AI-DO I Interactive Tutorials

The AI Driving Olympics, presented by the Duckietown Foundation with help from our partners and sponsors is now in full swing. Check out the leaderboard!

We now have templates for ROS, PyTorch, and TensorFlow, as well as an agnostic template.

We also have baseline implementation using the classical pipeline, imitation learning with data from both simulation and real Duckietown logs, and reinforcement learning.

We are excited to announce that we will be hosting a series of interactive tutorials for competitors to get started. These tutorials will be streamed live from our Facebook page.

See here for the full tutorial schedule.

Updated duckietown-challenges server fixes speed problems; updated “dts commands evaluate”

As we have more participants, the Duckietown Challenges Server started to feel slow. The reason: we were a bit lazy and some pages had O(n) implementations where O(1) was needed - loading all challenges/submissions/etc.

We also updated the "dts challenges evaluate" command to be more robust. Please continue to report bugs as this part is fragile by nature --- running containers that spawn other containers on the user's machines.

Announcing the AI Driving Olympics (AI-DO)

Press release

The Duckietown Foundation is excited to announce the official opening of the The AI Driving Olympics, a new competition focused around AI for self-driving cars.

The first edition of the AI Driving Olympics 2018 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 competition will use the Duckietown platform, a scaled-down affordable and accessible vision-based self-driving car platform used for autonomy education and research. This open-source project originated at MIT in 2016 and is now used by many institutions worldwide.

The AI Driving Olympics is presented in collaboration with 6 academic institutions: ETH Zurich (Switzerland), Université de Montréal (Canada), NCTU (Taiwan), TTIC (USA), Tsinghua (China) and Georgia Tech (USA), as well as two industry co-organizers: nuTonomy and Amazon Web Services (AWS).

The competition will comprise 5 challenges of increasing complexity: 1) Road following on an empty road; 2) Road following with obstacles; 3) Point-to-point navigation in a city network; 4) Point to point navigation in a city network with other vehicles; and 5) Fleet planning for a full autonomous mobility on demand system.

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.

 

The competition aims at directing academic research towards the hard problems of embodied AI, such as modularity of learning processes, and learning in simulation while deploying in reality. The competition also promotes the democratization of AI/robotics research by offering a common infrastructure available to everybody through the use of remote testing facilities.

Competitors can also build their own Duckiebots using provided DIY instructions, or buy Duckiebots and Duckietown hardware through a kickstarter campaign.

For rules and time line, please see the site http://AI-DO.duckietown.org/