Opportunities and Challenges with Autonomous Racing


2021 ICRA Full-Day Workshop

31 May, 2021

[This workshop will be held online]

[Registration is Free]

Announcement:

The Online Meeting link for the workshop will be posted here and a notification will also go out to those who fill in the registration form below.

Register Here [Free]

Thank you to all our participants and speakers for making this workshop a huge success!

Congratulations to our joint best paper award winners

  • Chanyoung Jung, Seungwook Lee, Hyunki Seong, Andrea Finazzi and David Hyunchul Shim, Game-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing
  • Rongyao Wang, Yiqiang Han and Umesh Vaidya, Deep Koopman Data-driven Control Framework forAutonomous Racing

About this workshop

In motorsport racing, there is a saying that “If everything seems under control, then you are not going fast enough”. Expert racing drivers have split second reaction times and routinely drive at the limits of control, traction, and agility of the racecar - under high-speed and close proximity situations. Autonomous racing presents unique opportunities and challenges in designing algorithms and hardware that can operate firmly on the limits of perception, planning, and control. Racing has a long and illustrative history of serving as a proving grounds for automotive technology. Similarly, autonomous racing has the potential to serve as the litmus test - but this time - for self-driving software. While a large portion of autonomous vehicle research and development is focused on handling routine driving situations, achieving the safety benefits of autonomous vehicles also requires a focus on driving at the limits of the control of the vehicle.

The main objective of this workshop is to attract the interest of the robotics community on research challenges specific to high-speed autonomous racing. We aim at bringing together experts and researchers from various robotic fields explore the challenges associated with modeling vehicle dynamics at high-speeds, head-to-head multi-agent racing, AI-enabled racing solutions, sensor fusion, overtaking, state-estimation of opponents, racing simulation at scale, perception, localization, and planning. Autonomous racing competitions such as F1/10 Autonomous Racing, Roborace, and Indy Autonomous Challenge are encouraging researchers to think about these problems. We expect that this workshop will become the focal point for bringing together researchers from the growing autonomous racing and robotics communities to foster collaborative and creative solutions.

Video Recordings

Opening Remarks

[Invited Session 1] Alex Liniger - Pushing the Limits of Friction: A Story of Model Mismatch

[Invited Session 1] Markus Lienkamp (TUM) - Indy Autonomous Challenge Key Opportunities and Challenges

[Invited Session 1] Panagiotis Tsiotras (Georgia Tech) - Fast and Furious: Modeling and Control Design for Competitive Car Racing

Invited Session 1: QnA and Discussion

Contributed Papers 1-6

[Invited Session 2] Davide Scaramuzza (U of Zurich): Autonomous Drone Racing

[Invited Session 2] Todd Murphey (Northwestern): Real-Time Learning After Safety Violations

[Invited Session 2] Chris Gerdes (Stanford): Lessons for Autonomous Racing from Professional Drivers and Neural Networks

Invited Session 2: QnA and Discussion

Contributed Papers 7-13

[Invited Session 3] Sertac Karaman (MIT) - On Fast and Agile Autonomous Super-Vehicles

[Invited Session 3] Ugo Rosolia (Caltech) - Learning to race using a predictive control

