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Fall 2021 GRASP Seminar: Rahul Mangharam, University of Pennsylvania, “What can we learn from Autonomous Racing?”
October 1 @ 10:30 am - 11:45 am
*This was a HYBRID Event with in-person attendance in Wu & Chen Auditorium and Virtual attendance…
Balancing performance and safety are crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but conservative policies, highlighting the need for robust, adaptive strategies. Current approaches either make simplifying assumptions about other agents or lack robust mechanisms for online adaptation. In this talk, we will explore research themes on perception, planning and control at the limits of performance. We explore (1) How to build the most efficient autonomous racecar with Multi-domain optimization across vehicle design, planning and control; (2) How to generate the most competitive agents who dynamically balance safety and assertiveness by using distributionally robust online adaptation; (3) How to stress test the overtaking logic and path planning algorithms in interactive adversarial agents; (4) How to combine previous system designs to auto-complete new designs with new requirements, and (5) Understand the value of Cooperation in Multi-Agent Games. We realize all our research in the https://f1tenth.org autonomous racecar platform that is 10th the size, but 10x the fun! The main takeaway from this talk is how you can get involved in very exciting research on safe autonomous systems. This is a team presentation by Rahul Mangharam, Johannes Betz and Billy Zheng.