts, who can program robots through intuitive ways, rather than describing orders to an engineer to add to their code,” says first author Ankit Shah, a graduate student in the Department of Aeronautics and Astronautics (AeroAstro) and the Interactive Robotics Group, who emphasizes that their work is just one step in fulfilling that vision. “That way, robots won’t have to perform preprogrammed tasks anymore. Factory workers can teach a robot to do multiple complex assembly tasks. Domestic robots can learn how to stack cabinets, load the dishwasher, or set the table from people at home.”

Joining Shah on the paper are AeroAstro and Interactive Robotics Group graduate student Shen Li and Interactive Robotics Group leader Julie Shah, an associate professor in AeroAstro and the Computer Science and Artificial Intelligence Laboratory.

Bots hedging bets

Robots are fine planners in tasks with clear “specifications,” which help describe the task the robot needs to fulfill, considering its actions, environment, and end goal. Learning to set a table by observing demonstrations, is full of uncertain specifications. Items must be placed in certain spots, depending on the menu and where guests are seated, and in certain orders, depending on an item’s immediate availability or social conventions. Present approaches to planning are not capable of dealing with such uncertain specifications.

A popular approach to planning is “reinforcement learning,” a trial-and-error machine-learning technique that rewards and penalizes them for actions as they work to complete a task. But for tasks with uncertain specifications, it’s difficult to define clear rewards and penalties. In short, robots never fully learn right from wrong.

The researchers’ system, called PUnS (for Planning with Uncertain Specifications), enables a robot to hold a “belief” over a range of possible specifications. The belief itself can then be used to dish out rewards and penalties. “The robot is essentially hedging its bets in terms of what’s intended in a task, and takes actions that satisfy its belief, instead of us giving it a clear specification,” Ankit Shah says.

The system is built on “linear temporal logic” (LTL), an expressive language that enables robotic reasoning about current and future outcomes. The researchers defined templates in LTL that model various time-based conditions, such as what must happen now, must eventually happen, and must happen until something else occurs. The robot’s observations of 30 human demonstrations for setting the table yielded a probability distribution over 25 different LTL formulas. Each formula encoded a slightly different preference — or specification — for setting the table. That probability distribution becomes its belief.

“Each formula encodes something different, but when the robot considers various combinations of all the templates, and tries to satisfy everything together, it ends up doing the right thing eventually,” Ankit Shah says.

Following criteria

The researchers also developed several criteria that guide the robot toward satisfying the entire belief over those candidate formulas. One, for instance, satisfies the most likely formula, which discards everything else apart from the template with the highest probability. Others satisfy the largest number of unique formulas, without considering their overall probability, or they satisfy several formulas that represent highest total probability. Another simply minimizes error, so the system ignores formulas with high probability of failure.

Designers can choose any one of the four criteria to preset before training and testing. Each has its own tradeoff between flexibility and risk aversion. The choice of criteria depends entirely on the task. In safety critical situations, for instance, a designer may choose to limit possibility of failure. But where consequences of failure are not as severe, designers can choose to give robots greater flexibility to try different approaches.

With the criteria in place, the researchers developed an algorithm to convert the robot’s belief — the probability distribution pointing to the desired formula — into an equivalent reinforcement learning problem. This model will ping the robot with a reward or penalty for an action it takes, based on the specification it’s decided to follow.

In simulations asking the robot to set the table in different configurations, it only made six mistakes out of 20,000 tries. In real-world demonstrations, it showed behavior similar to how a human would perform the task. If an item wasn’t initially visible, for instance, the robot would finish setting the rest of the table without the item. Then, when the fork was revealed, it would set the fork in the proper place. “That’s where flexibility is very important,” Ankit Shah says. “Otherwise it would get stuck when it expects to place a fork and not finish the rest of table setup.”

Next, the researchers hope to modify the system to help robots change their behavior based on verbal instructions, corrections, or a user’s assessment of the robot’s performance. “Say a person demonstrates to a robot how to set a table at only one spot. The person may say, ‘do the same thing for all other spots,’ or, ‘place the knife before the fork here instead,’” Ankit Shah says. “We want to develop methods for the system to naturally adapt to handle those verbal commands, without needing additional demonstrations.”  

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• Paper: “Planning With Uncertain Specifications (PUnS)”
• Paper: “Bayesian Interference of Temporal Task Specifications from Demonstrations”
• Ankit J. Shah
• Interactive Robots Group
• Computer Science and Artificial Intelligence Laboratory
• Department of Aeronautics and Astronautics

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• Artificial intelligence
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• Computer Science and Artificial Intelligence Laboratory (CSAIL)

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This AI-powered robot has worked out how to solve a Rubik's Cube in just 0.305 seconds

Footage shows the record-breaking TOKUFASTbot solving a Rubik's Cube so fast that it appears to happen in a single move. But in reality, advanced AI is helping it rapidly turn the puzzle's colored panels in an imperceptibly fast sequence.

A Japanese robot has solved a Rubik's Cube in world record time, thanks in part to artificial intelligence (AI) that helps it to distinguish between the puzzle's colored panels, new footage shows. The entire process happens in less time than the blink of a human eye .  

The record-breaking robot, "TOKUI Fast Accurate Synchronized Motion Testing Robot" (TOKUFASTbot), was created by Japan's Mitsubishi Electric Corporation to help improve factory automation equipment used in electronics production. 

It has six arms connected to a multi-axis motor and a high-speed camera, both of which are connected to an industrial computer . The system is capable of turning each arm 90 degrees in just 0.009 seconds, Mitsubishi representatives said in a statement .

On May 21, TOKUFASTbot solved a rotating 3x3x3 "puzzle cube" in 0.305 seconds, setting a new world record, according to Guinness World Records . The previous record time was 0.38 seconds, which was set by an MIT robot in 2018 . For comparison, a human blink takes between 0.1 and 0.4 seconds, according to Harvard University's bionumbers database .

The new record is around 10 times quicker than the record for a human solving the puzzle — 3.13 seconds, set by Max Park in June 2023 . 

In the Mitsubishi video, which uses slow-motion cameras to show the robot in action, TOKUFASTbot solved a puzzle cube even faster — in 0.204 seconds — on May 7 using around 15 moves. However, this attempt did not adhere to the "measurement rules" set out by Guinness World Records so it does not count, Mitsubishi representatives wrote in the video's YouTube description.

Related: 32 times artificial intelligence got it catastrophically wrong

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Due to a historic trademark that was recently overturned, the cubes used in record attempts are simply referred to as puzzle cubes, Ars Technica reported . However, the objects are almost certainly all Rubik's Cubes — the iconic toys created in 1974 by Hungarian sculptor and architect Ernő Rubik, who took a month to solve the first cube (largely because it had no colors).

Solving the Rubik's Cube, which has more than 43 quintillion possible combinations, is a great test of dexterity and computing power. As a result, robotics engineers have been competing to see how quickly their creations can complete the puzzles.

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Apart from the speed of the machinery, the main limitation is how quickly the robots' computer systems can process information. But TOKUFASTbot excels in this area thanks to an AI system that helps it distinguish between the colors on the cubes' panels by factoring in minute changes caused by positioning, lighting and shadows that can trip up a standard color sensor, Ars Technica reported.

Just like humans, the hardest colors for AI's to distinguish between are red and orange because the wavelengths of these colors are closer together than any other color combination, Ars Technica reported. However, TOKUFASTbot's AI was able to quickly overcome this problem.

Harry is a U.K.-based senior staff writer at Live Science. He studied marine biology at the University of Exeter before training to become a journalist. He covers a wide range of topics including space exploration, planetary science, space weather, climate change, animal behavior, evolution and paleontology. His feature on the upcoming solar maximum was shortlisted in the "top scoop" category at the National Council for the Training of Journalists (NCTJ) Awards for Excellence in 2023. 

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This bot will do your homework for $9.95 a month. Does it actually work?

According to one 10th-grade history teacher, it’s unlikely to get you an A.

by Luke Winkie

“EssayBot is the highly acclaimed online platform giving essay writing assistance to students and subject authors. As the program has been produced with the most sophisticated tools and technologies, it is extremely automated and individualized. This US-based corporation works with the only purpose to give honest and convincing aid to authors for creating superior volumes that will get rewards and praises.”

That’s what EssayBot says when I asked it to describe itself. The service aims to be the holy grail for the world’s burnout 11th-graders. Type in your prompt — any prompt, from your history assignment to the question “what is EssayBot?” — and the machines get to work.

“To give honest and convincing aid to authors for creating superior volumes that will get rewards and praises”

Your opening paragraph is pulled whole cloth from a database of scholastic material. Then the diction is gently rephrased, with synonyms swapped in for non-essential words, until it can fly under the radar of the average plagiarism detector. From there, you can import a laundry list of additional paragraphs related to the subject of your essay, or you can use a drop-down menu called a “sentence creator,” perched patiently next to your blinking cursor. Write a word and EssayBot does its best to think up a sensible follow-up clause, based on the contours and language of what you’ve already got written down. All this for only $9.95 a month, or $49.95 a year. If you’ve ever spent a sleepless school night staring at an empty Word doc, you know what it’s like to be desperate enough to pay up.

