Robotics and autonomous systems enable us to interact more richly and extensively with the world we live in. Robots provide in-situ monitoring of the environments they are immersed in and can adapt their strategies to respond to various external stimuli. As such, robots of all shapes and sizes have given us unprecedented access to landscapes and habitats both big and small. In this talk, I will highlight our efforts in developing robotic systems and strategies for monitoring and tracking complex spatiotemporal phenomena. I will focus on our recent efforts in data-driven system identification, reduced-order modeling, and adaptive sampling strategies for distributed robotic systems. While most of our work is targeted towards applications in ocean sciences, I will discuss how the ideas can be extended to more general dynamical systems.
Bio: M. Ani Hsieh is a Research Associate Professor in the C. Her research interests lie at the intersection of robotics, multi-agent systems, and dynamical systems theory. Hsieh and the members of the ScalAR Lab design algorithms for estimation, control, and planning for multi-agent robotic systems with applications in environmental monitoring, estimation and prediction of complex dynamics, and design of collective behaviors. She is a member of the GRASP (General Robotics, Automation, Sensing, and Perception) Lab at the University of Pennsylvania.
She received her B.S. in Engineering and B.A. in Economics from Swarthmore College and her PhD in Mechanical Engineering from the University of Pennsylvania. Prior to Penn, she was an Associate Professor in the Department of Mechanical Engineering and Mechanics at Drexel University. Hsieh is the recipient of a 2012 Office of Naval Research (ONR) Young Investigator Award and a 2013 National Science Foundation (NSF) CAREER Award.