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F1TENTH: 1/10th the scale. 10X the Fun! Autonomous Racing Community, Course and Competitions

Seminar by Rahul Mangharam (UPenn)

  • Date 09 Apr 2021
  • Time 3.00pm-4.00pm
  • Category Seminar

F1TENTH: 1/10th the scale. 10X the Fun! Autonomous Racing Community, Course and Competitions

Abstract: F1TENTH is a complete, ready-to-race autonomous race car that is 1/10th-scale and 1/100th the cost of a real self-driving car. In this talk we will demonstrate how F1TENTH is an easy-to-use high-performance platform for machine learning engineering for perception, planning, control and coordination for future safe and connected autonomous systems. F1TENTH has a growing community of over 60 universities, 7 international autonomous racing competitions and hands-on course offerings in over a dozen institutions. We'll detail the platform’s hardware, autonomous vehicle software stack, simulators, and systems infrastructure. We highlight three specific capabilities for streamlined algorithm development, testing and validation: a set of simulators, control and verification, and efficient machine-learning algorithm development. Members of the F1TENTH community have published new research at ICML, ICRA, NeurIPS, and HSCC to demonstrate autonomous driving at the limits of performance and to accelerate the development of safe autonomous vehicles. Together with Autoware and the US Department of Transportation CARMA 1Tenth community, we would like to invite you to join the community for experimentation, standardization and certification of Cooperative Driving Autonomy. Check out https://f1tenth.org to get started!

Bio: Rahul designs safe autonomous systems and works at the intersection of formal methods, control systems and machine learning. He is the Penn Director for the US DoT $14MM Mobility21 National University Transportation Center on technologies for safe and efficient movement of people and goods. He is the thrust leader for Data-driven Agriculture in the $26MM NSF IoT4Ag Center. Rahul leads the F1Tenth Autonomous Racing Community [https://f1tenth.org] to develop machine learning for perception, planning and control of autonomous systems. Rahul received the 2016 US Presidential Early Career Award (PECASE) from President Obama for work on Life-Critical Systems. He received the DoE’s CleanTech Prize (Regional, 2016), IEEE Benjamin Franklin Key Award (2014), NSF CAREER Award (2013), and Intel Early Faculty Career Award (2012). He is a Carnegie Mellon University alum.

Website: https://www.seas.upenn.edu/~rahulm/

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