People - Duckietown

University of Nevada: Professor Lei Yang uses Duckietown based RET

Posted on March 14, 2023 | by Ivano Marocchi

University of Reno, March 7, 2023: Lei Yang, Associate Professor in the Department of Computer Science and Engineering of the University of Nevada in Reno shares with us his experience conducting a program called Research Experience for Teachers (RET) focused on “Integrating Big Data into Robotics”.

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Professor Lei Yang tells us about conducting a Duckietown based Research Experience for Teachers

Professor Lei Yang shares with us his relationship with Duckietown and how it performed used in a K-12 teachers research experience led by the Computer Science and Engineering department of the University of Nevada in Reno.

Good morning Professor and thank you for finding the time to speak to me.

Good morning, thank you.

How did you come across Duckietown the first time? When did you discover it?

Well, we needed a specific platform for our project, and a collaborator from Europe told us about this platform he was very familiar with. He let us know that it was a great platform, and that we should have a look at it. We accepted and ended up using Duckietown and suiting it to our project.

Could you tell us more about this project?

For three years now at the University of Nevada, Reno’s Computer Science and Engineering department (CSE) we’ve been conducting a program called Research Experience for Teachers (RET) focused on “Integrating Big Data into Robotics”. It’s a six-week course, through which participants can gain hands-on robotics experience that can be later applied in classrooms, in a fun way. The main idea is trying to provide a research experience to K-12 teachers. That’s why we proposed the idea of using Duckietown to teach K-12 teachers. We asked ourselves. what is the state of the art in terms of data analytics, machine learning? I think Duckietown is a very good education platform for teachers. We make use of the very good materials provided by Duckietown and I’m very satisfied with its implementation.
We purchased a Duckietown set for each participant and let them bring the hardware back to their school. Some teachers started their very own robotics clubs! They basically utilize that as an additional platform for their students.

What would you say are the characteristics of Duckietown that make it useful for you?

Our RET program involves all K-12 teachers, and one of the main goals of our program is to work with these teachers to develop curriculum modules suitable for their students. We have teachers from different levels, but we find that actually middle school and high school teachers are kind of more suited for this program. Duckietown is freely available and includes curricula that can be adapted for all levels of education. It is tangible, it is accessible, and looks fun!

"I think Duckietown is a very good education platform for teachers. We make use of the very good materials provided by Duckietown and I’m very satisfied with its implementation."

Prof. Lei Yang

It’s also easy to deal with. We can find all the materials online, and it is hands-on as I already mentioned. People like hands on activities, it’s good for kids. The duckies also serve to present robotics as less intimidating, making it easier to teach the harder, underlying concepts. I think that’s very nice: it can be used to teach optimization, control theory, these are fundamental things. I think this is a platform that can suit people with different levels of background and also an easy way to start one’s journey into robotics.

What does the future hold?

I think we’ve done a great job this year, and the teachers liked our project. I can see a significant improvement compared to the first year. This is a three-year project, so this year was the last for the program. After the program expired, we submitted another proposal to continue utilizing Duckietown, and to integrate new things like blockchain technology and other new ideas into this program so hopefully we’ll be using this platform in the future as well.

Learn more about Duckietown

The Duckietown platform enables state-of-the-art robotics and AI learning experiences.

It is designed to help teach, learn, and do research: from exploring the fundamentals of computer science and automation to pushing the boundaries of human knowledge.

Tell us your story

Are you an instructor, learner, researcher or professional with a Duckietown story to tell? Reach out to us!

How Duckietown set “Frank” Chude Qian on the path to autonomous vehicles

Posted on February 3, 2023 | by Ivano Marocchi

University of Toronto, February 3, 2022: “Frank” Chude Qian, A Master Student at the University of Toronto, shares with us his experience with Duckietown.

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How Duckietown set Chude (Frank) Qian on the road to autonomous vehicles

“Frank” Chude Qian is a Master’s student at the University of Toronto. He first encountered Duckietown at the International Conference on Robotics and Automation (ICRA) in 2019, and from that moment he decided that autonomous vehicles would have been his path forward.

Hello and thank you so much for having accepted to have this brief chat with us! Tell us about yourself and what you do.

Definitely! My name is Frank, and I’m currently a student at the University of Toronto. I’m in the second year of my program. I started as an Engineering Master’s student, and then I switched over to a Master of Science. My main focus is on developing the second generation of the University of Toronto’s autonomous vehicles that participate in the SAE Auto Drive Challenge. My work will end with the transition to the new vehicle, which will happen next year.

Thank you. Could you describe to us your first approach with Duckietown?

Yeah, definitely. So I was actually at ICRA 2019 wandering around and figuring out what to do with my life. I was taking part in another competition where I saw the Duckietown setup at the ICRA challenge [AI-DO 2]. It looked like great fun, I really loved the idea of how the project is and how it’s designed as a global initiative. You have people from different parts of the world trying to do the same thing, which I found inspiring.

Compared to the actual large-scale autonomous vehicles, Duckietown is an affordable option to learn mobility, and I really liked it. After I came back from ICRA, I just started looking at Duckietown and the AI Driving Olympics competition in more detail.

Nice! And how did that go?

In 2019, I started looking into what we could do with Duckiebots at my at Case Western Reserve University, where I was doing my undergrad studies. After learning about the AI-DO challenges, I was like, well, I’ll give it a try! It’s a challenge. I’m pretty competitive. So it took some trying and it ended up, I would say, good enough for where I was back then.

The other thing I looked into was Duckietown’s large code base for demonstrations because I was mainly working on answering the question: “what can you do with limited computing power for a system?”. I tested out the demos, and the Autolab idea, and tried to work on some improvements.

Back in 2019, there wasn’t a lot of work being done on that, unfortunately, but a good part of what was available had been tested, and the documentation was well-proofread. I then took over as a team lead for University of Toronto’s Autonomous Vehicle team, a role less involved with the project, but I still used Duckietown as a great introduction idea, of course.

We have a lot of students who are joining our team with almost no background in autonomous driving, and the Duckietown materials serve as a very good introduction idea to basically educate the younger students on the concept of autonomous vehicles.

Another thing I must say I learned a lot from is the Duckietown challenge and the evaluation side of the AI Driving Olympics, the evaluation server, and the idea of automated evaluation. I think I really gained a lot of experience and knowledge in testing and evaluating thanks to the Duckietown project.

