Boston, October 2023: several Duckietown objects officially joined the Science Museum Group permanent Collection: the United Kingdom’s national archive of science, technology, engineering, and medicine!
Duckietown joins UK's Science Museum Group Collection
Duckietown is a trailblazer in providing accessible solutions for teaching and learning state-of-the-art autonomy, helping in the dissemination of the science and technology of modern robotics.
In 2019, the Science Museum of London picked up on the project and included Duckietown items: a Duckiebot (DB19), a segment of Duckietown, and a Duckietown traffic light, in their “Driverless: Who is in control?” exhibition.
Following the success of this exhibition, the Board of Directors of the Science Museum started considering including the DUckietown items in the permanent collection of their institution.
We are proud to announce that, in August 2023, these Duckietown items have officially joined the Science Museum Group Collection – the UK’s national collection of science, technology, engineering and medicine.
Duckietown in the history books
Joining the permanent collection will:
“ensure that the items – as rare and representative objects – are acquired, conserved, preserved and stored in order that they may be accessible to current and future generations for interpretation, loans to other institutions, research, education, and sometimes display in temporary or permanent exhibitions.”
here are some details:
2023-216
E2019.0205.1
Duckiebot – small autonomous robot from Duckietown Project, 2018-2019
2023-222
E2019.0205.2
Traffic light kit from Duckietown Project, 2018-2019
2023-502
E2019.0205.3
City expansion pack from Duckietown Project, 2018-2019
Westminster, Maryland: MAGIC and Duckietown partner to bring robot autonomy education in Westminster, MD.
The Mid-Atlantic Gigabit Innovation Collaboratory (MAGIC) was awarded funding from the Knorr-Bremse Global Care program in July of 2022 to launch an Autonomous Robotics Innovation Center (ARIC) in the heart of downtown Westminster.
Their goal for ARIC is to use the Duckietown platform to give Westminster students industry-relevant skills and hands-on experience that will prepare them for careers or further learning in robotics and engineering.
Bringing industry relevant skills and hands-on experience to high school and undergrad students
We are very pleased to announce our partnership with MAGIC, bringing the Duckietown platform to Carroll County students and introducing the local community to robotics and AI technology.
MAGIC is a 501(c)3 non-profit organization headquartered in Westminster, MD, USA. Their mission is to build a technological ecosystem that creates and nurtures talent, entrepreneurship, and tech businesses, elevating the Westminster Gigabit community to lead the Mid-Atlantic region.
We talked with Graham Dodge, Executive Director of MAGIC, to know more about their new Autonomous Robotics Innovation Center (ARIC) project and how Duckietown is being used in this context.
Hi! Could you introduce yourself?
My name is Graham Dodge. I’m the executive director of Magic Inc., a 501(c)3 non-profit based in Maryland, United States. We focus on technology, education, and workforce development within our community.
Thank you for taking the time for this interview, Graham. How did you learn about Duckietown?
I was speaking with the CEO of a local company called Dynamic Dimension Technologies. We were discussing our autonomous corridor project in the city of Westminster, Maryland. He recommended using Duckietown as a platform to demonstrate some of the technologies to local elected officials and stakeholders. After seeing videos of Duckietown on their website, I was impressed by its user-friendly and cute approach to making technology accessible to people unfamiliar with computer vision and robotics. It seemed like a perfect way to explain these concepts to our community.
Very interesting! What are you using Duckietown for?
Initially, we used Duckietown to demonstrate autonomous technologies for our corridor project. However, we later secured funding and set up the Autonomous Robotics Innovation Center (ARIC), where we now use Duckietown for a broader robotics program. In ARIC, we teach students ROS, Python, Linux, and the documentation that comes along with Duckietown. Additionally, we plan to integrate railroad intersections with Duckietown, thanks to grant funding from Knorr-Bremse Global Care program in Germany, a train parts manufacturer involved in autonomous train systems.
“We’re seeing that students with very minimal computer science education can jump right into Duckietown and excel”.
Graham Dodge
That’s impressive, so you are integrating Duckietown with a rail system?
