Event
Microsoft Future Leaders in Robotics and AI Seminar Series: Elena Shrestha
Friday, April 5, 2024
2:00 p.m.
Online Seminar
Sense, Imagine, Act: Multimodal Perception & Reinforcement Learning for UxV Guidance & Control
Elena Shrestha
Postdoctoral Fellow
University of Michigan
Abstract
While reinforcement learning offers potential for continual learning and adaptability in complex scenarios, its application to real-world robotics faces significant challenges. Unlike in simulations, physical platforms struggle to collect a diverse corpus of training data due to critical safety risks and the inherent constraints of operating within a dynamic and partially observable environment. My work draws inspiration from the human capability to fuse and exploit multiple sensing modalities, construct comprehensive models of how the world operates, and then leverage those models to adeptly navigate in challenging and often unpredictable environments. In this seminar, I will present an overview of how unmanned vehicles (ground, air, and surface) can exploit a world model constructed through multimodal perception, to learn near-optimal policies for guidance and control. A key aspect of the approach is learning from imagination in which the world model is used to simulate future imagined trajectories, enabling it to anticipate potential risks before encountering them in the real world. My ongoing work and long-term vision is to evolve the traditional sense-plan-act framework into a more intuitive and cognitively inspired sense-imagine-act model.
Bio
Elena Shrestha is a Postdoctoral Research Fellow at the University of Michigan (U-M) mentored by Prof. Ram Vasudevan and Prof. Katie Skinner. Her primary research focus is on developing model-based reinforcement learning algorithms that enable autonomous agents to generalize and safely adapt to unseen real-world environments. Prior to joining U-M, she was a Section Supervisor of the Unmanned Systems Concepts Section at the Johns Hopkins University Applied Physics Lab. She received her Ph.D. in Aerospace Engineering from the University of Maryland (2018) advised by Prof. Inderjit Chopra. She is a recipient of the Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, ORAU Postdoctoral Fellowship, NSF Graduate Research Fellowship, Amelia Earhart Fellowship, and has also been recognized as an Aviation Week & Space Technology’s Tomorrow’s Engineering Leader. Her Ph.D. work on a cyclocopter UAV was selected for Best Paper in Advanced Vertical Flight at the VFS Annual Forum (2014) and has been featured on IEEE Spectrum and Vertiflite.
