Author: Duckietown Admin

Professor Peter Affolter of BFH portrait

Driving autonomy education at BFH with Prof. Affolter

Posted on | by Duckietown Admin

Bern, Switzerland: Prof. Peter Affolter, Head of the automotive department at Berner Fachhochschule (BFH), shares his experience creating a curriculum in autonomy education with Duckietown. Quick links Bern University of Applied Science Prof. Peter Affolter @ BFH Prof. Peter Affolter Driving autonomy

Bern, Switzerland: Prof. Peter Affolter, Head of the automotive department at Berner Fachhochschule (BFH), shares his experience creating a curriculum in autonomy education with Duckietown.

Quick links
Students controlling Duckiebots at BFH

Driving autonomy education with Duckietown

Prof. Affolter at the Bern University of Applied Sciences introduces autonomy education in the automotive curriculum

Hi! Thank you for taking the time to chat with us. I'd like to start by asking you to introduce yourself, and tell us who you are and what you do.

Certainly! My name is Peter Affolter. I am at the head of the automotive department at the Bern University of Applied Science. I work as a lecturer in autonomous driving, vehicle communications, and related areas.

How did you get to know Duckietown?

The first time I saw it was probably two or three years ago. I came across it by chance while Googling on the internet. I was looking for information about lessons and classes on autonomous driving, a very complicated topic. I was searching for an easy platform, especially hardware, to simulate a simple vehicle. Then, I stumbled upon Duckietown. Initially, it looked a bit childish, but I was surprised by its concept, quality, and comprehensive documentation, including lessons slides for this complex theory. I decided to focus on Duckietown, especially on the massive online open course hosted on edX [Self-Driving Cars with Duckietown]. I also really enjoyed the great support from all the stakeholders and universities involved in this initiative.

Students learning robotics in at BFH with Duckietown
Did you find the "Self-Driving Cars with Duckietown", the massive open online course (MOOC) on edX, helpful?

Yes, at that time, there was only the archive available on edX.org, and I registered there. I couldn’t participate in real-time, but I went through the materials myself. I also contacted the Duckietown staff, and they provided me with support and missing documents. I adapted the content for my own class, focusing on bachelor-level students, parallel to the massive online open course from edX.

Very interesting, so you adapted the materials for your course. How did you set up the class, did you find any challenges?

It was clear to me that I could introduce our students, future automotive engineers, to autonomous driving. I wanted to give them an overview of the potential, limits, obstacles, and areas needing progress. Since they were not programmers or IT technologists, I needed to simplify it. I decided to conduct whole-class courses using video material from the MOOC. I adapted the quizzes and provided them with virtual machines, avoiding Linux and network issues. They could use the vehicles hosted on the BFH server farm through a browser terminal, even utilizing the Duckiebots. It became an infrastructure for exercises from simulation to reality, based on Duckietown classes.

How did the teaching experience go?

The first class had potential for improvement, but we adopted a flipped classroom approach with four lessons a week for 16 weeks. Students studied theory at home, and class time was for exercises, discussions, and additional explanations. The students enjoyed it, and while they didn’t grasp every detail, they felt proud and motivated. There’s still plenty of room for improvement in the next classes. They grasped the feeling and had the chance to work on neural networks, image manipulations, and more. I made good progress, and there’s still plenty of material to explore and implement in future classes.

Honestly, I haven't found another hardware platform as good as Duckietown for my needs. It's a simple platform with a fun approach, well-documented, and with a really reactive community. Even compared to other commercial products, Duckieown stands out. It fulfills all the needs from beginners to experts.

Prof. Peter Affolter, Head of Automotive Dept. at BFH
What were your overall impressions introducing autonomy education to your students with Duckietown?

Honestly, I haven’t found another hardware platform as good as Duckietown for my needs. It’s a simple platform with a fun approach, well-documented, and with a really reactive community. Even compared to other commercial products, Duckietown stands out. It fulfills all the needs from beginners to experts.

Thank you again for sharing your experience with us. Best of luck in your next classes!

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.
Get started with Duckietown!
Read other Duckietown stories

Tell us your story

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

Reach out to us!

Duckietown Sky logo

Duckiedrone: how to fly a Raspberry Pi-based autonomous quadcopter

Posted on | by Duckietown Admin

Boston, 20 October 2023: Duckietown Sky and the Duckietown drone, a Raspberry Pi-based autonomous quadcopter, are discussed with the Aerial ROS community, a group of experts working to define the future of software architectures for quadcopters.  

Quick links

Learning robot autonomy by flying with Duckietown Sky

Following an invitation to the Aerial ROS workgroup community meeting, Duckietown staff was delighted to present the Duckietown Sky initiative, the current Duckiedrone design, a DIY Raspberry Pi-based autonomous quadcopter, and future plans for both hardware and courseware development.