Yes, we are considering names like Duckierail or Duckietrains. This project aims to develop open-source solutions for Duckiebots to interact with trains and railroad crossings. We are excited to collaborate with the Knorr-Bremse Global Care program, who provided the funding, to showcase rail systems in a smart, connected infrastructure with autonomous vehicles.
We can’t wait to see the developments! Are you satisfied with your experience with Duckietown so far?
Absolutely! We started with a small MOOC kit, and despite lacking an internal instructor, two student interns managed to get the Duckiebots up and running within three months. The hands-on experience has been rewarding for them, and it’s remarkable how much they’ve learned. We are now expanding the program and have plans to engage with local colleges as well.
That’s fantastic! So, do you see Duckietown as a valuable tool for education and career development in the robotics industry?
Yes, absolutely! Our goal is to set up an apprenticeship program for career pathway development. By providing students with hands-on experience through Duckietown, we aim to make them more attractive to local employers in the robotics industry. The students are already gaining valuable skills that match or even exceed those of some graduate students seeking internships with the same employers.
“We’ve had industry professionals and local employers look at what we’re teaching and say that what our high school interns are learning and building with Duckietown is more advanced – and more industry relevant – than most of the undergraduate students they’ve seen”.
Graham Dodge
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.
Boston, 7-11 July 2023: Congratulations to the fourth cohort of students of the Duckiedrone summer academy, hosted by Massrobotics, Brown University and Duckietown with the generous support of Amazon Robotics!
Exploring the skies at the summer Duckiedrone academy
As the sun shines high, the summer Duckiedrone academy, a program which sees the cooperation of Duckietown, Amazon Fulfillment Technology and Robotics, MassRobotics and Brown University, has attracted high school students from the greater Boston area to dive into the world of autonomous aerial vehicles.
The Duckiedrone is a DIY, open, Raspberry Pi-based quadcopter kit designed for introducing learners to autonomous flight. Comes with a polished undergraduate-level course and the support of the Duckietown international community.
Students learned how to build, program, and fly a drone starting from a box of components, in addition to participating in workshops held by industry professionals such as Stephanie Tellex, Associate Professor of Computer Science at Brown University, and Andrea Francesco Daniele, Chief Technology Officer at Duckietown.
In recent years autonomous robots have started revolutionizing many industries, and drones are playing an important role in this ongoing trend with applications from agriculture to inspection, surveillance, and warehouse management.
These versatile flying machines are a gateway to the fundamentals of robot autonomy, especially (but not only!) for younger learners. Seeing a machine fly on its own is exciting!
The Duckiedrone comes with step-by-step instructions for assembly, calibration, manual and autonomous operations. Students learn from the basics of mechatronics, such as soldering and handling of electrical circuits, to elements of autonomy including sensor calibration, middlewares (ROS), PID control, online filtering and simultaneous localization and mapping (SLAM) using Python and interactive Jupyter notebooks.
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.
IIT Jodhpur, June 03, 2023: Prof. Debasis Das of IIT Jodhpur, Rajasthan, India, tells us about his experience in bringing Duckietown to his lab to support the teaching, research, and outreach efforts of his team in the fields of autonomous vehicles, robotics, computer vision, machine learning.
Robotics education and research at IIT Jodhpur: an interview with Prof. Debasis Das
Hello Professor Das, thank you for your time in taking our questions. How did you learn about Duckietown?
I learned about the Duckietown project through a variety of sources, including online platforms like social media, discussion forums, and academic publications, where many researchers and robotics enthusiasts have shared information related to the project. Additionally, some of my collaborators have also mentioned the project and its educational and research goals. Through these sources, I gained an understanding of what the Duckietown project is and the impact it has had in the field of robotics education and research.
This is great to hear! Starting from the education aspects, what classes are you teaching at IIT Jodhpur using Duckietown?
Duckietown is being used for a variety of classes and educational programs, primarily in the fields of computer science and engineering at IIT Jodhpur. Most recently we have utilized the platform to teach the following classes:
Vehicular Ad Hoc Networks: This class focuses on the design, development, and testing of autonomous vehicles using the Duckietown platform to simulate real-world scenarios.