I discovered EssayBot via YouTube ad, and when I put the site’s name into Google, I found hundreds of cautiously hopeful students taking to forums and review sites over the past year, asking if EssayBot is too good to be true. Procrastinating teens are an underserved market.

Aaron Yin, the proprietor of EssayBot, has been trying to sell AI text generation for years with limited success. His first attempt came in 2017 with a service that automatically constructed résumés, and the tech infrastructure of EssayBot was initially intended to help small businesses generate branding copy. But that angle never took off. Instead, Yin needed to find a hungrier demographic, and the millions of young men and women on a humanities deadline were a match made in heaven. “We use the same technology [from the business writing] for EssayBot,” he says. “To help students write essays.”

Yin considers EssayBot to be a streamlined version of what kids are already doing with their papers. He tells me he held focus groups full of college kids during EssayBot’s initial development and found that they all used similar tactics to write their essays. They would research and copy down the finer points of the arguments they wanted to use, they would reword those passages, and they turned to Google Scholar to find citations. If you’re extremely generous in your interpretation, you can argue that EssayBot is essentially a harmless mechanization of the academic process — rather than, you know, cheating. “The technology is actually a little similar to translation,” says Yin. “You’re putting something in a different way.”

“The technology is actually a little similar to translation. You’re putting something in a different way.”

There’s reason to believe what Yin is selling. In 2019, AI text generation is closer to the mainstream than ever. In February, there was a brief mania over the Elon Musk-backed company OpenAI and its silver-tongued text generator. Journalists from Wired , the Guardian , The Verge , and Vox were all invited to play with the fancy new algorithm that could generate cohesive short stories with reasonably consistent clarity. The generator has yet to be released to the public, with OpenAI claiming that it was “too dangerous” in our current Facebook-poisoned news culture. No matter how hyperbolic that warning might be, it seemed we were fast approaching a world where machines could demand column space.

• An AI helped us write this article

It’s a reality echoed by Neil Yager, the chief scientist and co-founder of Phrasee , an AI platform that formulates ideal, scientifically precise email headlines for press releases and marketing campaigns. He says that whether we realize it or not, we’re already reading a fair amount of computer-generated text as part of our media diet. “In things like weather reports, it’s called data to text. You take some numbers, like the humidity and temperature, and use an algorithm to automatically to spin that into a story,” he explains. “You have some simple logic in there. ‘If the temperature is above this, then say that it’s going to be a warm day.’ Robo-journalism is quite a big field.”

Still, it was difficult to believe that technology could adequately replicate a standard five-paragraph high school essay. Sure, EssayBot was able to introduceitself in its own uncanny syntax, but that was easy. How would it hold up in the eyes of a wary teacher? So I got my hands dirty in the EssayBot module and resolved to craft an essay about Brown v. Board of Education , a Supreme Court case any American student will inevitably write about at least once during their academic career.

The results were uneven. The language and the facts were mostly reasonable, but the overall narrative was jumbled.

EssayBot gave me a rock-solid opening paragraph, after which I was presented with a suite of additional paragraphs I could plug into the copy. As before, each of those paragraphs was plucked from the web and rephrased into something less plagiaristic by the site’s algorithm. I continued that process until I had about 700 words that tracked the basics of the trial and some light analysis about segregation in the public school system today. The results were uneven. The language and the facts were mostly reasonable, but the overall narrative was jumbled. The essay wasn’t tethered to a concrete thesis and read like a loose distillation dreamed up by an entity that knew all the information but wasn’t able to synthesize it into an authentic argument.

I decided to use the automatic sentence creator to fill out the conclusion, where things got funnier, and more dire. The sentences themselves were grammatically correct, but they’d often contradict each other within the text. At one point, EssayBot wanted to add “the solution is to change the way schools are run,” exactly one sentence after it added “the solution isn’t to simply change the way schools are run.” It figures that when you ask something non-sentient to write for you, you can expect something non-sentient in return.

So, naturally, when I emailed the essay to my 10th-grade history teacher Mr. Lourey, he gave it an easy F.

”The paper would probably earn a very low score in most classes, because it doesn’t seem to be clearly answering a prompt,” he wrote. “I guess if a teacher assigned a short essay that asked students to simply summarize an event, then maybe this type of paper could fly under the ‘teacher radar.’ But most properly designed writing prompts on civil rights would ask students to make some sort of original claim … even if I did not identify the paper as a creation of AI, it would earn a failing grade.”

“Even if I did not identify the paper as a creation of AI, it would earn a failing grade”

His reaction didn’t surprise me, nor did it surprise Yager. An AI text generator like EssayBot is simply incapable of responding to a multifaceted essay proposal with a human point of view. Your best bet is simulacrum, and simulacrum can break down very, very quickly. In fact, Yager says Phrasee’s AI model starts to degenerate after about 150 words or so.

Algorithms “don’t write like how you or I would write an essay. It doesn’t think, ‘Okay, here’s my idea, and here’s how I’m going to argue this point.’ Instead, it’s writing one word at a time with no idea where it’s going,” he explains. “There’s no understanding there. It’s not trying to get any point across; any point it makes is purely random and accidental. That’s the limitation of the technology today. … It studies the statistical properties of the language and can generate new text that shares those properties.”

That said, Yager is a little concerned about the future. As tools like EssayBot get better and more AI software hits the market, there will eventually come a moment, he says, where text generation will be a major concern for academia. “Technology is going to help people cheat. It’ll be a bit of an arms race. Things will improve over time, and so will the detection methods,” he says. “Even now, though it’s not great quality, I bet people are getting away with it.”

Yin, of course, would never call EssayBot software for cheaters, and he says that over the past year, he’s only ever gotten one angry email from a teacher. He points to a service called Chegg , which provides specific answers to classroom textbook questions for $15 a month. EssayBot, in his comparison, is a research tool rather than a flat, rote cheat sheet. A shortcut rather than misconduct.

”A student could use Chegg [to answer a problem,] and after graduation, if they saw a similar question, they still couldn’t do it,” says Yin. “With EssayBot, after graduation, if a student became a marketing specialist and write marketing material, they could still use EssayBot.”

Perhaps one day we might need to formally establish the parameters for how much a robot is allowed to assist you in the writing process. Until then, be careful with the machines. They might just flunk you.

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How to build your own robot friend: Making AI education more accessible

by Caitlin Dawson and Rania Soetirto, University of Southern California

From smart virtual assistants and self-driving cars to digital health and fraud prevention systems, AI technology is transforming almost every aspect of our daily lives—and education is no different. For all its promise, the rise of AI, like any new technology, raises some pressing ethical and equity questions.

How can we ensure that such a powerful tool can be accessed by all students regardless of background?

Inspired by this call to action, USC researchers have created a low-cost, accessible learning kit to help college and high school students build their own "robot friend." Students can personalize the robot's "body," program the robot to mimic their head posture, and learn about AI ethics and fairness in an engaging, accessible way.

"We're proposing this open-source model to not only improve education in AI for all students but also to make human-interaction research more affordable for labs and research institutions," said Shi. "Ultimately, we want to increase access to human-centered AI education for college students and create a pathway to more accessible research."

To reduce costs and development time for learners, the team customized and simplified Blossom, a small, open-source robot originally developed by Hoffman at Cornell University. Blossom is a common fixture in USC's Interaction Lab—Shi previously used the robot to design better AI voices for mindfulness exercises, while O'Connell programmed it to act as a "study buddy" for students with ADHD symptoms.

Last year, the duo began to devise ways to use the robot for educational purposes and set to work creating a low-cost, customizable and "human-focused" module that could mirror some of the ways that students will interact with technology in their everyday lives.

The system is outlined in a new study, titled " Build Your Own Robot Friend: An Open-Source Learning Module for Accessible and Engaging AI Education ," which appears on the pre-print server arXiv and was presented at the AAAI Conference on Artificial Intelligence, education symposium track.

"We believe it is important for students to learn about fairness and ethics in AI in the same way that we learned about math and physics in K-12," said co-lead author Zhonghao Shi, a doctoral student in computer science who conducts his research in the USC Interaction Lab led by Professor Maja Matarić.

"We may not use these subjects every day, but having a basic understanding of these concepts helps us do better work and be mindful of new technologies."

Hands-on experience

The three-part open-source learning module provides students with hands-on experience and introductory instruction about various aspects of AI, including robotics, machine learning, software engineering, and mechanical engineering. It helps to address a gap in the market for AI education, said Shi and O'Connell.

Currently, pre-built robots, such as the NAO, are unaffordable for schools with limited resources, while educational robot kits, such as LEGO Mindstorms, though affordable, do not adapt to students at different levels.

To make the robot more affordable, they developed strategies to subsidize its cost. In the version of Blossom presented in the study, the materials are created using 3D printers, instead of more costly laser printing. Currently, one of the team's customizable robots costs around $250 to make. In comparison, a NAO robot runs at around $15,000.

O'Connell, who learned to crochet during the pandemic, designed five new Blossom exteriors and created detailed, easy-to-follow patterns and tutorials for each version, including a baby onesie, knitted and crocheted options, which are all low-cost and customizable.