Download the presentation

The goal of the ROS (Robotic Operating System) aerial robotics working group is to gather drone enthusiasts within the ROS community and facilitate the sharing of ideas and discussion of issues regarding autonomous robotic platforms operating in the air.

Duckietown Sky, a National Science Foundation-funded educational effort in collaboration with Brown University started in 2019, is an integral component of the Duckietown education vision, representing the commitment to fostering robot autonomy education in all its forms. Beyond self-driving cars (Duckiebots) and smart cities (Duckietowns), Duckietown highlights what is common despite the different applications of robot autonomy. From ground to sky, whether it drives, flies, or blinks, Duckietown is a platform to learn, explore and innovate when it comes to robot autonomy.

With the focus on quadcopters, Duckietown Sky offers MOOC-style learning experiences tailored for undergraduate and senior high school students. Flight is exciting! 

The program’s design criteria revolves around achieving state-of-the-art autonomy ground-up using off-the-shelf components, with a Raspberry Pi as core computational unit, for its wide-spread applications and large community.  Duckiedrones, now at the second hardware design iteration moving towards the third, aim to provide students with hands-on learning experiences covering from the basics, such as soldering, to pretty advanced algorithmic cornerstones of autonomy such an UKFs (Unscented Kalman Filters) and SLAM (Simultaneous Localization and Mapping). 

Aspiring engineers should however be prepared for preliminary requirements like soldering, have access to a laptop or base station, and an internet connection for setting the working environment up. 

Duckiedrone Operation Manual
Duckiesky Instructor Manual

From a box of parts to a Raspberry Pi-based autonomous quadcopter

Duckietown Duckiedrone model DD21 - happy yellow box
Duckietown Duckiedrone model DD21 - what's in the box?

The Duckietown Sky experience is an exciting journey that begins with a simple box of parts and culminates in the creation of an autonomously flying drone. In the Duckietown spirit of democratizing access to the science and technology of autonomy through accessible platforms, the happy-yellow Duckiebox includes almost everything needed to get flying. 

We encourage instructors, students and practitioners to check the development roadmaps for both our hardware design and courseware, outlined in our presentation, and reaching out without hesitation to provide comments or feedback! 

Building on the extensive experience of the Duckietown team in massive open online courses (check out the Self-Driving Cars with Duckietown MOOC: the world’s first robot autonomy MOOC with hardware), we look to prepare a series of short online courses. These courses will be led by Professors from Brown, as well as other universities, and will provide an ever broader audience with the opportunity to explore the fascinating world of robot autonomy: from the science and technology to the tools and workflows, to real-world applications presented by industry and academic leaders. 

Duckiedrone Raspberry Pi-based autonomous quadcopter isometric view
Duckiedrone Raspberry Pi-based autonomous quadcopter top view

Want to try the Duckietown Sky experience yourself, build a DYI Raspberry Pi-based autonomous quadcopter, or teach an aerial autonomy class at your high school or at university level? Follow the steps below to begin now.

1. Get the Duckiedrone
2. Build the Duckiedrone
3. Fly the Duckiedrone

Learn more about Duckietown

Duckietown 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.

Get Started with Duckietown!
Request a quote for your class
Felix Donoso Duckietown POD

Practical and playful: Duckietown talks with Prof. Donoso

Posted on | by Duckietown Admin
FĂ©lix Donoso, Associate Professor at Duoc UC uses Duckietown to teach his students about the science and technology of autonomy in a practical and playful way.

Santiago de Chile, 17 October 2023: Learn how FĂ©lix Donoso H., Associate Professor at the School of Computer Science and Telecommunications at the Duoc UC Professional Institute, utilized the Duckietown platform to engage with students and teach them complex concepts in a practical and playful way.

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Happy students use Duckietown

Practical and playful, an interview with Prof. Donoso

Hi! Could you introduce yourself?

My name is FĂ©lix Donoso H. I hold a Master’s degree in Education, specializing in Teaching for Higher Education. I am also an Engineer in Connectivity and Networks and have a Diploma in Applied Research and Innovation. I have been working in higher education for 8 years. Currently, I am an Associate Professor at the School of Computer Science and Telecommunications at the Duoc UC Professional Institute. I am involved in various projects at the Center for Innovation and Technology Transfer.

