The Duckietown Foundation is excited to announce the official opening of the The AI Driving Olympics (AI-DO), a new competition focused around AI for self-driving cars.
The first edition of the AI-DO will take place in December 2018, at NIPS, the premiere machine learning conference, in Montréal. This is the first competition that will take place at a machine learning conference with real robots.
The second edition of AI-DO is already scheduled to take place in May 2019 in conjunction with the International Conference on Robotics and Automation (ICRA) 2019.
The main purpose of the competition is to probe the frontier of the state of the art in machine learning in the interactive and embodied setting.
Recent progress in Deep Learning, Machine Learning, and Reinforcement Learning has produced incredible results. This competition is designed to evaluate the real ability for these learning-based systems to control physical mobile robots.
Competitors will have access to simulators, logs, reference implementations, and finally real environments (“Robotariums”) that will be remotely accessible for evaluation. The entries that score best in the Robotariums will be run during the live event at NIPS 2018 to determine the winners.
Quotes from the experts
“The AI Driving Olympics is a great way to push the limits of deep learning on physically embodied systems.”
— Yoshua Bengio, University of Montreal
“The AI Driving Olympics offer a glimpse of the challenges of creating self-driving cars. A playful but rigorous competition on a smaller and safer testbed is the best way to develop the creativity needed to make progress in this field.”
— Emilio Frazzoli, ETH Zurich / nuTonomy
“It is great to see Duckietown host the AI Driving Olympics at ICRA and NIPS. What a fun way to demonstrate the real challenges in building and deploying self driving cars!”
— John Leonard, MIT
“Starting from MIT CSAIL, Duckietown has grown into a global initiative that is inspiring students around the world to learn about self-driving cars, as well as the science and engineering of autonomy.“
— Daniela Rus, MIT