Tag: AI Driving Olympics

Tag for AI Driving Olympics

Join the AI Driving Olympics, 5th edition, starting now!

Posted on | by Ivano Marocchi

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 to benchmark the state of the art of artificial intelligence in autonomous driving by providing standardized simulation and hardware environments for tasks related to multi-sensory perception and embodied AI.

Duckietown hosts AI-DO competitions biannually, with finals events held at machine learning and robotics conferences such as the International Conference on Robotics and Automation (ICRA) and the Neural Information Processing Systems (NeurIPS). 

 The AI-DO 5 will be in conjunction with NeurIPS 2020 and have two leagues: Urban Driving and Advanced Perception. 

Urban driving league challenges

This year’s Urban League includes a traditional AI-DO challenge (LF) and introduces two new ones (LFP, LFVM).

Lane Following (LF)



Get the LF kit

The most traditional of AI-DO challenges: have a Duckiebot navigate a road loop without intersection, pedestrians (duckies) or other vehicles. The objective is traveling the longest path in a given time while staying in the lane.

Lane following with Pedestrian (LFP)



Get the LFP kit

The LFP challenge is new to AI-DO. It builds upon LF by introducing static obstacles (duckies) on the road. The objectives are the same as for lane following, but do not hit the duckies! 

Lane Following with Vehicles, multi-body (LFVM)



Get the LFVM kit

In this traditional AI-DO challenge, contestants seek to travel the longest path in a city without intersections nor pedestrians, but with other vehicles on the road. Except this year there’s a twist. In this year’s novel multi-body variant, all vehicles on the road are controlled by the submission.

Getting started: the webinars

We offer a short webinar series to guide contestants through the steps for participating: from running our baselines in simulation as well as deploying them on hardware. All webinars are 9 am EST and free!

Introduction

Learn about the Duckietown project and the Artificial Intelligence Driving Olympics.




  • Nov. 9, 2020

ROS baseline

How to run and build upon the “traditional” Robotic Operation System (ROS) baseline.




  • Nov. 11, 2020

Local development

On the workflow for developing and deploying to Duckiebots, for hardware-based testing.




  • Nov. 13, 2020

RL baseline

Learn how to use the Pytorch template for reinforcement learning approaches.




  • Nov. 16, 2020

IL baseline

Introduction to the Tensorflow template, use of logs and simulator for imitation learning.




  • Nov. 18, 2020






Synch Webinar Calendar

Advanced sensing league challenges

Previous AI-DO editions featured: detection, tracking and prediction challenges around the nuScenes dataset.

For the 5th iteration of AI-DO we have a brand new lidar segmentation challenge.

The challenge is based on the recently released lidar segmentation annotations for nuScenes and features an astonishing 1,400,000,000 lidar points annotated with one of 32 labels.

We hope that this new benchmark will help to push the boundaries in lidar segmentation. Please see https://www.nuscenes.org/lidar-segmentation for more details.

Furthermore, due to popular demand, we will organize the 3rd iteration of the nuScenes 3d detection challenge. Please see https://www.nuscenes.org/object-detection for more details.

AI-DO 5 Finals event

The AI-DO finals will be streamed LIVE during 2020 edition of the Neural Information Processing Systems (NeurIPS 2020) conference in December.

Learn more about the AI-DO here.



Participate in AI-DO 5 now



Get your AI-DO hardware kit



Join our Slack Community

Thank you to our generous sponsors!

The Duckietown Foundation is grateful to its sponsors for supporting this fifth edition of the AI Driving Olympics!



AI-DO 3 – Urban Event Winners

Posted on | by Kirsten Bowser

In case you missed it AI-DO 3 has come and gone. Interested in reliving the competition? Here’s the video.

We had a great time at NeurIPS hosting the Third Edition of the AI Driving Olympics. As usual the sound of Duckies attracted an engaging and supportive crowd.