Also along the way, I did another course project on a new baseline for the AI Driving Olympics or for what we call the conditional behavior cloning baseline. So that became another cross-project.

"It’s not only the cost-effectiveness but also the scalability of Duckietown and the potential it has to make a difference in key industrial sectors of the future."

"Frank" Chude Qian

It is great to hear that Duckietown helped you get comfortable with real self-driving cars. Is there anything else you would like to add?

Actually, yes. I know Duckietown is also planning on expanding its materials to the K-12 education side of things. I think that’s a great idea to get more students and younger folks excited about autonomous vehicles. And I think that one day autonomous vehicles will be more and more popular on the road, and the job market for developing and maintaining autonomous vehicles is going to be huge.

I really like the effort, and in fact, that’s probably something I’ll try to do: once I graduate from my current program, I’ll try to hop back on and further the development effort of expanding it to K-12 education.

Would you recommend Duckietown to students or colleagues?

Yeah, definitely! And I want to even sort of move it a step further.: for those students who want to get into autonomous vehicle research or development, but maybe their university doesn’t have much funding support for these kinds of programs, Duckietown is such a great project to just adopt.

You just start with the initial concept, and I’ve seen amazing research done thanks to Duckietown. I personally tried a couple of ideas, too. The one thing Duckietown can provide that nothing else can, as far as I can tell, at the same cost range is the development of multi-robot collaboration and the swarm robotics idea.

I think both of these features just provide great advantages for researchers and for students. You know, it’s a Jetson Nano plus some hardware. Or you can use the Raspberry Pi version. I think for students in the universities which don’t provide as much funding this could be a great starting point. And I personally learned so much throughout those projects, and ultimately that lead me to where I am today. So, yeah, definitely I would recommend it.

What would you say is the biggest quality of Duckietown?

I think from my experience with the AI-DO, it’s not only the cost effectiveness, but also the scalability of Duckietown and the potential it has to make a difference in key industrial sectors of the future.

Thank you very much!

Note from the editors: a few months after this interview, Frank started working as Software Simulation Developer at General Motors. Congratulations, Frank!

Learn more about Duckietown

The Duckietown platform enables state-of-the-art robotics and AI learning experiences.

It is designed to help teach, learn, and do research: from exploring the fundamentals of computer science and automation to pushing the boundaries of human knowledge.

Tell us your story

Are you an instructor, learner, researcher or professional with a Duckietown story to tell? Reach out to us!

Introduction to robotics at the University of Massachusetts Lowell using Duckietown

Posted on December 19, 2022 | by Ivano Marocchi

University of Massachusetts, Lowell, December 20, 2022: Paul Robinette, Assistant Professor at the University of Massachusetts Lowell (UML), shares with us his Duckietown teaching experience.

Introduction to robotics at the University of Massachusetts Lowell using Duckietown

Paul Robinette is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Lowell. He shares his experience, and that of his students, using Duckietown for teaching throughout the years. His “Fundamentals of Robotics” (EECE 4560/5560) course with Duckietown platform has been repeating since 2019.

Quick links

Thank you for finding the time to talk with us! Could you introduce yourself?

My name is Paul Robinette [Linkedin] and I’m a Professor of computer engineering at the University of Massachusetts Lowell [website].

When was your first experience with Duckietown?

My first experience with Duckietown would have been when I worked at MIT as a research scientist, just after Duckietown was run. I didn’t have a chance to see it live there, but I did talk with several of the postdocs who worked on it as it ran. I also saw it live for the first time at ICRA 2019.

Do you use Duckietown or did you use Duckietown in the past for some specific project or activity?

Sure! For the last three years, I’ve been using Duckietown robots in my class every semester. Primarily I use the Duckiebots to teach ROS and basic robot skills through the Duckietown system and infrastructure. I leverage the development infrastructure heavily and some of the course materials as well.

That sounds great! Can you tell us more about your ongoing class?

The class I teach every semester so far is called Fundamentals of Robotics [2022 class page], and we go over the basics of robotics, starting with multi-agent processing or multi-process systems, like most robots are these days, some basic networking problems, etc. The Duckiebots are perfect for that because they have Docker containers on board which have multiple different networks running. They have to work with the computer system, so it’s always at least interfacing with the laptop. The robots can be used with a laptop, with a router, you can have multiple robots out at once, and they give the students a really good sense of what moving real robots around feels like. We have students start by implementing some open loop control systems, then have them design their own lane detector, similar to the Duckietown [perception] demo, and then have them design their own lane controller again, similar to the Duckietown [lane following] demo.

Are your students appreciating using Duckietown? Would you consider it a success?

Yes, especially the newer version. The DB21s are great robots for using their class applications and infrastructure. The software infrastructure has made it pretty easy to set up our own Git repositories for the robots and be able to run them. In this way, students can run them at home or on campus.

Would you suggest Duckietown to your students or colleagues?

Yes, I’d suggest Duckietown, especially if people want to run an introductory robotics class and have every student purchase their own robot, or have the University provide the robots for all. Duckietown is much more affordable than any other robot system that could be used for this same purpose.

"In my class we go over the basics of robotics, starting with multi-agent processing or multi-process systems, like most robots are these days, and the Duckiebots are perfect for that"

Prof. Paul Robinette

It is great to hear Duckietown addresses your needs so well. What would you say is the advantage that Duckietown has when compared to other systems?

I’d say the expense is probably the biggest advantage right now. It’s a nice platform and very capable for what we wanted to do. At this point, the fact that it’s affordable for students to purchase on their own or for us to purchase a bunch of them is definitely the biggest advantage for us. You guys also have a really quick response time if we have any problems. It’s nice to be able to talk directly with the development team and work with them to set up the systems so that I can run them in my class as I need to.

Thank you very much for your time!

Learn more about Duckietown

The Duckietown platform enables state-of-the-art robotics and AI learning experiences.

It is designed to teach, learn, and do research: from exploring the fundamentals of computer science and automation to pushing the boundaries of knowledge.

Tell us your story

Are you an instructor, learner, researcher or professional with a Duckietown story to tell? Reach out to us!