Robotics and Mobility: This class teaches students the principles of mobility and the role of machine learning for decision-making, using the Duckietown platform for practical exercises.
What has your and your students’ experience been in these courses?
We have found that hands-on learning experiences, such as those provided by Duckietown, are more effective in increasing students’ knowledge and capacity to recall topics than standard lecture-based teaching approaches.
Furthermore, the dynamic and fascinating elements unique to Duckietown increase students’ passion for and interest in their assignments.
We have received large positive feedback for Duckietown from students and researchers who have used it at IIT Jodhpur, with many appreciating its entertaining and challenging nature. The platform’s scalability and ease of use across a wide range of disciplines and programs are commendable. Students also appreciate the opportunity to learn programming and problem-solving with real-world robotics difficulties.
Though there may be some disparities in how each student utilizes the platform and what they gain in terms of education and enjoyment, the data thus far suggests that Duckietown can be a helpful and fun resource for students working in robotics and related fields.
"The Duckietown platform has been a valuable resource in supporting our research activities. We have used it as a tool for engaging with the broader community and promoting interest in science, technology, engineering, and STEM fields, including hosting workshops, competitions, and other events that showcase the capabilities of autonomous vehicles and provide opportunities for hands-on learning and exploration."
Are you using Duckietown to support your research activities too?
Yes, the Duckietown platform has been a valuable resource in supporting our research activities. We have used the platform to test and evaluate novel algorithms and methods for autonomous vehicle design and control, and to investigate issues such as computer vision, machine learning, and control systems.
Are there other ways Duckietown has helped you conduct teaching, research, and outreach efforts?
We have used Duckietown as a tool for engaging with the broader community and promoting interest in science, technology, engineering, and mathematics (STEM) fields. We have hosted workshops, competitions, and other events that showcase the capabilities of autonomous vehicles and provide opportunities for hands-on learning and exploration.
Would you suggest Duckietown to your colleagues?
Yes, I would definitely recommend Duckietown to my colleagues who are interested in teaching and researching areas such as autonomous vehicles, robotics, computer vision, machine learning, and control systems.
Duckietown provides a realistic and scalable environment for testing and assessing novel algorithms and methods for autonomous vehicle design and control, as well as a platform for engaging students and the general public in learning and discovery in these domains.
"We have received large positive feedback for Duckietown from students and researchers who have used it at IIT Jodhpur, with many appreciating its entertaining and challenging nature. The platform's scalability and ease of use across a wide range of disciplines and programs are commendable."
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.
“La Sapienza” University of Rome, April 28, 2023: Shima Akbari, a Ph.D. student at the Italian National Program in Autonomous Systems, shares her experience working with Duckietown for her master’s thesis on lane following control for mobile robots.
Shima's work on control strategies for lane following
Hi, thank you for joining us today. Could you introduce yourself?
Certainly. My name is Shima Akbari, and I have a degree in Control Engineering from “La Sapienza” University of Rome. Currently, I am a Ph.D. student in the Italian National Program in Autonomous Systems.
You recently obtained your master’s degree, congratulations! You worked on lane following control approaches for mobile robots using Duckietown. How did you discover Duckietown?
I first learned about Duckietown while working on my master’s thesis. I have always been passionate about control and autonomy, particularly in mobile robots. However, I didn’t want to limit my project to theoretical calculations or computer simulations. I wanted to have a practical component to my work. When I shared this with my supervisor, Professor Oriolo, he introduced me to Duckietown and suggested that I conduct my experiments in this environment. So I implemented the lane following control in the Duckietown environment as part of my master’s thesis, using both the Duckietown simulator called Duckietown Gym, and the Duckiebots, which are the robots used in Duckietown. I thoroughly enjoyed every minute of conducting my tests.
It’s great to hear you enjoyed working with Duckiebots! Tell us a little more about your project and what was your experience like.