After constructing their robot friend, students are encouraged to further customize Blossom with, for instance, mechanical eyebrows, color-changing lights, or even an expressive face screen. For O'Connell, creativity has been a crucial part of her own engineering journey.

"Crafting and engineering require similar strengths like counting, planning, and spatial reasoning," said O'Connell. "By incorporating crafting into this project, we hope to draw in creative students who might not have considered how their skills align with robotics and engineering."

Understanding ethics and fairness

The system was piloted in a two-day workshop in May 2023 with 15 undergraduate college students from a local minority-serving institution. Four teams of students constructed Blossom robots following the learning module assembly guide with blank knitted exterior to personalize with accessories. On the second day, the students used pre-trained head pose tracking and gesture recognition models to detect and mimic nodding behaviors from the user.

From post-workshop surveys, they found that 92% of the participants believed that the workshop helped them learn more about the topics covered and all the participants believed that the workshop encouraged them to study more about robotics and AI in the future.

"Equipping users with AI literacy, including an understanding of AI ethics and fairness, is crucial to avoid unintended discrimination against marginalized groups," said Shi.

In continued work, the team plans to further evaluate and improve the module for high school students and K-12 students. Ultimately, the researchers hope to expand access for students at different educational levels.

"We're excited to share more about our project with people from around the world," Shi said. "We want to make sure that people from different kinds of socioeconomic backgrounds have the opportunity to gain an education on AI and participate in the process of improving AI for future use."

Journal information: arXiv

Provided by University of Southern California

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The Use of Robotics and Simulators in the Education Environment

Advances in technology continue to push the envelope in healthcare, travel, communication and education. The use of robotic and simulation technologies have proven themselves to be worthy components of available educational resources. These technologies use in the education environment have shown their value in everyday learning and in the specialized education of students with disabilities.

Robotics and Simulators in Education

The use of robotics has allowed complicated medical procedures to be simplified, the work of dangerous construction projects to be safer and the discovery of our universe to be possible. When applied to education, robotics and simulators can change the way students learn and ultimately create a more knowledgeable and well-adjusted student.

Elementary and High School Education

• Robotics – Robots can be used to bring students into the classroom that otherwise might not be able to attend. In New York, a second grader with severe, life-threatening allergies was unable to attend school due to his condition. A four-foot-tall robot provided a ‘real school’ experience for the boy, ‘attending’ school and bringing the boy with him via an internal video conferencing system. Robots such as the one mentioned are able to ‘bring school’ to students who cannot be present physically.
• Simulators – High school sees the strongest example of simulators within drivers’ education courses. Simulators provide a true-to-life experience while removing any real dangers or risk from scenarios. In drivers’ education, students can experience the feeling of being behind the wheel without ever leaving the safety of the classroom. Simulators offer a chance for ‘what if’ scenarios, which can better prepare student drivers for real-life hazards and obstacles on the roadway.

Higher Education

• Robotics – Many careers require specialized knowledge in delicate practices, specifically in the realm of healthcare. When receiving a medical education, many students find benefits in the use of robotics. When learning to perform complicated medical procedures, a human subject isn’t feasible, so educators are employing the use of robots as stand-ins. Robots can be created and programmed to give off all indications of human life, including breath and heartbeat. Their use can also be seen in such procedures as injections, surgeries and even delivering children.
• Simulators – Simulation technology is utilized in a variety of college degree focuses, offering 360 degree real-life scenarios and 3D projections of real experiences. In addition to providing medical students with the means for thorough exploration of the human body, simulators also provide exceptional methods of crisis and disaster training for emergency response and law enforcement trainees. These types of all-encompassing simulators offer a choice and response technology, requiring officers to make split-second decisions and immediately see the ramifications of their actions. These types of scenarios can include violent altercations or behind-the-wheel high-speed chases.

Special Education

• Robotics – Students with special requirements are reaching new levels of learning through the use of robotics in the classroom. With these technologies children with autism are learning communication and social skills and students with developmental issues and attention disorders are learning focus. Individuals with severe physical disabilities are also offered a constant companion and health monitoring system – all through the use of robotics. Robots can be programmed to suit each individual child’s need, offering special education in a much simpler, accessible format.
• Simulators – Simulators are able to offer students with special needs an introduction to real-world scenarios in a non-threatening environment. Everyday lessons can be taught at a comfortable pace, including subjects ranging from basic self-care to stay-safe techniques in emergency situations. Simulators have also provided a way for special education educators to see the world from their students’ perspectives, including hearing-impaired or blind simulations.

Assistive technology is growing, and the abilities it provides to special education students are limitless. Simulation and robotics technologies offer a range of possibilities within education, with a helpful solution for every student’s learning needs. As the technological world unveils new innovations daily, the educational world will continue to benefit from the opportunities offered with these groundbreaking tools.

You can help shape the influence of technology in education with an Online Master of Science in Education in Learning Design and Technology from Purdue University Online. This accredited program offers studies in exciting new technologies that are shaping education and offers students the opportunity to take part in the future of innovation.

Learn more about the online MSEd in Learning Design and Technology at Purdue University today and help redefine the way in which individuals learn. Call (877) 497-5851 to speak with an admissions advisor or request more information.

How To Make A Robot: Ultimate Guide [Updated 2020]

• How-To Guides
• Tech Setup & Troubleshooting

Building a robot at home is not as hard as it seems at first glance. Robots are in use all around us while many people do not realize that learning how to make a robot does not require expertise in electronics and computer programming. In fact, making a robot is easier than you expect.

This is because even experts of the think of robots as intelligent systems while the definition of a robot says these are machines that are able to carry out a complex series of actions automatically. In this sense, your electric toothbrush is also a robot as it automatically performs a series of actions your grandfather had performed manually.

Actually, nearly half of all manual and physical world activity is forecast to be performed by robots by 2022, according to the World Economic Forum.

Will Robots Replace Humans At Work?

We now make robots as sophisticated that they can perform many activities once considered only doable by humans and robotic machines are entering even more fields as artificial intelligence and machine learning algorithms mature.

Nonetheless, those who are interested in how do you make a robot should be aware that more sophisticated robots really require advanced knowledge in electronics and coding as well as access to industrial equipment to build such robots. Nonetheless, you will show you how to build a robot at home following a number of easy steps.

How To Make A Robot: Design Aspects

When you start studying how to make your own robots, you realize that you can actually assemble a robot in an hour or so and without having access to very advanced technology. Making robots is about using a power source, moving parts and, most important, attaching sensors that tell your robot what actions to perform.

When you are advancing your knowledge of how to build a real robot, you also learn that it does need coding either – sensors can do the work at the level of physical actions and without a single line of programming code.

A robotic vacuum cleaner, for instance, does not require artificial intelligence to operate. And we will show you how to build a real robot that resembles the movement of a 1,000-dollar automated vacuum cleaner by using parts that cost only a few bucks.

How To Make A Robot For Under $100

Your robotic vacuum cleaner is looking smart as it is driving around the house bypassing obstacles and turning right or left when hitting a wall. You can build a real robot like that using just five simple components:

• Four wheels
• Four switches
• Four paperclips

Do not forget to buy also a battery to power up your first home-made robot.

When you have all the parts in place, take your time to attach the four wheels to the chassis of your first robot. The result is look like the one on the image below.

Now comes the fun part – how to make a robot that acts intelligently .

How To Build A Self-Driving Robot

Well, our robot will not exactly avoid walls but will drive back when it hits one and will then head in a new direction. Which is actually smart enough for a beginner engineer. 

Our robot’s design sports two small electrical engines that each power up the wheels on the left side and on the right side of the car, respectively. You can attach them to only one pair of wheels, with the first motor powering one left-side wheel and the other driving its neighbor on the right side.

Thus, you can add switches to each engine that reverse the wheels’ motion direction. You are adding one switch to the front and the back of your chassis – two on the left side and two on the right side. After you have the switches in place, you need sensors to activate them.

Attach one paperclip to each switch. You can actually make it work by attaching a longer hardwire to each switch but make sure it moves back and forth when pressed in order for the switch to work.

Then, comes the time to add the battery which you fix somewhere on the chassis.

How To Build A Robot’s Chassis

It is simple. Let’s name the four corners of our robot’s chassis A, B, C, and D – starting from the upper-left corner and going clockwise.

When sensor A hits a wall or another obstacle, it reverses the wheeling direction of the left-sided wheels (or wheel) backward. The right-sided wheels are still rotating toward the wall. Hence, the wheels on the two sides of the car are rotating in opposite directions.

The result is that your robot vehicles start to turn back and on the left. When it completes the turn, the paperclip in point D hits the wall, thus switching the direction of rotation of left-sided wheels once again. Now, the wheels on both sides rotate in the same direction and your “smart” robot is heading forward at full speed.

Concluding Words

You now can enjoy your first robot, but be on alert that your intended robotic application will determine the whole robot design of any machine. For instance, you do not put wheels on a robot that will roam a swampy land shaft and you do not need legs for a robot that works in outer space where no gravity is available.

People often associate robots with androids but when you decide how to build a real robot the anthropoid design should be your least concern. Building a robot at home should follow these basic principles of robotics that put function before design.