Prof. Francesco Maurelli - Jacobs University

The Duckietown path to robotics: an interview with Prof. Francesco Maurelli

Posted on July 4, 2022 | by Ivano Marocchi

Jacobs University, Bremen, June 1, 2022: Francesco Maurelli, professor at the Jacobs University of Bremen, talks about how Duckietown impacted his work and his academic career.

The Duckietown path to robotics: an interview with Prof. Francesco Maurelli

Francesco Maurelli, professor at the Jacobs University of Bremen, Germany, shares in the interview below his interaction with Duckietown.

Quick links

Let’s start by simply asking your name, who you are, where you work, what you do for a living.

Hi, Federico. Hi, everyone. I am Francesco Maurelli and I’m a professor in robotics at Jacobs University in Bremen.

When was the first time you came across Duckietown in your life? Describe your first contact with Duckietown for us.

Well, that was in my team. I was there as a Marie Curie scholar from Europe. I met Andrea and Liam, and learned about this new initiative. I was interested so I spoke in depth with them and with the students who took the course. I then looked at the videos and thought it was a great setup because it brings robotics closer to the students in a fun way by reducing the access barrier. Many people think that robotics is very hard, which is true. I’m not saying it’s easy, but on the other hand, there are easier paths to access robotics. Additionally the element of gamification makes people happy when they work with Duckietown. I found that students want to get involved regardless of the course work, they just like the concept.

Thank you. Is there a specific thing that maybe you did using Duckietown in your life, a project, a program or some sort of ecosystem?

We have had three different initiatives based on Duckietown.

The first one, called Jacobs Robotics, was an extracurricular activity for students. I would meet interested students outside of class time, it wasn’t linked to academic credit. It was just for fun and for learning. Among the different robotics platforms, we had a group working on Duckietown. This was the initial step in using Duckietown at our university.

Then the second step was to embed Duckietown in the official curriculum. We have a bachelor’s program in robotics and intelligence systems, and I’m its program manager. We were rewriting and updating some parts of it as we underwent a new wave of accreditation. So I took the opportunity to redesign some aspects of the program and in this process decided to embed Duckietown at Bachelor level. I’ve introduced it at Ross Lab in simulation in the fall of the second year, in the third semester, and then we have a robotics project based on Duckietown in the spring, ofthe second year, (i.e. in the fourth semester). That means that when students start their third year, they already have an understanding of ROS, they have knowledge of Duckietown and they work with real systems. This means that they can do a much better thesis, even if it’s a Bachelor level, we can improve the average level. When I joined the University, the first month of the thesis was lost on students learning to use Ross, for example. Now we are a step ahead.

The third part is the research application. It’s not only a matter of having fun with students, or delivering courses to students, but also doing my own research. I have a project which is funded by the German Research Foundation, DFG, it is in collaboration with the psychology Department. The psychologists want to look at the characteristics that humans assign to entities to identify the “self”. We as roboticists are going to develop and program different robotic behaviors, which the behavioral scientist from the psychology department will analyze. In a nutshell, we will prepare different videos illustrating the same actions performed in different ways. A very basic example would be moving in a city at constant speed or moving in a city at variable speeds. Our partners in the psychology department will show these videos to the study participants and collect user feedback through questionnaires to determine which behaviors they think are more alike a self determined behavior.

This is extremely interesting. Thank you very much. Have you ever heard about the MOOC course?

Yes, actually. In fact I suggested to our students to look at the MOOC. Of course, it is set up in a different way with respect to our course, but it can be and it has been a useful tool for students to review some of the material through a different viewpoint. So it’s definitely a valuable learning material which is available to the community.

"It's not only a matter of having fun with students, or delivering courses to students, but also doing my own research."

Francesco Maurelli

Okay. My last question is would you suggest Duckietown to other people, colleagues or your students? And why?

Absolutely. I see that from my own experience, students like it and they learn a lot about robotics. All the different concepts ranging from control to localization to computer vision can be applied in Duckietown. So in our projects, in our robotics projects, different groups of students develop different ideas. And I see that they are enjoying themselves and they are learning. So it’s definitely a plus.

Thank you very much.

Learn more about Duckietown

The Duckietown platform offers robotics and AI learning experiences.

Duckietown is modular, customizable and state-of-the-art. It is designed to teach, learn, and do research: from exploring the fundamentals of computer science and automation to pushing the boundaries of knowledge.

Tell us your story

Are you an instructor, learner, researcher or professional with a Duckietown story to tell? Reach out to us!

Prof. Liam Paull - University de Montrèal

When rubber duckies meet the road: an interview with Prof. Liam Paull

Posted on May 10, 2022 | by Ivano Marocchi

UdM, Montréal, May 5, 2022: Liam Paull, professor at the University of Montreal and one of Duckietown’s founders, talks about his role and experiences with Duckietown.

When rubber duckies meet the road: an interview with Prof. Liam Paull

Liam Paull, professor at the University of Montreal in Quebec, and one of the very founders of Duckietown, shares below his unique perspective about Duckietown’s journey and its origin.

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Good morning, Liam.

Hello.

Thank you very much for accepting to have this little chat.
Could you tell us something about you?

Sure. So my name is Liam Paull. I’m a professor at the University of Montreal in Quebec, Canada. I teach in the computer science Department, And I do research on robotics.

Ok and when was the first time you “came across” Duckietown?

Well, I’m actually one of the creators of Duckietown, So I didn’t come across it as much! The origin story of Duckietown is kind of interesting, But I probably forgot some of the details. It must have been about 2015. And myself, Andrea Censi, and a few others were interested to get more teaching experience. We were all postdocs or research scientists at MIT at the time. I guess we started brainstorming ideas, and then roughly around that time, I switched positions at MIT. I was previously a postdoc in John Leonard’s group working on marine robotics, and then I switched to become part of Danielle Lerous lab and lead an autonomous driving project. And so somehow the stars just aligned. That the right topic for this class that we would teach would be autonomous driving. Yeah, the Ducky thing is kind of a separate thing. Actually, Andrea had started this other thing that was making videos for people to publicize their work at a top robotics conference Called the international conference robotics automation, and somehow had the idea that every single video that was submitted should have a rubber Ducky in it. And this was for scale or something.
There was some kind of reason behind it I sort of forget. But anyway, so the branding kind of caught fire.
When we were building the class, we agreed the one constraint was that there should be duckies involved somehow, and the rest is kind of history!