 

Racing Event

The competition began with the Racing Event, hosted by AWS DeepRacer. They ran their top 10 submissions and selected the winner by who could complete the fastest lap.

Racing Event Winner 
Ayrat Baykov at 8:08 seconds

 

Advanced Perception Event

The winners of the Advanced Perception Event hosted by APTIV and the nuScenes dataset were announced. Luckily a member of the winning team was present to accept the award.

Rank 3
CenterTrack – Open and Vision

Rank 2
VV_Team

Rank 1
StanfordlPRL-TRI

 

Urban Event

The competition culminated with Duckietown’s own Urban Driving Event, where we ran the top submissions for each of the three challenges on our competition tracks.

Winners

 

Lane Following 

JBRRussia1: Konstantin Chaika, Nikita Sazanovich, Kirill Krinkin, Max Kuzmin

Lane Following with Vehicles

phmarm

Lane Following with Vehicles and Intersections

frank_qcd_qk

 

Final Scoreboard

A few pictures from the event

Congratulations to all the winners and thanks for participating in the competition. We look forward to seeing you for AI-DO 4!

Round 3 of the the AI Driving Olympics is underway!

Posted on | 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. 

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

Posted on | by Kirsten Bowser

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. 

Results from the AI-DO2 Finals event on May 22, 2019 at ICRA

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

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.org

Check out the leaderboard

View your submission in simulation

Step 3: Run your submission on a robot

https://get.duckietown.org/

in a Robotarium

AI-DO Robotarium Evaluations Underway

Posted on | by Liam Paull

We have started evaluating the submissions in our “robotarium”:

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.

Update to Dynamics Model in Duckietown Simulator

Posted on | by Liam Paull

We have implemented an improved dynamics model in the simulator. If you are using the simulator to:

  • Train your agent with reinforcement learning
  • Generate data for imitation learning
  • Test and debug your submission

then you may want to retrain/retest with the new dynamics model. This model is much closer to the true Duckiebot and should permit much easier transfer from simulation to the real robot hardware.

AI-DO 2 Validation and Testing Registration

Posted on | by Kirsten Bowser

We are in the final countdown to AI-DO 2 at ICRA!

Now is the time to let us know if you will be using the validation and testing facilities at the Duckietown competition ground. Please register below!

AI-DO technical updates

Posted on | by Andrea Censi
Here are some technical updates regarding the competition. Thanks for all the bug reports via Github and Slack!

Changes to platform model in simulations

We have changed the purely kinematic model in the simulations with one that is more similar to the real robots obtained by system identification. You can find the model here. Properties:
  • The inputs to the model are the two PWM signals to the wheels, left and right. (not [speed, omega] like last year)
  • The maximum velocity is ~2 m/s. The rise time is about 1 second.
  • There is a simulated delay of 100 ms.
We will slightly perturb the parameters of the model in the future to account for robot-robot variations, but this is not implemented yet. All the submissions have been re-evaluated. You can see the difference between the two models
purely kinematic platform model more realistic platform model
  The new model is much more smooth. Overall we expect that the new model makes the competition easier both in simulation, and obviously, in the transfer.

Infrastructure changes

  • We have update the Duckietown Shell and commands several times to fix a few reported bugs.
  • We have started with provisioning AWS cloud evaluators. There are still sporadic problems. You should know that if your job fails with the host-error code, the system thinks it is a problem of the evaluator and it will try on another evaluator.

Open issues

  • Some timeouts are a bit tight. Currently we allow 20 minutes like for NeurIPS, but this year we have much more realistic simulation and better visualization code that  take more time. If your submission fails after 20 minutes of evaluation, this is the reason.
  • We are still working on the glue code for running the submissions on the real robots. Should be a couple of days away.
  • Some of the changes to the models/protocol above are not in the docs yet.

Round 2 of the the AI Driving Olympics is underway!

Posted on | by Kirsten Bowser

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.

The finals of AI-DO 1 at NeurIPS, December 2018

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

offering help