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Manipulation technology makes home-helper robot possible

by Kaitlyn Landram

New locomotion and manipulation technology from Ding Zhao’s lab will enable four-legged robots to lend a hand in the not-so-distant future.

Parents spend roughly 300 hours each year cleaning up after their kids. That’s nearly two weeks that could be otherwise spent doing, well, anything else. Researchers in Carnegie Mellon University’s Department of Mechanical Engineering , in collaboration with Google DeepMind and the University of Washington, are hopeful that parents will regain tidying time and then some with LocoMan , a four-legged version of the Jetsons’ beloved maid “Rosey the Robot,” that could lend a hand in the not-so-distant future.

Quadrupedal robots, designed to move on four legs much like a dog, are already found leading search and rescue missions, surveying construction sites, and moving parts around factories. Their ability to navigate complex environments with a low center of gravity and light weight make quadrupedal robots a top contender for household use, too. Until now, the missing piece was the dexterity and versatility skills necessary for them to be efficient in daily life.

By installing two custom-designed, lightweight manipulators (think robot arms) onto the front legs of a quadrupedal robot, Ding Zhao has created a robot versatile enough to open doors, pour drinks, plug a phone in to charge, and—perhaps best of all—clean up after your on-the-go toddlers.

While many researchers work on humanoid robots that look like humans, with potential to directly learn from humans or even replace humans in some tasks, we focus on robots that are complementary to humans to team up with them. Ding Zhao , Associate Professor , Mechanical Engineering

“While many researcher work on humanoid robots that look like humans, with potential to directly learn from humans or even replace humans in some tasks, we focus on robots that are complementary to humans to team up with them,” said Zhao, associate professor of mechanical engineering.

Unlike humanoid robots that come at a high cost and hefty weight, Zhao’s manipulators can be added to existing lower-cost quadrupedal robots and are compact, lightweight, and easy to fabricate, making them an accessible technology.

The core idea is to leverage the leg as an integral component of the “robotic arm” for executing 6D pose manipulation.

“We used four commercially available servos and 3D printed a few other parts to bring them to life,” Changyi Lin, a Ph.D. candidate in the CMU Safe AI Lab and the first author of the paper explained.

Zhao’s team introduced the robot to a class of five preschool students at The Cyert Center for Early Education. After explaining to children how robots work and what we use them for, the children had the opportunity to interact with Zhao’s robot. The students were impressed with the robot’s capabilities and didn’t want it to leave their classroom.

Ding Zhao (center), with children from the Cyert Center, interacting with the home-helper robot.

The group continues to develop LocoMan to perform tasks autonomously by integrating advanced perception and intelligence planning capabilities into its existing whole-body controller.

“We anticipate that robots like LocoMan will be ready to help out at home, or in daycares, within the next three years,” said Zhao. “It is a pleasant job just to imagine that I may no longer need to handle my kids’ messy fun.”

This work will be presented at the loco-manipulation workshop and the manipulation skills workshop of the 2024 IEEE International Conference on Robotics and Automation.

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How to Build a Robot at Home

Last Updated: June 2, 2024 Fact Checked

wikiHow is a “wiki,” similar to Wikipedia, which means that many of our articles are co-written by multiple authors. To create this article, 88 people, some anonymous, worked to edit and improve it over time. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 1,792,600 times. Learn more...

Do you want to learn how to build your own robot? There are a lot of different types of robots that you can make by yourself. Most people want to see a robot perform the simple tasks of moving from point A to point B. You can make a robot completely from analog components or buy a starter kit from scratch! Building your own robot is a great way to teach yourself both electronics as well as computer programming.

Assembling the Robot

• Arduino Uno (or other microcontroller) [1] X Research source
• 2 continuous rotation servos
• 2 wheels that fit the servos
• 1 caster roller
• 1 small solderless breadboard (look for a breadboard that has two positive and negative lines on each side)
• 1 distance sensor (with four-pin connector cable)
• 1 mini push-button switch
• 1 10kΩ resistor
• 1 USB A to B cable
• 1 set of breakaway headers
• 1 6 x AA battery holder with 9V DC power jack
• 1 pack of jumper wires or 22-gauge hook-up wire
• Strong double-sided tape or hot glue

• The servos should now be taking up the back half of the battery pack.

• If you bought a kit, the caster may have come with a few risers that you can use to ensure the caster reaches the ground. i

Wiring the Robot

Wiring the Power

Installing the Arduino Software

Programming the Robot

• You may want to lift the robot off of the surface, as it will just continue to move forward once the program is uploaded.

• 1 Follow an example. The following code will use the sensor attached to the robot to make it turn to the left whenever it encounters an obstacle. See the comments in the code for details about what each part does. The code below is the entire program. #include <Servo.h> Servo leftMotor ; Servo rightMotor ; const int serialPeriod = 250 ; // this limits output to the console to once every 1/4 second unsigned long timeSerialDelay = 0 ; const int loopPeriod = 20 ; // this sets how often the sensor takes a reading to 20ms, which is a frequency of 50Hz unsigned long timeLoopDelay = 0 ; // this assigns the TRIG and ECHO functions to the pins on the Arduino. Make adjustments to the numbers here if you connected differently const int ultrasonic2TrigPin = 8 ; const int ultrasonic2EchoPin = 9 ; int ultrasonic2Distance ; int ultrasonic2Duration ; // this defines the two possible states for the robot: driving forward or turning left #define DRIVE_FORWARD 0 #define TURN_LEFT 1 int state = DRIVE_FORWARD ; // 0 = drive forward (DEFAULT), 1 = turn left void setup () { Serial . begin ( 9600 ); // these sensor pin configurations pinMode ( ultrasonic2TrigPin , OUTPUT ); pinMode ( ultrasonic2EchoPin , INPUT ); // this assigns the motors to the Arduino pins leftMotor . attach ( 12 ); rightMotor . attach ( 13 ); } void loop () { if ( digitalRead ( 2 ) == HIGH ) // this detects the kill switch { while ( 1 ) { leftMotor . write ( 90 ); rightMotor . write ( 90 ); } } debugOutput (); // this prints debugging messages to the serial console if ( millis () - timeLoopDelay >= loopPeriod ) { readUltrasonicSensors (); // this instructs the sensor to read and store the measured distances stateMachine (); timeLoopDelay = millis (); } } void stateMachine () { if ( state == DRIVE_FORWARD ) // if no obstacles detected { if ( ultrasonic2Distance > 6 || ultrasonic2Distance < 0 ) // if there's nothing in front of the robot. ultrasonicDistance will be negative for some ultrasonics if there is no obstacle { // drive forward rightMotor . write ( 180 ); leftMotor . write ( 0 ); } else // if there's an object in front of us { state = TURN_LEFT ; } } else if ( state == TURN_LEFT ) // if an obstacle is detected, turn left { unsigned long timeToTurnLeft = 500 ; // it takes around .5 seconds to turn 90 degrees. You may need to adjust this if your wheels are a different size than the example unsigned long turnStartTime = millis (); // save the time that we started turning while (( millis () - turnStartTime ) < timeToTurnLeft ) // stay in this loop until timeToTurnLeft has elapsed { // turn left, remember that when both are set to "180" it will turn. rightMotor . write ( 180 ); leftMotor . write ( 180 ); } state = DRIVE_FORWARD ; } } void readUltrasonicSensors () { // this is for ultrasonic 2. You may need to change these commands if you use a different sensor. digitalWrite ( ultrasonic2TrigPin , HIGH ); delayMicroseconds ( 10 ); // keeps the trig pin high for at least 10 microseconds digitalWrite ( ultrasonic2TrigPin , LOW ); ultrasonic2Duration = pulseIn ( ultrasonic2EchoPin , HIGH ); ultrasonic2Distance = ( ultrasonic2Duration / 2 ) / 29 ; } // the following is for debugging errors in the console. void debugOutput () { if (( millis () - timeSerialDelay ) > serialPeriod ) { Serial . print ( "ultrasonic2Distance: " ); Serial . print ( ultrasonic2Distance ); Serial . print ( "cm" ); Serial . println (); timeSerialDelay = millis (); } }

Community Q&A

• Attach 2 toothbrush heads to the base of your robot if you want it to sweep the floor. Thanks Helpful 1 Not Helpful 0

Tips from our Readers

• If you want to add more character to your robot, cut out eye, arms, and legs out of paper, then attach them with tape.
• Make sure to measure each part before buying so you don't have to return anything!