What’s your relationship with Duckietown today? Like, do you use it in particular for some activities, your daily work or some project? Yeah, for sure. I guess I use it in a number of ways. Maybe the first way is that I teach a class every fall called autonomous vehicles, Where the Duckietown platform is the platform that we use for the experiments and labs in the class. So just like the original class, Every student gets a robot that they assemble, and then we learn about computer vision and autonomous driving and all the good stuff related to robotics. But I also use the platform for some amount of research. Also in my group, I believe that there’s a lot of interesting research directions that come from a kind of standardized, small scale, accessible autonomous driving platform like this. Recently, most of the work that we’ve been doing in terms of research has been about training agents in simulation and then deploying them in the real world. So this isa nice setup for that because we have a simulator that’s very easy, fast and lightweight to train in, and then we have the environment that’s also really accessible. So, yeah, so we’ve been doing some research on that front.

So would you recommend Duckieown to colleagues or students of yours? And if yes, why. Of course. I think that’s what’s nice. Going back to the original motivation behind building Duckietowng and some of the tenets: thee guiding principle for us was this idea that to learn robotics, you have to get your hands on a robot. And we are also very adamant that it should be that every student should have their own robot. With teams of robots or going into the lab and only being able to use the robot at certain hours. It’s something funny.

You don’t develop the same kind of personal relationship. It sounds weird, but it’s true. Like when you have your own thing that you’re working with every day, you have some kind of bond with that thing, and you develop some kind of love or hate or whatever the case may be depending on how things are going on that particular day. So I think that with this set up, we have a platform where we’ve scaled things down and made things cost effective, to be able to do that. We built an engaging, experimental platform where it’s totally, I think, reasonable for most University budgets to be able to get their hands on the hardware.

"I believe that there's a lot of interesting research directions that come from a standardized, small scale, accessible autonomous driving platform like Duckietown."

Liam Paull

The other big piece is the actual teaching materials that we’ve developed. And I think that we have some good stuff. It could be better. Some stuff could be better, but that’s where we also need the community to come in. I mean, if we have this standardized platform and lots of people start using it and building educational experiences around the platform, then the entire thing just starts to get better and better for everybody. And it just grows into a very nice thing where you can also pick and choose the pieces that you want to include for your particular class, and you can customize the experience of what your class is going to look like using all of the resources that are out there. Also, the other part that I’ve really tried to cultivate, this is sort of a new thing. When we ran the first class at MIT, it was really an isolated thing. But in the subsequent iterations of the class, like myself and others have been in different places around the world, whether it’s Matt Walter at TTIC or Jacopo and Andrea at ETH. So we tried to turn the class into this kind of global experience, where you feel like you’re part of something that’s bigger than just the class that you’re taking at the specific University. And I think students really like that. We’ve experimented with different models where people do projects with other students from other universities or even just feeling part of the global community. I think it’s a very fun and engaging. Students are so connected these days. They’re so plugged in. They like this aspect of feeling like there’s a bit more of a broad social aspect, too. So I think these are some of the elements that this platform project experience brings to the table that I don’t see replicated and too many other setups.

Anything else you would like to add about Duckietown and it’s uses?

I didn’t mention specifically about the MOOC. One of the core missions of this project from the onset has been that it’s accessible. Both in terms of hardware but also in terms of software. And part of what that means to us Is that no matter where you are, no matter who you are, you should be able to get the hardware and you should be able to use the educational resources to learn. And part of the motivation for that Was that we saw that while we were at MIT. When you’re at a place like MIT you are extremely privileged and if you come from a background of less privilege, you see the discrepancy. In some sense, it’s palpable. Part of that, I guess, was that we don’t even necessarily want it to be a prerequisite that students should be enrolled in universities in order to be able to address the platform. So we built this massive online open source course through edx, which is also an open source provider Where people can, regardless of their background or regardless of their situation, they can sign up for this thing, and it’s a creative set of materials that also have exercises to interact with the robot that anybody can do, Regardless of whether they’re at a University or not.
I think this is the next step for us in making the platform accessible to all, and we’re going to continue to run iterations of this thing. But I also think that this is an exciting objective that very much fits in the mission of what we’re trying to do with this project.

This was great thank you for your time!

Awesome. Great. Thank you for your time. Bye.

Learn more about Duckietown

The Duckietown platform offers robotics and AI learning experiences.

Tell us your story

Are you an instructor, learner, researcher or professional with a Duckietown story to tell? Reach out to us!

Learning Autonomy with Vincenzo Polizzi

Posted on March 16, 2022 | by Ivano Marocchi

ETHZ, Zurich, March 11, 2022: How Vincenzo discovered his true professional passion as a student using Duckietown.

Learning Autonomy in practice with Vincenzo Polizzi

Vincenzo Polizzi studied robotics, systems and control at the Swiss Federal institute of Technology (ETH Zurich). Vincenzo shares below his experience with Duckietown. Starting off as a student, becoming a Teaching Assistant and onto how he uses Duckietown to power his own research as he moves from academia to industry.

Quick links

Could you tell us something about yourself?

I’m Vincenzo Polizzi , I studied automation engineering at the Politecnico di Milano, and I currently study robotics, systems and control at the Swiss Federal Institute of Technology (ETH Zurich).

You use Duckietown. Could you tell us when you first came into contact with the project, and what attracted you to Duckietown?

Sure! I learned about Duckietown my first year during a master’s program at ETH, where there was a course called: “Autonomous mobility on demand, from car to fleet” where I saw these cars, these robots. And I asked myself “what is this thing?”. It seemed very interesting. The first thing that struck me was that it did not look theoretical, but clearly practical.

"It captures you with simplicity and then you stay for the complexity."

Vincenzo Polizzi

So the idea of a practical aspect interested you?

Yes, during the presentation, it was clear that the course was based on projects the student had to carry out, where one could practice what they had learned theoretically in other classes.
I come from a scientific high school, and I studied automation engineering in Milan. In both my study experiences, I was used to learning concepts theoretically. For example, in the control system for a plant you design on paper in university, you don’t really face the complexity of implementing it on a real object.