We read on the DUOC website about your Duckietown class, could you tell us a little more about it?​
At the Center for Innovation and Technology Transfer of the School of Computer Science and Telecommunications at DuocUC, we have recently implemented Duckietown to offer our students hands-on experience in robotics and autonomous vehicles. The workshops are designed to teach fundamental concepts of control, computer vision, and machine learning, using the Duckietown platform to provide a hands-on and cutting-edge yet accessible experience.
top view of duckiebots on a section of duckietown, rubber duckies scattered around, traffic signs
side view of duckiebots on a section of duckietown, rubber duckies scattered around, traffic signs
What is the pedagogical focus of your learning activities?
The pedagogical approach is and will be eminently practical and collaborative. We want students to not only understand theoretical concepts but also apply them in a real environment. Collaboration among students is essential, fostering teamwork and problem-solving in a practical context.
How did you learn about Duckietown?​
I learned about Duckietown during a robotics course at the University of Chile. The platform was presented as an innovative educational tool, and I was intrigued by its potential to teach complex concepts in an accessible and attractive way.
What is the thing you liked most about using Duckietown in your class?​
What I liked most about using Duckietown was the ability to bring abstract concepts to real life. Students were able to see how their algorithms and codes work in a tangible and entertaining environment, making the concepts easier to understand and more appealing.
How did your students react to the course?​

The students responded very positively.
The practical and playful nature of the course allowed them to actively engage
in learning, and many expressed that the experience with Duckietown has been
one of the most memorable in their education. 

Pablo Zapata, a fourth-year student of Computer Engineering and one of the project members, highlights that “my experience has been incredible, as I entered an area that is not part of our curriculum, and for this reason, we have learned to build robots and work with different components. This project has surprised me a lot because of the
technology we are using, and at the same time, it has greatly enriched us over
time.”

On the other hand, NĂ©stor Carvacho, a second-year student in the Computer Programmer Analyst career, points out that “I have been able to work with cutting-edge technology and, with it, learn new work tools that are not part of my career; like Linux, which will help me
in my future work.”

Duckietown has allowed students from different campuses of the school of computer science and telecommunications at Duoc UC to immerse themselves in the world of robotics and autonomous vehicles, Linux, ROS, and Python, in an accessible and exciting way.

FĂ©lix Donoso H.
Felix donoso and two colleagues kneeling behind a duckietown setting (duckietown, duckiebots, traffic signs)
How would you recommend we improve the platform?
Although the platform is excellent, it could benefit from more resources and tutorials aimed at different levels of experience. It would also be helpful to have more examples of projects and applications in different fields to inspire students and showcase the versatility of the platform.
Would you like to add anything else?

I would just like to emphasize how valuable the Duckietown platform has been to our institution. It has allowed students from different campuses of the school of computer science and telecommunications at Duoc UC to immerse themselves in the world of robotics and autonomous vehicles, Linux, ROS, and Python, in an accessible and exciting way. I am eager to see how the platform evolves and how we can continue to use it in the future with the practical challenges we are preparing.

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.
Get started with Duckietown!
Read other Duckietown stories

Tell us your story

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

Reach out to us!

Three girls watching Duckiebot - Science museum

Duckietown to join the UK Permanent Science Museum Collection!

Posted on | by Duckietown Admin

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! 

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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

Get Started with Duckietown!
Request a quote for your class
Prof. Das- IIT Jaidpur

Robotics education and research at IIT Jodhpur: an interview with Prof. Debasis Das

Posted on | by Duckietown Admin

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.

Quick links

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.
VANET lab team at IIT Jodhpur - Prof. Debasis Das

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."

Prof. Debasis Das
Visit to Prof. Das Duckietown research lab at IIT Jodhpur

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.

Lab visit to VANET@IITJ - outreach effort using Duckietown

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."

Debasis Das

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.

Get Started with Duckietown!
Find out more use cases

Tell us your story

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

Ubuntu laptop terminal interface with hands operating keyboard, Duckiebot and duckies out of focus in foreground

“Self-Driving Cars with Duckietown” MOOC starting soon

Posted on | by Duckietown Admin

Join the first hardware based MOOC about autonomy on edX!

Are you curious about robotics, self-driving cars, and want an opportunity to build and program your own? Set to start on March 22nd, 2020, “Self-Driving Cars with Duckietown” is a hands-on introduction to vehicle autonomy, and the first ever self-driving cars MOOC with a hardware track!

Designed for university-level students and professionals, this course is brought to you by the Swiss Federal Institute of Technology in Zurich (ETHZ), in collaboration with the University of Montreal, the Duckietown Foundation, and the Toyota Technological Institute at Chicago.

Learning autonomy requires a fundamentally different approach when compared to other computer science and engineering disciplines. Autonomy is inherently multi-disciplinary, and mastering it requires expertise in domains ranging from fundamental mathematics to practical machine-learning skills.

This course will explore the theory and implementation of model- and data-driven approaches for making a model self-driving car drive autonomously in an urban environment, while detecting and avoiding pedestrians (rubber duckies)!