You Might Also Like

• ↑ https://www.makerspaces.com/arduino-uno-tutorial-beginners/
• ↑ https://learn.adafruit.com/Cardboard-Robot-Inchworm/add-the-electronics
• ↑ https://makezine.com/projects/building-a-simple-arduino-robot/
• ↑ https://www.sciencebuddies.org/science-fair-projects/references/how-to-use-a-breadboard
• ↑ https://support.arduino.cc/hc/en-us/articles/360019833020-Download-and-install-Arduino-IDE

About This Article

To build a simple robot that can move on its own, purchase a starter kit, or assemble the components you need from an electronics supplier. You'll need a microcontroller, the small computer that will serve as your robot's brain; a pair of continuous rotation servos to drive the wheels; wheels that fit the servos; a caster roller; a small solderless breadboard for building your circuits; a battery holder; a distance sensor; a push button switch, and jumper wires. Affix the servos to the end of the battery pack with double-sided tape or hot glue, making sure the the rotating ends of the servos are on the long sides of the battery pack. Attach the breadboard to the battery pack next to the servos with the tape or hot glue. Place the microcontroller on the flat space on top of the servos and affix firmly there. Press the wheels firmly onto the spindles of the servos. Attach the caster to the front of the breadboard. The caster spins freely, and acts as the front wheel of the robot, making it easy to turn and roll in any direction. Plug the distance sensor to the front of your breadboard. Wire up your robot, connecting the servos, microcontroller, switch and battery pack to your breadboard. Connect your microcontroller to a computer via a USB cable. Upload a basic control program from your computer to the microcontroller. This robot can go forward, backward, stop, and turn away from obstacles. Test your robot on a smooth flat surface, and experiment to see what you can make it do. For more tips, including how to use Arduino software, read on! Did this summary help you? Yes No

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Ultimate Guide to Homeschool Robotics

Look no farther than Kinvert’s Ultimate Guide to Homeschool Robotics. Which robots to get and which to avoid. Great for home and groups.

Ultimate Guide to Homeschool Robotics – Outline

Here is the outline to our Ultimate Guide to Homeschool Robotics:

• Why Should You Listen to Me? – You be the judge. A bit of my background.
• Importance – Why is it important for your kids to learn robotics?
• Where to Get Help – Several resources to help you get started
• How to Learn Before Teaching Your Kids – You can probably learn enough to get them started – Key Ideas
• Teaching at Home – How to get your kiddos learning this at home
• Groups / Co-Ops – Robotics is great in homeschool groups! How to get started.
• Programming Languages
• Graphical Vs Written
• What to avoid
• What to look for
• Which robots to avoid
• Which robots to buy
• Lego Limitations – Legos are great and all, but they are heavily over used in robotics
• Curriculum – How to choose/make your robotics for kids curriculum
• Helpful YouTube Videos – Helpful and free, what’s not to like?
• Books – Books that can help in your homeschool robotics journey
• Classes – Robotics classes you can take even in homeschool
• Field Trips – Where to go for a fun day learning robotics
• Online – Where to surf the web for robotics education
• How to Build Your Own Robot – The challenge is worth it
• Tools – What will you need to make this happen?
• Toys – The educational spectrum of robot toys
• Pitfalls – What could go wrong? Besides the robots taking over, keep an eye on these issues
• Related Subjects – There are some similar topics that you and your kids just might love!

Homeschool Robotics – Keith’s Background

A bit about me. I was in public school except for being homeschooled in 6th and 7th grade. Most likely I was a gifted kid but back then you’d just end up getting Ritalin thrown at you for such an offense. My interest in tech has always existed.

Winning the big CAD competition got me a lot of job offers, and I made enough money I thought I’d never go to college. Well the recession happened and I worked mostly in automotive.

Off to college I went, where I got a Mechanical Engineering degree and an Aerospace Engineering degree. Our robotics team won two competitions. I also did funded research and was a research assistant in autonomous vehicles and jet engine simulation.

That’s me in the middle. I’ve been teaching 4 years now.

My desire to help others in this important field made me leave behind my Engineering career. If you want to know more, you can read about me – Keith Young .

You can also read an article Anki, a robotics company, wrote about me https://developer.anki.com/blog/features/interview/from-stem-to-learn/

Homeschool Robotics – Importance

The job market is changing quickly. In 20 years things will be drastically different and that will largely be driven by robotics, coding, and other related fields.

Avoiding technological unemployment isn’t the only reason it’s important for everyone including homeschoolers to learn robotics. Besides the major changes needed in how governments control people, the next biggest issues are solvable with these important fields.

Think of the most important cause you can think of, and chances are it will be helped with teamwork, industriousness, problem solving skills, and technical skills.

We shape our world with our technology. It’s important to understand the technology, and to use it ethically.

But Keith, I Don’t Know Enough

First of all, that might not matter. Depending on the curriculum you choose, or the coop you find, you might not need much robotics knowledge.

That said, it’s good to know the basics. We will go over the basics of robotics later in this article.

There are baby steps that are incredibly achievable for you. If you feel like you might be over your head, check out our Ultimate Guide to Block Coding . It is a great step towards learning Robotics at home.

Homeschool Robotics – Sources of Help

As always I recommend you first ask around in your local homeschool community. That will probably always be the best source of help you can find. Everywhere I look I see strong homeschool communities where people are eager to help each other.

After that, I’d like to consider Kinvert, my educational company, to be a pretty good source at least when it comes to STEM.

If neither of these are good enough, you can always try YouTube, Google, and Facebook – or DuckDuckGo.

There is also a chance your local library has some cool STEM activities you were unaware of.

Homeschool Robotics – Learn Before Teaching

You don’t need to know everything before getting started. However a bit of research is important.

You’ll want to learn about how to choose the right robot for your family. In addition it’s good to try to stay one chapter ahead of your kids in case they need help. That said, if you find a great curriculum you might not need to give a ton of help.

We’ll go over some of the main things you should know below. The main thing to remember is you don’t have to know everything. Just learn the basics for now.

One article you might be interested in is What is Robotics .

Homeschool Robotics – Your Kids Level

An important consideration will be the level your kids are at for robotics. You might not want to sit your 17 year old down in front of an Ozobot or Legos. You might not want to sit your 5 year old down in front of a robot that needs assembly and can only be programmed in C.

Please keep in mind, when I say beginner, I don’t mean compared to kids their age. I mean how they sit in this topic of robotics.

A beginner has little to no programming and robotics experience. They might have done a semester or maybe a year of Lego robotics (or Ozobot, Dot and Dash, CoderMip, etc).

They understand somewhere between nothing, and how to make a robot make a basic decision such as if the button is pushed, then turn on the light.

They have done some coding of some sort whether that’s Scratch, Lego, or some other snap together language. Maybe they know what a loop is. They’ll start taking more complicated kits and robots and be able to follow along in tutorials.

For example they might program Cozmo with tutorials and make some slight modifications to them. They might do the same with the Parallax ActivityBot 360 .

Ability to start solving unique problems with robots. They’re ready to start learning how to design and build their own custom robots that actually work.

This is the point at which they can start doing more complicated things with Cozmo, apply some trigonometry, or build a custom robot using the Parallax ActivityBot or a similar platform.

Homeschool Robotics at Home

You’ll want to make sure you’re ready with curriculum, your own knowledge, or an online course.

Robots like hard flat surfaces. Though tables work, you’re taking a risk. We’ve taught hundreds of kids and we’ve only had one component break from a skydiving robot. That said, I’m very comfortable buying and replacing parts.

The best place to make this happen is a wood floor or linoleum. Tile can also work but it might give the robot a little trouble when trying to drive accurately. This is due to the uneven surface.

It will be more important home alone with the kiddos to make sure they don’t get too discouraged. I’ve seen kids give up and it was hard to win them back over after they’d tried this at home.

This is one of the pitfalls I’ll talk about later. Some kids can get stuck at a common sticking point, and without help decide they’re “not a coder” or that they “can’t do robotics.” Please don’t let this happen.

Homeschool Robotics in Groups Coops

This could be a great option depending on your situation.

First of all, it is obviously not true that everyone learns better in groups. That said, I think the majority of kids learn best in a well formed group.

Also, if you get your kids learning robotics in a group, you don’t necessarily have to be the teacher.

If you’re in a group there is a great advantage. If managed correctly, the kids will help each other learn. There are multiple reasons this is awesome.

For one, kids learn better generally when they have access to learning and working with peers. Another, and I believe in this strongly, you learn much more by teaching than by just being the student.

By having students help each other, they can learn so much more.

That said, there can be some logistical issues. One of the biggest, is getting all the equipment together.

If you have each kid bringing their own computer, I can say it’s likely you’ll have to troubleshoot a bunch of computers. But, by doing it this way you can save a fair bit of money.

Homeschool Robotics Basics

It might seem like there is a ton of information you need to know. And there sort of is. That said, with knowledge of the very basics you can still make informed decisions.

The main things to look for in an educational robot for your homeschool classroom is the support community, sensors, programming language, and room to grow.

As for the support community, the best I have seen is around the Parallax ActivityBot. Parallax really understands education and they’ve been doing this a long time. I taught myself on Parallax products starting back with the Whata’s a Microcontroller.

Next up is sensors. Without sensors the robot can’t make any meaningful decisions. Again, in my opinion, the Parallax ActivityBot wins here. You can add just about any sensor you can imagine. The only exception is adding a camera requires a fair bit of knowledge. Also keep in mind that when adding sensors, you’ll need to wire them in. That said, Parallax has great instructions.

When it comes to the programming language, this is where Cozmo shines over the ActivityBot. Cozmo can be programmed in Python while the ActivityBot is programmed in C. If you read up on these languages what you’ll quickly find is that Python is much easier than C and approximately as powerful – depending on what you’re doing of course.

For beginners graphical programming languages such as Scratch and Lego may be OK. That said, I encourage you to get your kids in Python as soon as they can type well. I talk about this in Best Age to Teach Kids Python .

