Upcoming Event:

Epigraph Convexification for Nonlinear Robust Optimal Control

Abraham P. Vinod, Mitsubishi Electric Research Laboratories (MERL)

Abstract

I will present a tractable set-based method for a broad class of robust control problems with nonlinear dynamics and bounded uncertainty. The key insight is that an epigraph-based relaxation of the dynamic programming (DP) recursion is tight for the considered class and yields near-globally optimal controllers in practice. Leveraging recent advances in set-based robust control, the approach also avoids the curse of dimensionality of the classical grid-based DP. Specifically, it converts the multi-stage, nonconvex problem into a state-discretization-free sequence of convex one-step optimizations. Applications include robust powered-descent guidance for lunar landers and robust motion planning for energy-constrained drones. If time permits, I will also talk about our recent work in using multi-arm bandits for environmental monitoring using heterogeneous robots.

Biography

Abraham P. Vinod is a Principal Research Scientist at Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA. His main research interests are in the areas of constrained control under uncertainty, multi-agent systems, and learning. Prior to joining MERL in 2020, he held a postdoctoral position at the  Oden Institute for Computational Engineering and Sciences (UT Austin). He received his B.Tech. and M.Tech. degrees from the Indian Institute of Technology-Madras (IIT-M), India, and his Ph.D. degree from the University of New Mexico, USA, all in electrical engineering. He was the recipient of the Best Student Paper Award at the 2017 ACM Hybrid Systems: Computation and Control Conference, Finalist for the Best Paper Award in the 2018 ACM Hybrid Systems: Computation and Control Conference, and the best undergraduate student research project award at IIT-M. He is the primary developer of pycvxset, a set computation toolbox in python, and co-developed SReachTools, a stochastic reachability toolbox in MATLAB.