Round 3 of the the AI Driving Olympics is underway!

Posted on October 29, 2019 | by Liam Paull

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 to be held at NeurIPS this Dec. 13-14.

The AI-DO is a global robotics competition that comprises a series of events based on autonomous driving. This year there are three events, urban (Duckietown), advanced perception (nuScenes), and racing (AWS Deepracer). The objective of the AI-DO is to engage people from around the world in friendly competition, while simultaneously benchmarking and advancing the field of robotics and AI.

Check out our official press release.

Learn more about the AI-DO competition here.

If you've already joined the competition we want to hear from you!

Share your pictures on facebook and twitter.

Duckietown Workshop at RoboCup Junior

Posted on June 19, 2019 | by Jacopo Tani

Duckietown Workshop at RoboCup Junior 2019

In collaboration with the RoboCup Federation, the Duckietown Foundation will be offering workshops at RoboCup 2019 in Sydney, Australia, providing a hands-on introduction to the Duckietown platform.

We will be hosting three one-day workshops as part of RoboCup 2019 from July 4-6, 2019 for teachers, students, and independent learners who are interested in finding out more about the Duckietown platform. Attendance is completely free and everyone is welcome to apply, even if you are not participating in RoboCup.

There are no formal requirements, though basic familiarity with GNU/Linux and shell usage is recommended.

If you would like to apply to attend a workshop, please complete this form.

We will have Duckiebots and Duckietowns for participants to use. However, you are more than welcome to bring your own Duckiebots, available for purchase at https://get.duckietown.com.

If you would like to apply to attend a workshop, please complete this form.

We will have Duckiebots and Duckietowns for participants to use. However, you are more than welcome to bring your own Duckiebots, available for purchase at https://get.duckietown.com.

Congratulations to the winners of the second edition of the AI Driving Olympics!

Posted on June 3, 2019 | by Jacopo Tani

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 Automation in Montreal for the organizers and competitors of the AI Driving Olympics.

The finals were kicked off by a semifinals round, where we the top 5 submissions from the Lane Following in Simulation leaderboard. The finalists (JBRRussia and MYF) moved forward to the more complicated challenges of Lane Following with Vehicles and Lane Following with Vehicles and Intersections.

If you couldn’t make it to the event and missed the live stream on Facebook, here’s a short video of the first run of the JetBrains Lane Following submission.

Thanks to everyone that competed, dropped in to say hello, and cheered on the finalists by sending the song of the Duckie down the corridors of the Palais des Congrès.

A few pictures from the event

: the validation tracks

: Team meeting

: Competitors at work

: DuckiePond

: Duckietown Junior

: A young Forbes roboticist

: Street name matching game!

: Street name matching game!

: Street name matching game!

: Street name matching game!

: Street name matching game!

: Street name matching game!

: Countdown to the finals

: Last minute touches on the slides

: Platform gurus

: Intro to the AI-DO, it’s as easy as a few lines of code

: The audience of AIDO2

: JetBrains saying a word or two

: Group shot with our winners!

Don't know much about the AI Driving Olympics?

It is an accessible and reproducible autonomous car competition designed with straightforward standardized hardware, software and interfaces.

Get Started

Step 1: Build and test your agent with our available templates and baselines

Step 2: Submit to a challenge

https://challenges.duckietown.com

Check out the leaderboard

View your submission in simulation

Step 3: Run your submission on a robot

https://get.duckietown.com/

in a Robotarium

AI-DO Robotarium Evaluations Underway

Posted on May 16, 2019 | by Liam Paull

Autolab evaluations underway

We have started evaluating the submissions in our Duckietown “Robotarium” (aka Autolab):

Duckiebot onboard camera feed

Robotarium watchtower camera feed

To queue your submissions for robotarium evaluation, please follow these instructions:

You need to use the –challenge option to specify 3 challenges: the two simulated ones (testing and validation) and the hardware one:

dts challenges submit –challenge aido2-LF-sim-validation,aido2-LF-sim-testing,aido2-LF-real-validation
dts challenges submit –challenge aido2-LFV-sim-validation,aido2-LFV-sim-testing,aido2-LFV-real-validation
dts challenges submit –challenge aido2-LFV-sim-validation,aido2-LFVI-sim-testing,aido2-LFVI-real-validation

We will evaluate submissions by participants that are in the top part of the leaderboard in the simulated testing challenge.

The robotarium evaluations are limited, and we will do them in a round robin strategy for each user. We aim to evaluate all in the top 10 of the simulated challenge; and then more if there is the possibility.

Participants can have multiple submissions in the “real” challenges. We will evaluate first according to “user priority” or by most recent. The priority is settable through the web interface by using the top right button.

Deadlines

The challenges will close May 21 at 8pm Montreal (EDT) time. Please check the server timestamp for the precise time in your time zone.

Round 2 of the the AI Driving Olympics is underway!

Posted on April 15, 2019 | by Jacopo Tani

The AI-DO is back!