With both the Parallax ActivityBot and Anki Cozmo, there is a lot of room to grow. The ActivityBot gives your kids the chance to build their programming and design / building skills for literally decades. With Cozmo you can also do a lot of growing with the programming, maybe more than the ActivityBot, but there is no feasible way to customize the hardware.

Homeschool Robotics – Choosing Your Robot

This might seem overwhelming. We can help break this down for you a bit here.

For beginners, you can look at plain old toys, as well as some of the robots that are very beginner friendly. Good examples will be Ozobot, Dot and Dash, CoderMip, Lego, etc.

At the medium and advanced levels, I recommend maybe Lego still, but mostly the Anki Cozmo SDK and the Parallax ActivityBot 360 .

There won’t be much homework that you the parent will need to do for the beginner robots. For the Cozmo and ActivityBot that might be a different story.

I’ll end up writing an article specifically about this one topic. For now, you might find out Best STEM Gifts for Kids – Educational Toys article useful.

Homeschool Robotics – Lego Limitations

While Lego is great for younger kids, I’ve seen it leave older kids behind when it comes to coding skills. It doesn’t stop there. Lego was pretty important for building robots before 3D Printers were so common. But now, we can design and 3D Print our own custom parts.

Real robots aren’t built with Lego bricks. They’re built with designed and manufactured parts.

Once your kids get past the beginner stage I think it’s critical to get them in to something on the level of the ActivityBot or Cozmo.

Homeschool Robotics Curriculum

You know your kids better than me. So you know if they like structured lessons or to be faced with a challenge to overcome which requires learning on the way.

Before you spend $200 or so you’ll want to know that there is enough of a knowledgebase behind the robot that your kids will be able to learn.

You probably won’t be able to create a robotics for kids curriculum if you can’t find good documentation and examples.

Parallax has pretty good information and tutorials at https://learn.parallax.com .

Anki doesn’t have nearly as much educational backing for Cozmo. They do have a bit with their example programs you can download when installing the SDK.

We do however have a bit of information and we’re constantly expanding it.

Currently the best place to learn about the Anki Cozmo SDK is in our Anki Cozmo Examples in Python – Tutorials and Projects . We also have info on the Anki Vector SDK and have Anki Vector Examples .

Homeschool Robotics YouTube Videos

We will keep adding to this section as we find more resources. If this sub section begins to grow too large, we’ll leave a summary and link to a new article that dives in more depth.

www.youtube.com/watch?v=3XkL0qQ21Oo

Homeschool Robotics Books

The one that I’ve always had and loved personally, is The Way Things Work (they also have The New Way Thinks Work and The Way Things Work Now ).

Look in to the Usborn books that deal with technical drawings of the insides of things. Very cool books. Again, not directly related to robotics but a good tangent.

As far as robotics books, we don’t have any. That said, we’re currently writing one 🙂

For now, look in to Everything Robotics, Building Your Own Robot, and honestly search around. You should find something your kids will like.

Homeschool Robotics Classes

We will expand this list in the future.

You can find some Lego stuff at Robot Garage. They might call some of their classes advanced but they are all what we at Kinvert to be beginner classes.

The one class that I’ve seen, anywhere, that can go from beginner to advanced is Robotics for Kids and Teens . Yes, it’s a Kinvert class, and I might be biased.

Homeschool Robotics Field Trips

Don’t think you want to go the route of buying a robot and teaching that way? You can still get your kids to learn a little about robotics. There is often the chance to get in a good robotics tour for you our your homeschool group.

Here are some places you might be able to set up some good field trips for your kids. For example, we did a field trip at a local robotics company in the Detroit area.

• Robotics companies
• Maker Faire
• Library program
• Walking with Dinosaurs

We’ve been at Maker Faire Detroit before. You can read our articles on that here:

Maker Faire Detroit 2016

Maker Faire Detroit 2017

Online Homeschool Robotics

Unfortunately I don’t see a ton of options here. I will research this in more depth and add to this section of the article later. If I do find enough info to justify it I will write a dedicated article to this topic and link to it from here.

Build Your Own Robot at Home

The easiest way to do this is with a kit.

Lego here is a fairly obvious choice if your kids are young. If they’re a bit older I’d look again at the Parallax ActivityBot. The great thing about the ActivityBot is our students used that exact kit to make the orange bulldozer you see drawn in this article.

Once you’re pretty advanced and have the right tools you can even design and 3D Print your own robot. This is the level we aim to get our Kinvert students.

Homeschool Robotics Tools

Again this will depend on how in depth you want to get. Maybe you just get them a basic breadboarding kit. Some others with a bigger budget can get their kids some more serious gear such as 3D Printers and an oscilloscope.

If you want to know more about the tools that will be useful for this, please let me know in the comment section below. If I see interest in this I’d be happy to go more in depth on the topic.

Homeschool Robotics Toys

We have an article on this very topic which goes more in depth than I will here. Check out Best STEM Toys for Kids – Educational Gifts .

Long story short, there are a ton of great options. We tend to funnel people towards either the Parallax ActivityBot 360 or the Anki Cozmo SDK .

There are other options as well for younger kids with less experience. Lego is an obvious choice. That said there are other robots we don’t view as fully educational, yet are better than nothing. These include Ozobot, Dot and Dash, Miposaur, and others.

Homeschool Robotics Pitfalls

There are a few pitfalls to avoid when trying to teach robotics to your homeschooling children.

I think the main thing overall is to keep the class challenging while achievable. The last thing you want to do is make your kids think robotics is boring. Worst still would be making them think they can’t be a coder or handle robotics.

You also have the struggle with technology. Some robots are very reliable. That said, things do break, there might be some troubleshooting involved. If you’re teaching this yourself rather than using curriculum, classes, or a homeschooling group, you’ll need to read up on some of this.

Also please make sure your kids can type well. You don’t want to put them in to a written programming language like C or Python before they can type. It is equally as important to not leave them in graphical languages too long.

Homeschool Robotics Related Subjects

If you don’t end up going with robotics, I implore you to please not step away from STEM. Here are some other things that you’ll probably find interesting.

I wouldn’t be doing my job if I didn’t make sure you’re aware of our classes. We teach Robotics Classes for Kids , Coding Classes for Kids , 3D Printing for Kids , and we are building an online course as well. We’ll add the link when it’s ready.

We also have several articles that could be helpful.

Best STEM Gifts for Kids – Educational Toys has helped a lot of families get the right educational gifts for their kids.

The Ultimate Guide to Robot Dinosaurs is a pretty cool article.

We have a lot of Anki Cozmo Examples in Python with Projects and Tutorials and more info on the Anki Cozmo SDK .

A similar robot to Cozmo is Vector, also made by the same company. We have an article on Cozmo Vs Vector , the Anki Vector SDK , and Anki Vector Examples, Tutorials, and Projects .

Also consider our Ultimate Guide to Robotics Projects and Ideas .

Applied Math Problems – Real World Math Examples and Uses

Did I Miss Something? Failed to Answer Your Question?

We’re here to help. We make additions to articles ALL THE TIME. Please let me know if I left your question unanswered either in the comments below or on our Contact Page .

Finally, we did link to a couple things on Amazon. It would be great if you could help support us by buying through those links. We get a small percentage and it won’t cost you a penny more.

6 responses to “ Ultimate Guide to Homeschool Robotics ”

Hello. My son is almost 12 and wants to ask for the Vector or Cozmo for Christmas. He’s concerned (seeing your pictures as I scrolled through your website) that Cozmo might be for elementary kids. He is new to coding and robotics so I thought Cozmo might be better after reading some of your comments/info?

Also, have you considered doing a coding class on Outschool.com? A lot of homeschoolers use the website to take various classes. Teachers offer live classes or prerecorded classes. My friend teachers on it and has students in her nature journaling class from Japan, US, England, and Australia.

Thanks for providing the information and suggestion for homeschoolers.

Cozmo is not only for elementary kids. That said there’s a reasonable chance that Vector could be the better option for him.

I just found out about 10 minutes ago that the Vector SDK is now available to all. So I’m going to be checking soon to see how reliable and in depth it is.

Currently Cozmo has a very mature SDK while Vector’s is new and still in testing.

I’ve had several parents mention I should teach on outschool. Currently we’re building classes on our own platform which is currently in development.

Are you interested in testing our classes as a beta tester?

Thanks Jen!

Interested in being a beta tester. My friend and I are homeschool mothers who want to introduce our kids to robotics. Our kids are beginner level and need to learn typing. Thx.

I will send you an email shortly. If for some reason it doesn’t come through send me a quick message to [email protected] .

As for typing I recommend Typing Instructor for Kids:

Amazon Link – https://amzn.to/2X8PSI8

FYI if you buy through that link above we’ll get a small percentage from Amazon and you won’t pay a penny more.

Will talk to you about Beta etc in the email.

I am just reading through this thread looking to provide a co-op course for middles school homeschool students. I would also be interested in being a beta-tester.

Sorry to reply so late. I will email you shortly.

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Benjie Holson is the Director of Robotics at Robust AI.

The original version of this post by Benjie Holson was published on Substack here , and includes Benjie’s original comics as part of his series on robots and startups .

