Control Meets Learning Seminar

Wednesday February 3, 2021 9:00 AM

Safe, Interaction-Aware Decision Making and Control for Robot Autonomy

Speaker: Marco Pavone, Department of Aeronautics and Astronautics, Stanford University
Location: Online Event

In this talk I will present a decision-making and control stack for human-robot interactions by using autonomous driving as a motivating example. Specifically, I will first discuss a data-driven approach for learning multimodal interaction dynamics between robot-driven and human-driven vehicles based on recent advances in deep generative modeling. Then, I will discuss how to incorporate such a learned interaction model into a real-time, interaction-aware decision-making framework. The framework is designed to be minimally interventional; in particular, by leveraging backward reachability analysis, it ensures safety even when other cars defy the robot's expectations without unduly sacrificing performance. I will present recent results from experiments on a full-scale steer-by-wire platform, validating the framework and providing practical insights. I will conclude the talk by providing an overview of related efforts from my group on infusing safety assurances in robot autonomy stacks equipped with learning-based components, with an emphasis on adding structure within robot learning via control-theoretical and formal methods.

Contact: Jolene Brink jbrink@caltech.edu
For more information visit: https://sites.google.com/view/control-meets-learning