I have to say that I have always been very passionate about robotics and informatics. In fact, even in high school, I was building these little robots,I participated in the robotics competition Rome Cup held by Fondazione Mondo Digitale, and there were these robots that were similar in shape to those of Duckietown, but where the scientific content was completely different. So in Duckietown, I saw something similar to what I was doing in my free time. I wanted to see exactly how it was inside, and there I discovered a whole other world that is obviously much more scientific than what a normal high school student could imagine by themself. However, initially I was curious to see a course where one can practice all the knowledge they have gradually acquired. It is not just about writing an equation and finding a solution but making things work.

What is your relationship with Duckietown, how long have you been using it? How do you interact with the Duckietown ecosystem? How do you use it, what do you do with it?

These are interesting questions because I started as a student and then managed to see what’s behind Duckietown. I was attending the course Duckietown held at ETH in 2019. The class was limited to 30 students, I was really excited to be part of it. I met many excellent students there, some of whom I am still in touch with today.

When I started the course, I immediately told myself, “Duckietown is a great thing. If all universities used Duckietown, this would be a better world.” I liked the class a lot, then I also had the opportunity of being a TA. The TAship was an important step because I learned more than during the course. One thing is to live the experience as a student who has to take exams, complete various projects, etc. You need a deeper understanding to organize an activity. You have to take care of all the details and foresee the parts of the exercise that can be harder or simpler for the students. This experience helped me a lot. For example, I did an internship in Zurich where we had to develop a software infrastructure for a drone, and I found myself thinking, “wow this can be done with Duckietown, we can use the same technologies.” I noticed that even in the industry, often we see the use of the same technologies and tools that you can learn about thanks to Duckietown. Of course, maybe a company has its own customized tools, probably well optimized for its products. Perhaps it uses some other specific tool but let’s say you already know more or less what these tools are about. You know because in Duckietown, you have already seen how a robotics system should work and the pieces it is composed of. Duckietown has given me a huge boost with the internship and my Master’s thesis at NASA JPL. Consider that my thesis was on a system of multi drones, so I used, for example, Docker as a tool to simulate the different agents. With Duckietown, I acquired technical knowledge that I used in many other projects, including work.

Do you still use it today?

The last project I did with Duckietown is DuckVision. I know we could have thought of a better name. With one of my Duckietowner friends, Trevor Phillips, we enhanced the Duckiebot perception pipeline with another camera, a stereocamera made by Luxonis and Open CV called OAKD (OpenCV AI Kit with depth). This sensor is not just a simple camera, but it also mounts a VPU, Visual Processing Unit. Namely, it can analyze and make inferences on the images that the camera acquires onboard. It can perform object detection and tracking, gesture recognition, semantic segmentation, etc. There are plenty of models freely available online that can run on the OAK-D. We have integrated this sensor in the Duckietown ecosystem, using a similar approach used in the MOOC “Self-Driving Cars with Duckietown”, we created a small series of tutorials where you can just plug the camera on the robot, run our Docker container and have fun! With this project, we passed the first phase of the OpenCV AI Competition 2021. The idea behind the project was to increase the Duckiebot understanding of the environment, by using the depth information, the robot can have a better representation of its surroundings and so, for example, a better knowledge of its position. Also, in our opinion, the OAK-D in Duckietown can boost the research in autonomous vehicles and perception.
I would like to add something about the use of Duckietown, I have seen this project both as a student and from behind the scenes and I really understood that by using this platform you really learn a lot of things that are useful not only in the academic field but can also be very useful in the working environment with the practical knowledge that is often difficult to acquire during school. And in this regard I thought then given my history, I am Sicilian but I studied in Milan and then I went to Zurich, I asked myself what can I bring as a contribution of my travels, so I thought about using Duckietown in some universities here in Sicily in the universities of Palermo and Messina. And also, at the Polytechnic of Milan, for example, they have already begun to use it and have participated in the AIDO and have also placed well, they ended up among the finalists, so there is a lot of interest in this project.

Did you receive a positive response every time you proposed Duckietown?

Yes, and then there is a huge enthusiasm on the part of the students. I spoke with student associations first, then with the professors etc. but when the students see Duckietown for the first time, they are always really enthusiastic about using it.

"There is something that captures you in some way, and then just opens up a world when you start to actually see how all the systems are implemented. This is the nice thing in my opinion, you can decide the level of complexity you want to achieve."

Vincenzo Polizzi

The duck was a great idea!

Absolutely right! The duck was a great idea, yes. I like contrasts, you see a super simple friendly thing that hides a state-of-the-art robotics platform. Even in the students I saw this reaction, because the duck is the first thing you see, it looks like a game, something to play with, this is the first impact, then when you start you get curious. It captures you with simplicity and then you stay for the complexity.

Would you suggest Duckietown to friends and colleagues?

Sure! There is something that captures you and opens up a world when you start to see how all the systems are implemented. This is the nice thing in my opinion, you can decide the level of complexity you want to achieve. It’s a platform that looks like something to play with, a game or something, but in reality there is a huge potential, in terms of knowledge that everyone can acquire, it’s something that you can not easily find elsewhere. I also think it offers great support, such as educational material, exercises that are of high quality. You can learn a lot of different aspects of robotics, in my opinion. You can do control, you can do the machine learning part, perception . There’s really a world to explore. You can see everything there is about robotics. But you can also just focus on one aspect that maybe you’re more passionate about. So yes, I would recommend it because you can learn a lot, and as a student myself I would recommend it to my fellow colleagues.

Learn more about Duckietown

The Duckietown platform offers robotics and AI learning experiences.

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Robert Moni’s experience after winning AI-DO 5

Posted on January 16, 2021 | by Liuxin

An interview with Robert Moni

Robert is a Ph. D. student at the Budapest University of Technology and Economics.

His work focuses on deep learning and he has (co)authored papers on reinforcement learning (RL), imitation learning (IL), and sim-to-real learning using for autonomous vehicles using Duckietown.

Robert and his team won the LFV_multi hardware challenge of the 2020 AI Driving Olympics.

Today, Robert shares some of his thoughts with us!

What brought you to work on AVs?

I started my journey in the world of AV’s in 2016 when I was hired at the automotive supplier company “Continental” in Romania. In 2018 I moved to Budapest, Hungary, to join Continental’s Deep Learning Competence Center where we develop novel perception methods for AVs.

In 2019, with the support of the company, I started my Ph.D. at Budapest University of Technology and Economics on the topic “Deep Reinforcement Learning in Complex environments”.