I worked on this idea for months before I decided it was a mistake. The second time I heard someone mention it, I thought, “That’s strange, these two groups had the same idea. Maybe I should tell them it didn’t work for us.” The third and fourth time I rolled my eyes and ignored it. The fifth time I heard about a group struggling with this mistake, I decided it was worth a blog post all on its own. I call this idea “The Mythical Non-Roboticist.”

The Mistake

The idea goes something like this: Programming robots is hard. And there are some people with really arcane skills and PhDs who are really expensive and seem to be required for some reason. Wouldn’t it be nice if we could do robotics without them? 1 What if everyone could do robotics? That would be great, right? We should make a software framework so that non-roboticists can program robots.

This idea is so close to a correct idea that it’s hard to tell why it doesn’t work out. On the surface, it’s not wrong : All else being equal, it would be good if programming robots was more accessible. The problem is that we don’t have a good recipe for making working robots. So we don’t know how to make that recipe easier to follow. In order to make things simple, people end up removing things that folks might need, because no one knows for sure what’s absolutely required. It’s like saying you want to invent an invisibility cloak and want to be able to make it from materials you can buy from Home Depot. Sure, that would be nice, but if you invented an invisibility cloak that required some mercury and neodymium to manufacture would you toss the recipe?

In robotics, this mistake is based on a very true and very real observation: Programming robots is super hard. Famously hard. It would be super great if programming robots was easier. The issue is this: Programming robots has two different kinds of hard parts.

Robots are hard because the world is complicated

The first kind of hard part is that robots deal with the real world, imperfectly sensed and imperfectly actuated. Global mutable state is bad programming style because it’s really hard to deal with, but to robot software the entire physical world is global mutable state, and you only get to unreliably observe it and hope your actions approximate what you wanted to achieve. Getting robotics to work at all is often at the very limit of what a person can reason about, and requires the flexibility to employ whatever heuristic might work for your special problem. This is the intrinsic complexity of the problem: Robots live in complex worlds, and for every working solution there are millions of solutions that don’t work, and finding the right one is hard, and often very dependent on the task, robot, sensors, and environment.

Folks look at that challenge, see that it is super hard, and decide that, sure, maybe some fancy roboticist could solve it in one particular scenario, but what about “normal” people? “We should make this possible for non-roboticists” they say. I call these users “Mythical Non-Roboticists” because once they are programming a robot, I feel they become roboticists. Isn’t anyone programming a robot for a purpose a roboticist? Stop gatekeeping, people.

Don’t design for amorphous groups

I call also them “mythical” because usually the “non-roboticist” implied is a vague, amorphous group. Don’t design for amorphous groups. If you can’t name three real people (that you have talked to) that your API is for, then you are designing for an amorphous group and only amorphous people will like your API.

And with this hazy group of users in mind (and seeing how difficult everything is), folks think, “Surely we could make this easier for everyone else by papering over these things with simple APIs?”

No. No you can’t. Stop it.

You can’t paper over intrinsic complexity with simple APIs because if your APIs are simple they can’t cover the complexity of the problem . You will inevitably end up with a beautiful looking API, with calls like “grasp_object” and “approach_person” which demo nicely in a hackathon kickoff but last about 15 minutes of someone actually trying to get some work done. It will turn out that, for their particular application, “grasp_object()” makes 3 or 4 wrong assumptions about “grasp” and “object” and doesn’t work for them at all.

Your users are just as smart as you

This is made worse by the pervasive assumption that these people are less savvy (read: less intelligent) than the creators of this magical framework. 2 That feeling of superiority will cause the designers to cling desperately to their beautiful, simple “grasp_object()”s and resist adding the knobs and arguments needed to cover more use cases and allow the users to customize what they get.

Ironically this foists a bunch of complexity on to the poor users of the API who have to come up with clever workarounds to get it to work at all.

The sad, salty, bitter icing on this cake-of-frustration is that, even if done really well, the goal of this kind of framework would be to expand the group of people who can do the work. And to achieve that, it would sacrifice some performance you can only get by super-specializing your solution to your problem. If we lived in a world where expert roboticists could program robots that worked really well, but there was so much demand for robots that there just wasn’t enough time for those folks to do all the programming, this would be a great solution. 3

The obvious truth is that (outside of really constrained environments like manufacturing cells) even the very best collection of real bone-fide, card-carrying roboticists working at the best of their ability struggle to get close to a level of performance that makes the robots commercially viable, even with long timelines and mountains of funding. 4 We don’t have any headroom to sacrifice power and effectiveness for ease.

What problem are we solving?

So should we give up making it easier? Is robotic development available only to a small group of elites with fancy PhDs? 5 No to both! I have worked with tons of undergrad interns who have been completely able to do robotics. 6 I myself am mostly self-taught in robot programming. 7 While there is a lot of intrinsic complexity in making robots work, I don’t think there is any more than, say, video game development.

In robotics, like in all things, experience helps, some things are teachable, and as you master many areas you can see things start to connect together. These skills are not magical or unique to robotics. We are not as special as we like to think we are.

But what about making programming robots easier? Remember way back at the beginning of the post when I said that there were two different kinds of hard parts? One is the intrinsic complexity of the problem, and that one will be hard no matter what. 8 But the second is the incidental complexity, or as I like to call it, the stupid BS complexity.

Stupid BS Complexity

Robots are asynchronous, distributed, real-time systems with weird hardware. All of that will be hard to configure for stupid BS reasons. Those drivers need to work in the weird flavor of Linux you want for hard real-time for your controls and getting that all set up will be hard for stupid BS reasons. You are abusing Wi-Fi so you can roam seamlessly without interruption but Linux’s Wi-Fi will not want to do that. Your log files are huge and you have to upload them somewhere so they don’t fill up your robot. You’ll need to integrate with some cloud something or other and deal with its stupid BS. 9

There is a ton of crap to deal with before you even get to complexity of dealing with 3D rotation, moving reference frames, time synchronization, messaging protocols. Those things have intrinsic complexity (you have to think about when something was observed and how to reason about it as other things have moved) and stupid BS complexity (There’s a weird bug because someone multiplied two transform matrices in the wrong order and now you’re getting an error message that deep in some protocol a quaternion is not normalized. WTF does that mean?) 10

One of the biggest challenges of robot programming is wading through the sea of stupid BS you need to wrangle in order to start working on your interesting and challenging robotics problem.

So a simple heuristic to make good APIs is:

Design your APIs for someone as smart as you, but less tolerant of stupid BS.

That feels universal enough that I’m tempted to call it Holson’s Law of Tolerable API Design .

When you are using tools you’ve made, you know them well enough to know the rough edges and how to avoid them.

But rough edges are things that have to be held in a programmer’s memory while they are using your system. If you insist on making a robotics framework 11 , you should strive to make it as powerful as you can with the least amount of stupid BS. Eradicate incidental complexity everywhere you can. You want to make APIs that have maximum flexibility but good defaults. I like python’s default-argument syntax for this because it means you can write APIs that can be used like:

It is possible to have easy things be simple and allow complex things. And please, please, please don’t make condescending APIs. Thanks!

1. Ironically it is very often the expensive arcane-knowledge-having PhDs who are proposing this.

2. Why is it always a framework ?

3. The exception that might prove the rule is things like traditional manufacturing-cell automation. That is a place where the solutions exist, but the limit to expanding is set up cost. I’m not an expert in this domain, but I’d worry that physical installation and safety compliance might still dwarf the software programming cost, though.

4. As I well know from personal experience.

5. Or non-fancy PhDs for that matter?

6. I suspect that many bright highschoolers would also be able to do the work. Though, as Google tends not to hire them, I don’t have good examples.

7. My schooling was in Mechanical Engineering and I never got a PhD, though my ME classwork did include some programming fundamentals.

8. Unless we create effective general purpose AI. It feels weird that I have to add that caveat, but the possibility that it’s actually coming for robotics in my lifetime feels much more possible than it did two years ago.

9. And if you are unlucky, its API was designed by someone who thought they were smarter than their customers.

10. This particular flavor of BS complexity is why I wrote posetree.py . If you do robotics, you should check it out.

11. Which, judging by the trail of dead robot-framework-companies, is a fraught thing to do.

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Benjie Holson has been a roboticist since he first joined his high school robotics team, has programmed robots at startups and Google X’s Everyday Robots and is currently Director of Robotics at Robust AI , where he hopes to someday ship boring-looking robots that solve real problems to customers who pay money for them.

As someone currently building a platform & API to help people get into robotics easier, I agree with what you have to say. Complexity in robotics is wild. Many of my JS-dev friends don't even want to get close to a Raspberry Pi due to the "uncertainty" of it all.

Building a good "API" is a hard balance & I think one of the few similar to what you describe is Flutter - great defaults & seamless extensions.

Although, I think you missed an important point: Less-BS documentation. I do not want to touch ROS for that.

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Have you always wanted to build your own robot? It's not as difficult as you might think. You can use one of the many starter kits available or create your own programmable robot with an array of standard electronic components.

For the robot’s electronic brain, you could use a Raspberry Pi, Arduino, or another type of microcontroller. You’ll need a driver board to control motors to make it move, using wheels, tracks, or even legs. Or you could create a robot arm.