We are excited to announce that we are now ready to accept submissions for AI-DO 2, which will culminate in a live competition event to be held at ICRA 2019 this May 20-22.

The AI Driving Olympics is a global robotics competition that comprises a series of challenges based on autonomous driving. The AI-DO provides a standardized simulation and robotics platform that people from around the world use to engage in friendly competition, while simultaneously advancing the field of robotics and AI.

Check out our official press release.

We want to see your classical robotic and machine learning based algorithms go head to head on the competition track. Get started today!

Want to learn more or join the competition? Information and get started instructions are here.

If you've already joined the competition we want to hear from you!

Share your pictures on facebook and twitter.

Get involved in the community by:

asking for help

File a github issue
Ask a question
Join the slack community and discuss

offering help

Solve a github issue
Answer questions
Offer support in slack discussions

AI-DO I Interactive Tutorials

Posted on October 30, 2018 | by Liam Paull

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.

AI Driving Olympics Ready for Submissions

Posted on October 14, 2018 | by Liam Paull

Submissions to the AI Driving Olympics are officially open for the Lane Following task evaluated in simulation.

To make a submission, follow the instructions in the AIDO-book.

For example, a good place to start is the Quick Start Guide.

For discussion please check out the AIDO forums.

Las Olimpiadas AI Driving en NIPS 2018

Posted on August 9, 2018 | by Liam Paull

Autores:

Andrea Censi Liam Paull, Jacopo Tani, Julian Zilly, Thomas Ackermann, Oscar Beijbom, Berabi Berkai, Gianmarco Bernasconi, Anne Kirsten Bowser, Simon Bing, Pin-Wei David Chen, Yu-Chen Chen, Maxime Chevalier-Boisvert, Breandan Considine, Andrea Daniele, Justin De Castri, Maurilio Di Cicco, Manfred Diaz, Paul Aurel Diederichs, Florian Golemo, Ruslan Hristov, Lily Hsu, Yi-Wei Daniel Huang, Chen-Hao Peter Hung, Qing-Shan Jia, Julien Kindle, Dzenan Lapandic, Cheng-Lung Lu, Sunil Mallya, Bhairav Mehta, Aurel Neff, Eryk Nice, Yang-Hung Allen Ou, Abdelhakim Qbaich, Josefine Quack, Claudio Ruch, Adam Sigal, Niklas Stolz, Alejandro Unghia, Ben Weber, Sean Wilson, Zi-Xiang Xia, Timothius Victorio Yasin, Nivethan Yogarajah, Yoshua Bengio, Tao Zhang, Hsueh-Cheng Wang, Matthew Walter, Stefano Soatto, Magnus Egerstedt, Emilio Frazzoli,

Publicado en RSS Workshop on New Benchmarks, Metrics, and Competitions for Robotic Learning

Link: Disponible aquí

Die AI-Fahrolympiade auf der NIPS 2018

Posted on August 7, 2018 | by Liam Paull

Autoren:

Veröffentlicht auf dem RSS-Workshop über neue Benchmarks, Metriken und Wettbewerbe für Robotisches Lernen.

Link: Verfügbar hier

The AI Driving Olympics at NIPS 2018

Posted on August 2, 2018 | by Liam Paull

General Information

The AI Driving Olympics at NIPS 2018
Andrea Censi Liam Paull, Jacopo Tani, Julian Zilly, Thomas Ackermann, Oscar Beijbom, Berabi Berkai, Gianmarco Bernasconi, Anne Kirsten Bowser, Simon Bing, Pin-Wei David Chen, Yu-Chen Chen, Maxime Chevalier-Boisvert, Breandan Considine, Andrea Daniele, Justin De Castri, Maurilio Di Cicco, Manfred Diaz, Paul Aurel Diederichs, Florian Golemo, Ruslan Hristov, Lily Hsu, Yi-Wei Daniel Huang, Chen-Hao Peter Hung, Qing-Shan Jia, Julien Kindle, Dzenan Lapandic, Cheng-Lung Lu, Sunil Mallya, Bhairav Mehta, Aurel Neff, Eryk Nice, Yang-Hung Allen Ou, Abdelhakim Qbaich, Josefine Quack, Claudio Ruch, Adam Sigal, Niklas Stolz, Alejandro Unghia, Ben Weber, Sean Wilson, Zi-Xiang Xia, Timothius Victorio Yasin, Nivethan Yogarajah, Yoshua Bengio, Tao Zhang, Hsueh-Cheng Wang, Matthew Walter, Stefano Soatto, Magnus Egerstedt, Emilio Frazzoli
ETH Zurich, Zurich, Switzerland
The Springer Series on Challenges in Machine Learning, https://doi.org/10.1007/978-3-030-29135-8_3

Learn more

Duckietown is a platform for creating and disseminating robotics and AI learning experiences.

It is modular, customizable and state-of-the-art, and designed to teach, learn, and do research. From exploring the fundamentals of computer science and automation to pushing the boundaries of knowledge, Duckietown evolves with the skills of the user.