At this time, I crossed paths with the Duckietown environment. Continental bought 12 Duckiebots and supplementary materials to build our own Duckietown environment in a lab at the university.

Tell us about you and your team

At the beginning of my Ph. D. and with the arrival of the Duckietown materials we established the “PIA” (Professional Intelligence for Automotive) project with the aim to provide education and mentorship for undergrad and master students in the field on Machine Learning and AV.

In each semester since 2019 February I managed a team of 4-6 people developing their own solutions for AI-DO challenges. I wrote a short blogpost presenting my team and our solutions submitted to AI-DO 5.

"With the arrival of the Duckietown material we established the PIA project with the aim to provide education and mentorship for undergrad and master students in the field on Machine Learning and autonomous vehicles (AV)."

Robert Moni

What approach did you choose for AI-DO, and why?

I started to tackle the AI-DO challenges applying deep reinforcement learning (DRL) for driver policy learning and state representation learning (SRL) for sim2real transfer.

The reason for my chosen approach is my Ph. D. topic, and I plan to develop and test my hypotheses in the Duckietown environment.

What are the hardest challenges that you faced in the competition?

In the beginning, there was a simple agent training task that caused some headaches: finding a working DRL method, composing a good reward function, preprocessing the observations to reduce the search space, and fine-tuning all the parameters. All these were challenges, but well-known ones in the field.

One unexpected challenge was the continuous updates of the gym-duckietown environment. While we are thrilled that the environment gets improved by the Duckietown team, we faced occasional breakdowns in our methods when applying them to the newest releases, which caused some frustration.

The biggest headache was caused by the different setups in the training and evaluation environments: in the evaluation environment, the images are dimmed while during training they are clear. Furthermore, the real world is full of nuisances – for example lags introduced by WiFi communication, which causes different outcomes in the real environment. This challenge can be mitigated to some degree with the algorithms running directly on the Duckiebot’s hardware, and by using a more powerful onboard computer, e.g., the Jetson Nano 2GB development board.

Are you satisfied with the final outcome?

I am satisfied with the achievements of my team, which kept the resolve throughout the technical challenges faced.

I’m sure we would’ve done even better in the real-world challenge if we had seen our submission running earlier in the Autolab, so we could have adjusted our algorithms. We are going to work to bring one to our University in the next future.

What are you going to change next time?

I believe the AI-DO competition as well as the Duckietown platform would improve through more powerful hardware. I hope to see Duckiebots (DB19) upgraded to support the new Jetson Nano hardware!

(Since the date of the interview, Duckiebots model DB21 supports Jetson Nano boards)

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Community Spotlight: Arian Houshmand – Control Algorithms for Traffic

Posted on January 28, 2020 | by Jacopo Tani

Boston University, March 7, 2019: No one likes sitting in traffic: it is a waste of time and damaging to the environment. Thankfully researcher Arian Houshmand from Boston University CODES lab is on the case, and he’s using Duckietown to help solve the problem.

Quick links

Control algorithms to improve traffic

Traffic congestion around the world is worsening, according to transport data firm INRIX. In the U.S. alone, Americans wasted an average of 97 hours in traffic in 2018 – that’s two precious weekends worth of time. Captivity in traffic also costs them nearly $87 billion in 2018, an average of $1,348 per driver. Clearly, the need for smart transportation is reaching a fervor, not only to alleviate the mental and financial state of drivers, but to address the significant economic toll on affected cities. Fortunately, development of intelligent mobility technologies is advancing. In an ongoing research project funded by the U.S. Department of Energy’s (DOE) Advanced Research Projects Agency-Energy (ARPA-E) NEXTCAR program, BU researchers in collaboration with researchers from University of Delaware, University of Michigan, Oak Ridge National Lab, and Bosch are developing technologies for Connected and Automated Vehicles (CAVs) to increase their fuel efficiency and as a bi-product reduce traffic congestion.

The goal

The goal of this project is to design control and optimization technologies that enable a plug-in hybrid electric vehicle (PHEV) to communicate with other cars and city infrastructure and act on that information. By providing cars with situational self-awareness, they will be able to efficiently calculate the best possible route, accelerate and decelerate as needed, and manage their powertrain. This is an important task toward advancing the vision to create an ‘Internet of Cars,’ in which connected and self-driving cars operate seamlessly with each other and traffic infrastructure, improving fuel efficiency and safety, and reducing traffic congestion and pollution.

Today’s commercially-available self-driving cars rely on costly sensors, specifically radar, camera, and LIDAR (light) to operate semi-autonomously. In the NEXTCAR project, BU researchers with project collaborators are looking to go beyond that by developing decision-making algorithms to improve the autonomous operation of a single hybrid vehicle as well as algorithms for communications between vehicles and their environment, enabling self-driving cars to cooperate and interact within their socio-cyber-physical environment.

Several different functions have been developed throughout this project including:

● Eco-routing: Procedure of finding the optimal route for a vehicle to travel between two points, which utilizes the least amount of energy costs.

● Eco-AND (Economical Arrival and Departure): An optimal control framework for approaching a traffic light without stopping at the intersection by having traffic light cycle time information.

● CACC (Cooperative Adaptive Cruise Control): An extension of adaptive cruise control

"We use Duckietown to train students on how to implement their algorithms on embedded systems and also as a means to demonstrate our developed technologies in action and in a live setting."

Arian Houshmand

(ACC) that by benefiting from vehicle to vehicle (V2V) communication increases the safety and energy efficiency by reducing headway.

In order to validate and test the developed technologies, researchers first use simulation environments to test the algorithms. After verifying through simulation, they implement the algorithms on Duckietown, and finally deploy them on real cars (Audi A3 e-tron) at the University of Michigan’s M-city (test track for self-driving cars).

We use Duckietown to train students on how to implement their algorithms on embedded systems and also as a means to demonstrate our developed technologies in action and in a live setting. Since most of our research focuses on Connected and Automated Vehicles (CAVs), we need to establish connections between individual Duckiebots and traffic lights. As a result, we created a platform for exchanging information and control commands between all the cars and traffic lights.

Online localization of Duckiebots is a challenging task, and is missing from the current framework. We relied on our external motion capture sensors (OptiTrack) to localize the robots.

