Seminar "Safe, Interaction-Aware Decision Making and Control for Robot Autonomy", Prof. Marco Pavone
On Thursday, October 14th, 2021 at 5 p.m., Prof. Marco Pavone (Stanford University, Director of Autonomous Vehicle Research at NVIDIA) will give an invited talk on "Safe, Interaction-Aware Decision Making and Control for Robot Autonomy". The event is organized as part of a cycle of seminars in the "AI for Automotive" and "Learning Algorithms for Smart Intelligent Systems" courses (Prof. Cucchiara, Baraldi) and will be streamed online.
Abstract
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, interactionaware decision-making framework. The framework is designed to be minimally interventional; in particular, by leveraging backward reachability analysis, it ensures safety even when other vehicles 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 in adding structure within robot learning via control-theoretical and formal methods.
Short bio
Dr. Marco Pavone is an Associate Professor of Aeronautics and Astronautics at Stanford University, where he is the Director of the Autonomous Systems Laboratory and Co-Director of the Center for Automotive Research at Stanford. He is currently on a partial leave of absence at NVIDIA serving as Director of Autonomous Vehicle Research. His main research interests are in the development of methodologies for the analysis, design, and control of autonomous systems, with an emphasis on self-driving cars, autonomous aerospace vehicles, and future mobility systems.