My thesis focus was on computer vision based control. I used OpenCV, the well known computer vision library, and the camera mounted on the Duckiebots to extract lane lines from the streets in Duckietown. Based on information extracted from these features, I implemented control laws that enabled the Duckiebot to drive on the streets inside lanes.
To familiarize myself with the platform, I started by taking the Duckietown massive open online course on edX and completed the assignments and homework on my own. One of the modules was about implementing a PID controller for lateral position and another on steering rate control. I enjoyed the Braitenberg vehicles activity too, but my favorite project was on obstacle avoidance, obstacle detection, and computer vision.
"In engineering, true learning comes from practical implementation, and Duckietown offers that opportunity effectively."
You are studying in a field that is statistically dominated by male presence. What are your thoughts on this?
It’s indeed the case. According to recent statistics, only 16% of women are in engineering compared to 84% of men. While I acknowledge this disparity, I believe that women are just as capable as men in engineering or any other field. Moreover, I think that the situation is improving over time. If we look at statistics from 10 to 20 years ago, the percentage of women in engineering was even lower.
What would you say to a young woman who wants to study engineering and may be discouraged by the statistics?
I would tell her that statistics and other people’s opinions should not deter her from pursuing her interest in engineering or any other subject. She should follow her dreams and not be discouraged by external factors.
Thank you for this thought, we hope this interview will help it reach as many women thinking about pursuing engineering careers out there as possible.
Absolutely. I would recommend Duckietown to anyone interested in learning about autonomous systems, regardless of their background or gender. It provides an excellent opportunity to learn about autonomy and control in a practical and user-friendly way. In engineering, true learning comes from practical implementation, and Duckietown offers that opportunity effectively.
What would you consider to be the unique value or appeal of Duckietown? What makes it special?
I would say that the simplicity of Duckietown is its most appealing aspect. The robots are designed to be simple and easy to use, and working with them is a lot of fun. Additionally, Duckietown has excellent support, with comprehensive documentation and manuals that are written in a detailed, step-by-step manner. Even if you don’t have a strong background in tools like Linux or Docker, you can still make progress by reading and following the documentation
"Duckietown is simple and has excellent support, with comprehensive documentation and manuals that are written in a detailed, step-by-step manner. Even if you don't have a strong background in concepts like Linux or Docker, you can still make progress by reading and following the documentation."
Thank you very much for taking the time to share your experience with us, we really appreciate it. Is there anything else you would like to add?
I’d just like to express how amazing it was for me to be introduced to and work with Duckietown. I would highly recommend it to others 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.
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”.
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."
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.
University of Toronto, February 3, 2022: “Frank” Chude Qian, A Master Student at the University of Toronto, shares with us his experience with Duckietown.
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."
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.
For the third year, the University of Nevada, Reno’s Computer Science & Engineering (CSE) department conducted a Research Experience for Teachers (RET) program focused on “Integrating Big Data into Robotics.”
Through the six-week program, participants were able to gain hands-on robotics experience that can be applied in classrooms later, in a fun, nontraditional way.
Duckietown, an engineering and robotics/artificial intelligence (AI) project, focuses on accessible and engaging styles of learning. The project started at the Massachusetts Institute of Technology in 2016 as a graduate class, where they created a video “Duckumentary” highlighting the background and purpose of the research project but also its adaptability for varying age groups.
This year’s University project was taught by Ph. D. candidate and instructor Amirhesam Yazdi as well as CSE associate professor and principal investigator Lei Yang.
Participants were able to learn how to assemble the robots, build and design the track, and program the robots and the track.
“Duckietown is a freely available robotics platform and curricula for all levels of education. It is tangible, accessible, and fun. It has mobile robots and roads, constructed from exercise mats and tape,” Yang said. “The mobile robots are built from off-the-shelf parts and using open-source software and the curricula, such as lectures and exercises are provided on the Duckietown website. These unique features set Duckietown apart from other engineering, robotics and/or AI projects.”
Tell us your story
Are you an instructor, learner, researcher or professional with a Duckietown story to tell? Reach out to us!
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.
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"
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.
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.
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."
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.
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.
