AI Agents in the Physical World: Balancing Safety & Performance
Speaker
Rahul Mangharam
Professor in Electrical & Systems Engineering and Computer & Information Science at the University of Pennsylvania.
Title
"AI Agents in the Physical World: Balancing Safety & Performance"
Abstract
Balancing safety and performance is crucial to deploying autonomous agents in physical 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 explore the following research themes on learning-based perception, planning and control at the limits of performance:
(1) How to generate the most competitive agents who dynamically balance safety and assertiveness by using distributionally robust online adaptation and Game-theoretic planning
(2) How to be better-than-the-best using imitation learning with multiple imperfect experts
(3) Using invertible neural networks to solve inverse problems in localization and SLAM
(4) How to build the most efficient agents with multi-domain optimization across mechanical, decision and control designs;
We realize all our research in the https://f1tenth.org autonomous racecar platform that is 10th the size, but 10x the fun! In the Autoware Center of Excellence for Autonomous Driving we develop several EV and AV reference platforms
About Speaker
Rahul Mangaram is Professor in Electrical & Systems Engineering and Computer & Information Science at the University of Pennsylvania. Rahul builds autonomous systems at the intersection of formal methods, machine learning and controls. He applies his work to safety-critical autonomous vehicles, urban air mobility, life-critical medical devices, and AI Co- designers for complex systems. He is the Penn Director for DoT's $20MM Safety21 National University Transportation Center which focuses on technologies for safe and efficient movement of people and goods. Rahul is the Director of the Autoware Center of Excellence for Autonomous Driving, a consortium of 70+ companies and universities focused on open-source AV software for open-standards EV platforms.
Rahul received the 2016 US Presidential Early Career Award (PECASE) from President Obama for his work on Life-Critical Systems. He also received the 2016 Department of Energy’s CleanTech Prize (Regional), the 2014 IEEE Benjamin Franklin Key Award, 2013 NSF CAREER Award, 2012 Intel Early Faculty Career Award and was selected by the National Academy of Engineering for the 2012 and 2017 US Frontiers of Engineering. He has won several ACM and IEEE best paper awards in Cyber-Physical Systems, controls, machine learning, and education.