Enroll for free on edX

In this course you will learn, hands-on, introductory elements of:

  • computer vision
  • robot operations 
  • ROS, Docker, Python, Ubuntu
  • autonomous behaviors
  • modelling and control
  • localization
  • planning
  • object detection and avoidance
  • reinforcement learning.
Duckietown Duckiebot model DB21J4 on a lane

The Duckietown robotic ecosystem was created at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) in 2016 and is now used in over 90 universities worldwide.

“The Duckietown educational platform provides a hands-on, scaled down, accessible version of real world autonomous systems.” said Emilio Frazzoli, Professor of Dynamic Systems and Control, ETH Zurich, “Integrating NVIDIA’s Jetson Nano power in Duckietown enables unprecedented access to state-of-the-art compute solutions for learning autonomy.”

Pedestrian detection: there are many obstacles in Duckietown - some move and some don't. Being able to detect pedestrians (duckies) is important to guarantee safe driving.
Enroll for free on edX

This massive online open course will be have a hands-on learning approach using, for the hardware track, real robots. You will learn how autonomous vehicles make their own decisions, going from theory to implementation, deployment in simulation as well as on the new NVIDIA Jetson Nano powered Duckiebots.

“The new NVIDIA Jetson Nano 2GB is the ultimate starter AI computer for educators and students to teach and learn AI at an incredibly affordable price.” said Deepu Talla, Vice President and General Manager of Edge Computing at NVIDIA. “Duckietown and its edX MOOC are leveraging Jetson to take hands-on experimentation and understanding of AI and autonomous machines to the next level.”

The Duckiebot MOOC Founder’s edition kits are available worldwide, and thanks to OKdo, are now available with free shipping in the United States and in Asia!

Get the Hardware in the USA or Asia
Get the Hardware in the rest of the world

“I’m thrilled that ETH, with UMontreal, the Duckietown Foundation, and the Toyota Technological Institute in Chicago, are collaborating to bring this course in self-driving cars and robotics to the 35 million learners on edX. This emerging technology has the potential to completely change the way we live and travel, and the course provides a unique opportunity to get in on the ground floor of understanding and using the technology powering autonomous vehicles,” said Anant Agarwal, edX CEO and Founder, and MIT Professor.

Enroll now and don’t miss the chance to join in the first vehicle autonomy MOOC with hands-on learning!

Enroll for free on edX

Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents

Posted on | by Duckietown Admin

Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents

Why is this important?

As robotics matures and increases in complexity, it is more necessary than ever that robot autonomy research be reproducible.

Compared to other sciences, there are specific challenges to benchmarking autonomy, such as the complexity of the software stacks, the variability of the hardware and the reliance on data-driven techniques, amongst others.

We describe a new concept for reproducible robotics research that integrates development and benchmarking, so that reproducibility is obtained by design from the beginning of the research/development processes.

We first provide the overall conceptual objectives to achieve this goal and then a concrete instance that we have built: the DUCKIENet.

The Duckietown Automated Laboratories (Autolabs)

One of the central components of this setup is the Duckietown Autolab (DTA), a remotely accessible standardized setup that is itself also relatively low-cost and reproducible.

DTAs include an off-the-shelf camera-based localization system. The accessibility of the hardware testing environment through enables experimental benchmarking that can be performed on a network of DTAs in different geographical locations.

The DUCKIENet

When evaluating agents, careful definition of interfaces allows users to choose among local versus remote evaluation using simulation, logs, or remote automated hardware setups. The Decentralized Urban Collaborative Benchmarking Environment Network (DUCKIENet) is an instantiation of this design based on the Duckietown platform that provides an accessible and reproducible framework focused on autonomous vehicle fleets operating in model urban environments. 

The DUCKIENet enables users to develop and test a wide variety of different algorithms using available resources (simulator, logs, cloud evaluations, etc.), and then deploy their algorithms locally in simulation, locally on a robot, in a cloud-based simulation, or on a real robot in a remote lab. In each case, the submitter receives feedback and scores based on well-defined metrics.

Validation

We validate the system by analyzing the repeatability of experiments conducted using the infrastructure and show that there is low variance across different robot hardware and across different remote labs. We built DTAs at the Swiss Federal Institute of Technology in Zurich (ETHZ) and at the Toyota Technological Institute at Chicago (TTIC).

Conclusions

Our contention is that there is a need for stronger efforts towards reproducible research for robotics, and that to achieve this we need to consider the evaluation in equal terms as the algorithms themselves. In this fashion, we can obtain reproducibility by design through the research and development processes. Achieving this on a large-scale will contribute to a more systemic evaluation of robotics research and, in turn, increase the progress of development.

If you found this interesting, you might want to:

Join the AI-DO
Get your Autolab
Join our Slack
Prof. Krinkin

STEM Intensive Learning with Prof. Krinkin

Posted on | by Duckietown Admin | 1 Comment on STEM Intensive Learning with Prof. Krinkin


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.