The Duckietown project was conceived in 2016 as a graduate class at the Massachusetts Institute of Technology (MIT).
The goal was to build a platform that was small-scale and accessible yet still preserved the scientific challenges inherent in a full-scale real autonomous robot platform.
The first class had 24 students, over 15 postdocs, and 5 professors involved in the initial development.
The course culminated with a year-end demo showcasing the capabilities of the platform in a full-sized hockey rink in Cambridge, MA.
There were over 3000 visitors.
After the 2016 class, many of the key organizers left MIT for other opportunities.
In the meantime, all of the pieces of the experience (the slides, the demos, the platform, the software) were made openly available and other institutions began to take interest.
First adopters, precursors of many more universities, included NCTU in Taiwan, Tsinghua University in China, and Rensselaer Polytechnic Institute in the United States.
In the Fall of 2017, Liam Paull (Montréal), Andrea Censi and Jacopo Tani (ETHZ), Matthew Walter (TTIC), and Hsueh-Cheng Wang (NCTU) decided to teach an officially coordinated edition of the class. In this version, students from classes at ETH Zürich, Université de Montréal, TTI Chicago, and NCTU worked collaboratively in groups that spanned continents.
The result was a global demo that showcased the students’ achievements to the general public.
The requests from universities, companies, and makedemics around the world to use the platform started increasing dramatically.
To support this growth, the Duckietown platform had to become more affordable, easier to obtain, and of higher-quality, so as to provide more learning experiences and opportunities for performing cutting-edge research while creating the least possible entropy as the user base increased in size.
The Duckietown Foundation debuted the AI Driving Olympics (AI-DO), a competition focused on AI for self-driving cars, in December 2018 at the premiere machine learning conference: Neural Information Processing Systems conference (NeurIPS) in Montreal.
It was the first competition to ever take place at a machine-learning conference with real robots.
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 picks up on the project and includes Duckietown in their “Driverless: Who is in control?” exhibition.
(Pictures are courtesy of the Board of the Science museum of London.)
In August 2023, several Duckietown objects officially joined the Science Museum Group permanent Collection: the United Kingdom’s national archive of science, technology, engineering, and medicine.
This 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.”
The permanent collection can be browsed from here:
Duckiebot – small autonomous robot from Duckietown Project, 2018-2019
Traffic light kit from Duckietown Project, 2018-2019
City expansion pack from Duckietown Project, 2018-2019
The Duckietown Foundation supported the creation of the world’s first robot autonomy massive open online course with hardware.
Self-Driving Cars with Duckietown is hosted on the edX platform, and the first cohort in 2021 counted over 7000 learners from over 170 countries.
The course development was spearheaded by ETH Zurich, and developed in collaboration with the University of Montreal and the Toyota Technological Institute at Chicago.