Duckietown is a nice platform for performing experiments on autonomous robots since It is relatively simple to set up the town and Duckiebots. Moreover, the built in perception and lane keeping capabilities are very useful to kick off experiments quickly. Traffic lights and signs are also helpful to create different scenarios for testing algorithms in city-like scenarios.

What would make Duckietown even more useful in our application is feedback sensors for determining wheel rotational speed/position as it is difficult to correct for rotational speed errors of the wheels and a ROS node for exchanging information between robots and traffic lights for testing collaborative control algorithms.

Learn more about Duckietown

The Duckietown platform enables state-of-the-art robotics and AI learning experiences.

It is designed to help teach, learn, and do research: from exploring the fundamentals of computer science and automation to pushing the boundaries of human knowledge.

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STEM Intensive Learning with Prof. Krinkin

Posted on November 18, 2019 | by Duckietown Admin | 1 Comment

In the world of engineering education, there are many excellent courses, but often the curriculum has one serious drawback – the lack of good connectivity between different topics. Over in Saint Petersburg, Russia, Kirill Krinkin from SPbETU and JetBrains Research has been using Duckietown to address this problem through an intensive STEM winter course.

STEM Intensive Learning Approach

by Kirill Krinkin

The first part of the school program was a week of classes in the base topic areas which were chosen to complement each other and help students see the connection between seemingly different things – mathematics, electronics and programming.

Of course, the main goal of the program was to give students the opportunity to put their new found knowledge into practice themselves.

Duckietown was the perfect fit for our course because it offered a hands-on learning experience for all of our main topics areas, and once we covered those subject in the first lessons, we challenged the students with much more complex tasks – in the form of projects – in the second half of the course. It made for an exciting and engaging curriculum because students could address a problem, write a program to solve it, and then immediately launch it on a real robot.

The main advantage of Duckietown compared to many other platforms is that there is a very small learning curve: people who knew nothing about programming and robotics started working on projects after only a few days!

Overview of the course

Part 1 – Main Topic Areas

Subject 1: Linear Algebra

Students spent one day studying vectors and matrices, systems of linear equations, etc. Practical tasks were built in an interactive mode: the proposed tasks were solved individually, and the teacher and other students gave comments and tips.

Subject 2: Electricity and Simple Circuits

Students studied the basics of electrodynamics: voltage, current, resistance, Ohm’s law and Kirchhoff’s laws. Practical tasks were partially done in the electric circuits simulator or performed on the board, but more time was devoted to building real circuits, such as logic circuits, oscillatory circuits, etc.

Subject 3: Computer Architecture

In a sense, a bridge connecting physics and programming. Students studied the fundamental basis, the significance of which is more theoretical than practical. As a practice, students independently designed arithmetic-logic circuits in the simulator.

Subject 4: Programming

Python 2 was chosen as the programming language, as it is used in programming under ROS. After we taught the material and gave examples of solving problems, students were challenged with their own problems to solve, which we then evaluated.

Subject 5: ROS

Here the students started programming robots. Throughout the school day, students sat at computers, running the program code that the teacher talked about. They were able to independently launch the basic units of ROS, and also get acquainted with the Duckietown project. At the end of this day, students were ready to begin the design part of the course – solving practical problems.

Part 2 – Projects

1. Calibration of colors

Duckiebots needs to calibrate the camera when lighting conditions change, so this project focussed on the task of automatic calibration. The problem is that color ranges are very sensitive to light. Participants implemented a utility that would highlight the desired colors on the frame (red, white and yellow) and build ranges for each of the colors in HSV format.

2. Duck Taxi

The idea of this project was that Duckiebot could stop near some object, pick it up and then continue along, following a certain route. Of course, a bright yellow Duckie was the chosen passenger. The participants divided this task into two: detection and movement along the graph.

drive while Duckie is not detected

Duckie identified as a yellow spot with an orange triangle 🙂

Building a route according to the road graph and destination point

3. Building a road map

The goal of this project was to build a road map without providing a priori environmental data for the Duckiebot, relying solely on camera data. Here’s the working scheme of the algorithm developed by the participants:

4. The patrol car

This project was invented by the students themselves. They offered to teach one Duckiebot, the “patrol”, to find, follow, and stop an “intruding” Duckiebot. The students used ArUco markers to identify the Intruder on the road as they are easy to work with and they allow you to determine the orientation and distance of the marker. Next, the team changed the state machine of the Patrol Duckiebot so that when approaching the stop-line the bot would continue through the intersection without stopping. Finally, the team was able to get the Patrol Duckiebot to stop the Intruder bot by connecting via SSH and turning it off. The algorithm of the patrol robot can be represented as the following scheme:

Summary

Students walked away from our STEM intensive learning program with the foundations of autonomous driving, from the theoretical math and physics behind the programming and circuitry to the complex challenges of navigating through a city. We were successful in remaining accessible to beginners in a particular area, but also providing materials for repetition and consolidation to experienced students. Duckietown is an excellent resource for bringing education to life.

After our course ended students were asked about their experience. 100% of them said that the program exceed their expectations. We can certainly say that the Duckietown platform played a pivotal role in our success.

Duckietown in Ghana – Teaching robotics to brilliant students

Posted on August 13, 2018 | by VincentMai

July 2018: Vincent Mai travels from Canada to teach a 2-week Duckietown class to some of the brightest high school students in Ghana.

The email – Montreal, January 2018

On the morning of January 29th, 2018, I received an email. It was a call for international researchers to mentor for two weeks a small group of teenagers that will have been selected among the brightest of Ghana. Robotics was one of the possible topics.

At 4 pm, I had applied.

I was lucky enough to grow up in a part of the world where sciences are available to children. I spent summers in Polytechnique Montreal, playing with electro-magnets and making rockets fly with vinegar and baking soda. I also remember visiting the MIT Museum in Boston, where I was impressed by the bio-inspired swimming robots. There is no doubt that these activities encouraged 17-years-old me to choose physics engineering as my bachelor studies, which then turned into robotics at the graduate level.

The MISE Foundation

The call from the MISE Foundation was a triple opportunity.

First, I could transmit the passion I was given when I was their age. Second, I would participate, in my small, modest way, in the reduction of education inequalities between developing an developed countries. Countries like Ghana can only benefit from brilliant Ghanaians considering maths, computer science or robotics as a career.

Finally, it was an unique opportunity for me to discover and learn, from people living in an environment that is totally different from mine, with other values, objectives and challenges. It is not everyday you can spend two weeks in Ghana.

