Smart Mobility Connection - Rahul Mangharam 2.5.21
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. 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. 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 alumni.
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. 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. 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 alumni.