What we do
Compete in the 5th AI Driving Olympics (AI-DO) The 5th edition of the Artificial Intelligence Driving Olympics (AI-DO 5) has officially started! The AI-DO serves
Duckietown and NVIDIA work together for accessible AI and robotics education: Meet the NVIDIA powered Duckiebot
Duckietown and NVIDIA partnership for accessible AI and robotics education NVIDIA GTC, October 6, 2020: Duckietown and NVIDIA align efforts to push the boundaries of
The AI Driving Olympics (AI-DO) is back! We are excited to announce the launch of the AI-DO 3, which will culminate in a live competition event
Team JetBrains came out on top on all 3 challenges It was a busy (and squeaky) few days at the International Conference on Robotics and
Mathematical models allow us to predict the future. But are they always trustworthy?
In this video from the “#selfdrivingcars with #Duckietown” MOOC on @edXOnline we discuss the modeling of a differential drive #robot.
RT @MassRobotics: Day 6 (Boys 3week Jumpstart Program) – Making drones!
Thank you @BrownUniversity & @spaceguytye #amazon #amazonscience…
Representations of the robot and its environment are fundamental to the capabilities that make a vehicle autonomous: to sense, plan and act.
#learningautonomy #Duckietown #selfdrivingcars #robotics #stem #AI
How do we get machines to behave the way we want them to, as opposed to how they would naturally behave?
Design and deploy a control system yourself on real hardware with the “Self Driving cars with #Duckietown” MOOC!
#LearningAutonomy #Robotics #AI
An important challenge in #learningautonomy is harmonizing what we want to do with how we will do it. Deploying the logical architecture on the physical one, accounting for available resources and computation is an often overlooked but delicate matter.
Vehicle autonomy emerges from feedback loops. The notion of state of the robot and the world around it enables more advanced autonomous behaviors than direct sensorimotor connections.
#Duckietown #learningautonomy #selfdrivingcars #robotics
RT @foxglovedev: Check out our latest blog post to see how you can use @DuckietownAI’s Duckiebot & Foxglove Studio to build & visualize you…
Autonomous behaviors emerge from feedback loops. Even with very simple sensor-actuation connections, inspired by simple organisms, we can make Duckiebots behave in fascinating ways. Learn more about sensorimotor autonomy architectures with #Duckietown on
What is version control, and why is it important? In this video, we give an overview of #Git.
Want to learn more about #autonomousveichles? Join the @ETH_en “Self Driving Cars with #Duckietown” MOOC on @edXOnline!
The @ETH_en “Self-driving cars with Duckietown” MOOC on @edXOnline is based on #Docker.
What is containerization? In this video, we give an overview.
#learningautonomy #robotics #stem #AI
Get started with the platform
The Duckietown project
Duckietown started as a class at MIT in 2016. You can watch the “duckumentary” created about the first class.
Duckietown is now a worldwide initiative to realize a new vision for AI/robotics education.
Since 2018 the project is coordinated by the non-profit Duckietown Foundation.
The Duckietown platform
The platform has two parts: Duckiebots and Duckietowns.
Duckiebots are low-cost mobile robots that are built almost entirely from off-the-shelf parts. The only onboard sensor is the forward-facing camera.
Duckietowns are the roads, which are constructed from exercise mats and tape, and the signage which the robots use to navigate around.
Duckietown for education
The Duckietown platform designed as part of an a university AI/robotics curriculum.
It has been used in prestigious universities, such as MIT, ETH Zürich, and Université de Montréal.
We are developing a “class-in-a-box” that comprises lectures, exercises, and theory, that combine with the physical robot platform to reinforce the core concepts.
If you are an instructor interested in using Duckietown, read here to get started.
Duckietown for research
The Duckietown platform has also been used extensively for research on mobile robotics and physically embodied AI systems.
If you are a researcher, read more about getting started about using the platform for research. See also: papers using Duckietown, the researchers using Duckietown.
Duckietown for “Makademics”
Makademics (makers + academics) are people who want to learn and build on their own and also want a very deep understanding of how things are working.
We want to allow everybody to learn AI/robotics even if they are not at elite institutions like MIT and ETH Zürich.
With Duckietown you can easily build your own robot, and follow along our lectures and interact with a global community of learners.