After some exchanges with Joel, the organizer, with motivation letters, project plan and visa paperwork, it was decided: I was going to Accra from July 20th to August 6th.

The preparation – Montreal, June 2018

My specialty is working with autonomous mobile robots: this is what I wanted to teach. I was going to see the brightest young minds of a whole country. I needed to challenge them: I could not go there with a drag-and-drop programmed Lego.

I chose an option that was close to me. Duckietown is a project-based graduate course given at Université de Montréal by my PhD supervisor, Prof. Liam Paull. It allows students to learn the challenges of autonomous vehicles by having miniature cars run in a controlled environment. A Duckiebot is a simple 2-wheel car commanded by a Raspberry Pi. Its only sensor is a camera.

Along with my proximity with Duckietown, I chose it because making a Duckiebot drive autonomously is a very concrete problem, which involves a lot of interesting concepts: computer vision, localization, control, and integration of all these on a controller. Also, for teenagers, the Duckie is a great mascot.

I had not yet taken the Duckietown course. Preparing took me one month and a half of installing, reverse engineering, and documenting. The objective I designed for the kids? Having a Duckiebot named Moose follow the lanes with a constant speed, without getting out of the road or crossing the middle line.

It was inspired from a demo that was already implemented in the Duckiebot. I could not ask the kids to implement the whole code, so I cut out only the most critical parts of it. I also wrote presentations, exercises, planning each of the 10 days we would spend together, 6 hours a day. I packed the sport mats to do the road, a couple of extra pieces in case something broke, and the print-outs of the presentations. I was ready.

Packed Duckietown

Or, I hoped I was. It was not simple to adapt the contents of a graduate course for kids of whom I had no idea of the math and programming level. Did they know how to multiply matrices? What about Bayes law? Can I ask them to use Numpy? When I asked advice to Liam, he told me with a smile: “I guess you’ll have to take the go with the flow…”

The building – Accra, August 2018

Accra is a large city, spread along the shore of the Atlantic Ocean. Its people are particularly smiling and welcoming. The Lincoln Community School, a private institution hosting the MISE Foundation summer school, has beautiful and calm facilities which allowed us to give the classes in a proper environment. There were 24 children in total: 12 were training for the International Maths Olympics with two mentors, while three teams of 4 students would work with a mentor on projects like mine. The two other projects were adversarial attacks on image classifiers and stereo vision.

The first two days, we did maths. I tested their level: they did not know most of what was necessary to go on. Vector operations, integrals, probabilities… We went through these in a very short time: they amazed me by the speed at which they understood.

For the next five days, we went through the project setup. We started simple, understanding how we can drive the Duckiebot with a joystick. We had to setup Moose, discover ROS, and use it to send commands to the motors.

We followed with the real project: autonomous mobile robotics.

See-Think-Act cycle;
computer vision for line extraction, from RGB images to Canny edge detection and Hough transform;
camera calibration for ground projection, from image sensors to homography matrix;
Bayesian estimator for localization, with dynamic prediction and measurement update;
and finally, proportional control for outputting the right commands to the wheels.

Building Moose

Moose the Duckiebot, up and running!

For each of these steps, the students wrote their version of the code. Then, we made a final version together that we implemented in Moose.

The experiments – Accra, August 2018

In the two next days, the students had to think what they would do for their research projects. The experiments would be done together but the projects should be individual. Each of them decided to focus on one aspect of autonomous cars. Kwadwo decided to go for speed: he tested the limits of the car as if it was an autonomous ambulance. Abrahim was more concerned about safety: was Moose better than humans at driving? Oheneba thought about the reduction glasshouse gas emissions and William about lowering the traffic. In both cases, they argued that if autonomous cars could improve the situation, they first had to be accepted by humans and therefore be safe and reliable. They tested Moose in differently lit scenes, with white sheets on the road (snow) or with a slightly wrong wheel calibration, to see how it would cope with these conditions.

On the last day, they individually presented their research to a committee formed by the three project mentors. We asked them difficult questions for 15 minutes, testing them and pushing them to think above what they had learned in these 2 weeks. We judged them based on the Intel ISEF criteria (Research project, Methodology, Execution, Creativity and Presentation).

Presenting in front of the judging committee

The closing ceremony – Accra, August 2018

Saturday was parents day. The students made a general presentation of their projects, making the parents laugh uneasily every time they asked “Is everything clear?” At least, I think most of the parents enjoyed the demonstration: it is always nice to see a Duckiebot run!

Finally, at the closing ceremony, the students who had the best presentation grades were rewarded. I was proud that Kwadwo was named Scholar of the Year, winning a Mobile Robotics book and the right to represent Ghana at the Intel ISEF conference in Phoenix, Arizona, in May 2019. He will present his project with the Duckiebot!

The students and organizers also gave each of us a beautiful gift: a honorary scarf on which it is written “Ayeekoo”. In the local languages, it means: “Job well done.”

I hope I did my job well, and that William, Oheneba, Kwadwo and Abrahim will remember Moose the Duckiebot when they choose their careers. I know that, in any case, these four brilliant young men will continue to shine. On my side, I really enjoyed the experience. I will make sure I don’t miss an opportunity to teach again to teenagers using Duckietown, whether it is in another country or here, in Montreal.

The best team!

Important note

I had four boys in my group. You can notice on the picture below that, out of the 24 students, only 3 girls participated in the MISE Foundation program. When I asked Joel about it, he told me he has a very difficult time getting women to participate. At least 6 more girls were invited, but their parents would pressure them not to do maths and science, and discourage them from going to the Summer School. They feel this is not what a woman should be doing. I find this situation very frustrating. Ghana is a country with strong family values that are different from the ones I am used to. It is not our role as international researchers to tell them what is good and what is not. And, to be fair, software engineering presents similar ratios in Canada, even if the reasons are less tangible (maybe?).

On the other hand, engineers and scientists build the world around us, and they do so according to the needs they feel. Men cannot build everything women need. I strongly encourage any girl, in any country, who reads this blog post and who is interested about maths and computer science, to stand for what they want to do. We need you here, to build tomorrow’s world together.

MISE 2018 – Ayeekoo!

You can help the Duckietown Foundation fund similar experiences in Africa and elsewhere in the world by reaching out and donating.

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