Invited Session 3 - QnA and Discussion

Invited Speakers

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Todd Murphey

Northwestern University

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Davide Scaramuzza

University of Zurich

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Chris Gerdes

Stanford

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Sertac Karaman

MIT

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Panagiotis Tsiotras

Georgia Tech

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Markus Lienkamp

TU Munich

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Ugo Rosolia

Caltech

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Alex Liniger

ETH Zurich

Workshop schedule



All times in EDT (UTC - 04)
9:00a Welcome Remarks
9:10a Invited Session 1
9:10-9:30a Alex Liniger (ETH) - Pushing the Limits of Friction: A Story of Model Mismatch
9:30-9:50a Markus Lienkamp (TUM) - Indy Autonomous Challenge Key Opportunities and Challenges
9:50-10:10a Panagiotis Tsiotras (Georgia Tech) - Fast and Furious: Modeling and Control Design for Competitive Car Racing
10:10-10:30a Q/A and Discussion for Invited Session 1
10:30-11:30a Contributed Papers 1-6
11:30-11:50a Q/A for Papers 1-6
11:50a Invited Session 2
11:50-12:10p Davide Scaramuzza (U of Zurich) Autonomous Drone Racing
12:10-12:30p Todd Murphey (Northwestern) - Real-Time Learning After Safety Violations
12:30-12:50p Chris Gerdes (Stanford): Lessons for Autonomous Racing from Professional Drivers and Neural Networks
12:50-1:10p Q/A and Discussion for Invited Session 2
1:10-2:20p Contributed Papers 7-13
2:20-2:40p Q/A for Papers 7-13
2:40-3:00p Panel Discussion - Autonomous Racing Competitions
3:00p Invited Session 3
3:00-3:20p Sertac Karaman (MIT) - On Fast and Agile Autonomous Super-Vehicles: New Problems, Tools and Algorithms
3:20-3:40p Ugo Rosolia (Caltech) - Learning how to race using a predictive control approach: towards multi-agents racing
3:40-3:50 Q/A for Invited Session 3
3:50-4:15p Workshop concluding remarks

Contributed Papers

[Paper #1] Chanyoung Jung, Seungwook Lee, Hyunki Seong, Andrea Finazzi and David Hyunchul Shim, Game-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing [Link to Paper]
[Paper #2] Nan Li, Eric Goubault, Laurent Pautet and Sylvie Putot, Autonomous racecar control in head-to-head competition using Mixed-Integer Quadratic Programming [Link to Paper]
[Paper #3] Antonio Loquercio, Elia Kaufmann, Yunlong Song and Davide Scaramuzza, High-Speed Drone Flight with On-Board Sensing and Computing [Link to Paper]
[Paper #4] Markus Schratter, Jasmina Zubaca, Konstantin Mautner-Lassnig, Tobias Renzler, Martin Kirchengast, Stefan Loigge, Michael Stolz and Daniel Watzenig, Lidar-based Mapping and Localization for Autonomous Racing [Link to Paper]
[Paper #5] Trent Weiss, John Chrosniak and Madhur Behl, Towards Multi-Agent Autonomous Racing with the DeepRacing framework [Link to Paper]
[Paper #6] Matthias Schmid, Qilun Zhu, Ashley Boncimino, Robert Prucka and Chris Paredis, Control Informed Design of the IAC Autonomous Racecar for Operation at the Dynamic Envelope [Link to Paper]
[Paper #7] Xuesu Xiao, Joydeep Biswas and Peter Stone, Learning Inverse Kinodynamics for Accurate High-Speed Off-Road Navigation on Unstructured Terrain [Link to Paper]
[Paper #8] Dvij Kalaria, Parv Maheshwari, Animesh Jha, Arnesh Issar, Debashish Chakravarty, Sohel Anwar and Andres Tovar, Local NMPC on Global Optimised Path for Autonomous Racing
[Paper #9] Jayanth Bhargav, Johannes Betz, Hongrui Zheng and Rahul Mangharam, Track based Offline Policy Learning for Overtaking Maneuvers with Autonomous Racecars [Link to Paper]
[Paper #10] Shakti Wadekar, Benjamin Schwartz, Aly Gamal, Shyam Kannan, Manuel Mar, Rohan Manna, Vishnu Chellapandi and Daniel Gonzalez, Towards End-to-End Deep Learning for Autonomous Racing: On Data Collection and a Unified Architecture for Steering and Throttle Prediction [Link to Paper]
[Paper #11] Tim Brüdigam, Alexandre Capone, Sandra Hirche, Dirk Wollherr and Marion Leibold, Gaussian Process-based Stochastic Model Predictive Control for Overtaking in Autonomous Racing [Link to Paper]
[Paper #12] Rongyao Wang, Yiqiang Han and Umesh Vaidya, Deep Koopman Data-driven Control Framework forAutonomous Racing [Link to Paper]
[Paper #13] Minghao Jiang, Kristina Miller, Dawei Sun, Zexiang Liu, Yixuan Jia, Arnab Datta, Necmiye Ozay and Sayan Mitra, Continuous Integration and testing for Autonomous Racing Software: An Experience Report from GRAIC [Link to Paper]