Here we explore some of the most popular and interesting approaches to making a robot.

1. Wheeled Robot

The most popular type of DIY robot to build resembles a miniature car, featuring a chassis and typically two or four wheels, sometimes six.

Whether using a Raspberry Pi, Arduino , or another microcontroller, you’ll need a motor driver board to connect it to the DC motors that will spin the wheels. A portable power source is also required, such as a power bank or battery pack.

The chassis forms the body of the robot. For this, you could purchase a kit or build your own custom chassis from scratch using 3D-printed / laser-cut parts or any materials you have to hand.

For tricky terrain, your robot could be equipped with caterpillar tracks or even a rocker-bogie suspension system like NASA’s Perseverance Mars rover.

While steerable wheels can be added, the simplest way steer the robot is to make the motor(s) on one side go faster than the other. Or you could use special Mecanum wheels with angled roller treads to enable it to shift sideways.

Adding sensors to the robot will help it to move autonomously once programmed. An ultrasonic distance sensor will enable it to avoid obstacles, while a downward-facing IR sensor can be used for following a black line on the floor.

You could even add a camera for remote video viewing and object recognition using a computer vision library such as OpenCV.

2. Self-Balancing Robot

A two-wheeled self-balancing robot uses an IMU (inertial measurement unit) with accelerometer and gyroscope sensors to detect movement and rotation. This enables it to adjust its balance accordingly with the motors and avoid falling over.

It takes a good understanding of math and some advanced programming, but the results can be very impressive when your robot manages to roll along and stay upright.

3. Legged Robot

This concept has got legs… literally. Making and operating robot legs is a lot tricker than using wheels, as you’ll need to create flexible leg joints and add a servo motor to each joint to enable it to move with precision. Joints are typically made using 3D printing or laser cutting.

Read More: How to 3D Print for Beginners

Building a robot with four, six, or eight legs makes for better stability and ease of control than a bipedal one (see below). The downside is that there will be a whole load of wiring involved to connect all those leg servos. Will you make a robot cat, dog, insect, or spider?

4. Bipedal Robot

If you want to make your own Star Wars-style robot, this is the droid you’re looking for.

While simpler to wire up than a robot with a greater number of legs, a bipedal robot has the additional challenge of getting it to balance so it doesn't fall over.

Achieving a smooth walking motion is the key to getting your robot to stay upright as it strides along. Optionally, you may also want to install an IMU with accelerometer and gyroscope sensors (see Self-Balancing Robot above).

For a more humanoid robot, you could add moving arms to your creation, which could even be used to help it stay upright if it starts to fall.

5. Robotic Arm

Most industrial robots are mechanical arms that pick up items and manipulate them. If you want to build your own, there are a few kits available to get you started, such as the PiArm .

As with robotic legs, the arm will comprise several joints, each equipped with a servo motor for precise control of its movement. For maximum dexterity, you want an arm with enough joints—including a rotating base—that it offers at least six degrees of freedom (6DOF).

To build your own arm from scratch, you could use a toy construction set like Meccano or a more dedicated, precision robot-building system like Actobotics .

You could even make your robotic arm mobile by mounting it on the chassis of a wheeled robot.

6. Underwater ROV

As Homer Simpson predicted in the form of song, in the future everyone will live under the sea. Until then, you might want to explore the ocean with an underwater robot, aka ROV (remotely operated vehicle).

First things first: water and electronics are not a good mix! So you’ll need excellent waterproofing of the housing to protect the electronics inside your robot; for extra safety, you might even want to coat the interior wired connections with resin.

To make your mini ROV move, you’ll need brushless motors connected to propellers. While lateral steering is similar to that in a wheeled robot, the addition of a vertical propeller will enable you to control the robot’s depth in the water.

A gyroscope will help for sensing the robot’s orientation underwater, while a camera and light will enable the remote operator to see. Beaming video wirelessly to another device through water isn’t easy, so a cable connection is advised.

7. Robotic Fish

For the ultimate in underwater robots, you could create a robo-fish. Building one is an ambitious project, requiring precision 3D printing and a custom design for the body and movable fins/tail for steering.

Some impressive examples of robotic fish have been created by academic research teams seeking a discreet way to swim alongside real shoals of fish to study their behaviour. A team at CSAIL MIT, created SoFi; this robotic fish features an  ingenious tail inspired by the biological system used in tuna fins.

7 Ways to Build Your Own Robot Today: Success

Once you’ve built your robot, there are several ways to control it. You could steer it manually from another device or computer. Or program it to follow a particular pattern of movement: a typical way of using a robotic arm.

The seven types of robot you can build are:

• Wheeled robot
• Self-balancing
• Legged robot
• Robotic arm
• Underwater ROV

For your robot to be truly smart, you’ll need to code its microcontroller or single-board computer so it can act autonomously. For this, you will want to add sensors or even a mini camera so your robot can sense/see where it’s going and avoid obstacles.

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June 27, 2024 , Filed Under: Uncategorized

How to Transform a Great Idea Into a Winning Business

Whether you have a stroke of inspiration at midnight or have incredible insight from years of experience, you know when a great idea hits. It may be reinventing the wheel or simply making one step of the process much easier; whatever it is, you feel that it has the potential to change lives and make you millions. Sadly, it takes more than thoughts and prayers to turn a great idea into a profitable reality—indeed, many have tried and failed. In this article, we will look at how to take the first steps to turn your spark of genius into a roaring success with the help of organizations such as Bigspace Investments .

1. Validate Your Idea

Before congratulating yourself on your clever idea and celebrating your future wealth, let us make sure that it will actually work. 

Market Research : Market research is the foundation of any winning business. Start by defining your target market. What are the demographics and lifestyle, values, or buying habits of your potential customers? Analyze your competitors: who they are, what they offer, and how they price their offerings. Compare your strengths and weaknesses, observe industry trends and forecasts, and see if any gaps in the market are perfect for you.

Customer Feedback : Once you have a clear understanding of the market, it is time to validate your idea with potential customers. Start by conducting interviews with your target audience to find out about their needs and preferences and gather feedback on the appeal of your business idea. Consider creating a minimum viable product (MVP) to trial your idea in the market without expending too many resources.

Feasibility Study : A feasibility study evaluates the practicality of your business idea in terms of resources, skills, and logistics. Technical feasibility examines whether your business idea is technically viable. Financial feasibility evaluates the financial aspects of your business, including startup costs, funding requirements, and potential profitability. Operational feasibility assesses the operational aspects, such as supply chain management.

2. Create a Business Plan

With the information you have gathered during the previous stage, you can now create a business plan. A business plan is a comprehensive document that outlines your business idea, strategies, and financial projections. It is essential for presenting your idea and securing funding from investors or lenders.

A solid business plan will include a detailed description of your business: what your business does, the products or services you offer, your unique selling proposition (USP), and your short-term and long-term goals. You should also introduce the organizational structure and management team and explain how the skills of key team members will contribute to the success of your business.

In your business plan, include a market analysis that demonstrates your understanding of the market. Information about your target consumer, competitors, market trends, and growth potential will show investors that you have done your homework. Outline your sales and marketing strategies for attracting and retaining customers, including pricing and distribution channels.

Financial projections demonstrate the potential profitability and sustainability of your business. Include projected income statements and balance sheets for the next three to five years. Be sure to use realistic assumptions based on your research and current industry benchmarks. Highlight key financial metrics, such as net profit margin and break-even analysis.

3. Explore Funding Options

If, like many entrepreneurs, you do not have a huge amount of personal savings to put into a new project, you will need to explore sources of external funding.

Equity Investors: Venture capitalists and angel investors like Bigspace Investments bring more than just money to the table. These investors provide capital in exchange for shares in the company, which means they are invested in its success. Aside from injecting much-needed capital, they also provide valuable expertise, mentorship, and strategic connections. Having equity investors involved can significantly accelerate your company’s growth and open the door to beneficial opportunities and networks.

Business Loan: If you fail to catch the eye of investors, getting a business loan from a bank or credit can help you cover startup costs and initial operating expenses. There are several types of business loans available, including term loans and SBA-backed loans . To secure a loan, you will need a solid business plan, a good credit history, and, in most cases, collateral. This can include property or any vehicles or equipment you or the business owns.

Crowdfunding: Crowdfunding platforms like Kickstarter allow you to secure small contributions from many backers, often in exchange for the first batch of your product. An effective crowdfunding campaign can validate your business idea and serve as a marketing tool that generates a pre-launch buzz. However, it takes a well-crafted campaign, effective communication, and ongoing engagement with backers to maintain interest and trust.

Many people have great ideas, but few can turn them into reality, much less winning businesses. While the first steps of researching and writing a business plan may dampen your enthusiasm, they are essential for the creation of a roadmap to success. After all, you need a robust business plan to prove to investors or lenders that you can make this work. If you are lucky enough to secure the attention of equity investors, you will also gain from their guidance and experience throughout the entrepreneurship process. So, let’s get cracking and turn that great idea of yours into something that you can really be proud of.

The real voyage of discovery consists not in seeking new landscapes, but in having new eyes —  Marcel Proust

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