Category: competition

EdTech awards 2021: Duckietown finalist in 3 categories!

Posted on | by Ivano Marocchi

Duckietown reaches the finals in the EdTech Awards 2021

The EdTech awards are the largest and most competitive recognition program in all of education technology.

The competition, led by the EdTech digest, recognizes the biggest names in edtech – and those who soon will be, by identifying all over the world the products, services and people that bet promote education through the use of technology, for the benefit of learners.

The 2021 edition has brought a big surprise to Duckietown, as it was nominated as a finalist in 3 different categories:

  • Cool Tool Award: as robotics (for learning, education) solution;
  • Cool Tool Award: as higher education solution;
  • Trendsetter Award: as a product or service setting a trend in education technologies.

Although a final is just a starting point, we are proud of the hard work done by the team in this particularly difficult year of pandemic and lockdowns, and grateful to you all for the incredible support, constructive feedback and contributions!

To the future, and beyond!

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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!