Organizers

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Madhur Behl

Assistant Professor

Department of Computer Science
University of Virginia

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Johannes Betz

Postdoctoral Researcher

Department of Electrical and Systems Engineering
University of Pennsylvania

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Venkat Krovi

Michelin Chair Professor

Department of Automotive Engineering
Clemson University

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Rahul Mangharam

Associate Professor

Department of Electrical and Systems Engineering
University of Pennsylvania


Program Committee


  • Thomas Herrmann, TU Munich
  • Shreyas Kousik, Stanford
  • Dipankar Maity, University of North Carolina
  • David Fridovich-Keil, Stanford
  • Jack Silberman, UC San Diego
  • David Bevly, Auburn University
  • Kiril Solovey, Stanford
  • Leonhard Hermansdorfer, TU Munich
  • Markus Schratter, Virtual Vehicle Research GmbH
  • Yvonne Stuerz, UC Berkeley
  • Ilya Shimchik, SIT Autonomous

Call for Contributions

Demonstrating high-speed autonomous racing can be considered as a grand challenge for self-driving cars, and making progress here has the potential to enable breakthroughs in agile and safe autonomy. To succeed at racing, an autonomous vehicle is required to perform both precise steering and throttle maneuvers in a physically-complex, uncertain environment, and by executing a series of high-frequency decisions. This makes racing an interesting opportunity to explore the physical and algorithmic limits of autonomous driving. Autonomous racing competitions, such as Autonomous Formula SAE, F1/10 autonomous racing, Roborace, and Indy Autonomous Challenge are, both figuratively and literally, getting a lot of traction and becoming proving grounds for testing perception, planning, and control algorithms at high speeds.


We are proposing this workshop to raise awareness of the overall autonomous racing area to the IEEE Robotics and Automation Society community that can take inspiration from the problem space in their own research. This is a good time for such a workshop around this unique and important application space, that will require innovations across core topics in robotics and we believe it will gather a lot of interest.



Topics of Interest

  • Modeling vehicle dynamics at high-speeds
  • Head-to-head multi-agent racing
  • AI-enabled racing solutions
  • Overtaking strategies
  • State-estimation of opponents
  • Racing simulation at scale
  • Limits of perception, localization, and planning at high-speeds.
  • Adversarial vs Cooperative
  • Balancing safe vs aggressive driving policies
  • Hardware-software co-design for autonomous racing
  • Hardware AI accelerators for perception
  • Software stack and architectures for racing

Paper Submission:

We invite short papers (4-6 pages, including references) for submission to the workshop related to the topics above and the theme of autonomous racing. Position papers, work in progress and novel but not necessarily thoroughly worked out ideas are encouraged. The submissions will be reviewed by the workshop’s program committee and we will accept papers for oral (live) presentations, or a video highlight. A best paper award will be presented in both categories. We are currently exploring the possibility of a journal special issue in the Journal of Field Robotics for the best contributions at the workshop. Each paper will undergo a thorough review process and receive two high quality reviews. Accepted paper will be made available on the website.


The paper should be in PDF format and use the standard IEEE ICRA template.


Please use the following EasyChair link for paper submissions: Submission Link

Important Dates

Sponsors

This workshop is supported by the IEEE RAS TC on Autonomous Ground Vehicles and Intelligent Transportation.

AD Link technologies

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Autoware Foundation

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