Debdipta Goswami of Ohio State University

Advances in smaller and widely deployable robots, e.g., UAVs, have provided us the ability to perform a variety of complex task without direct involvement of humans. This has enabled us to perform dangerous or arduous tasks such as firefighting, search and rescue, package delivery etc. without putting humans in the harm's way. This talk presents a cooperative mapping and target-search algorithm for detecting a single moving ground target in an urban environment that is initially unknown to a team of autonomous quadrotors equipped with noisy, range-limited sensors. The target moves according to a biased random-walkmodel, and search agents (quadrotors) build a target state graph that encodes past and present target positions. A path is planned for the quadrotors by maximizing mutual information between target-state and environmental uncertainty. The algorithm outperforms the random search and lawnmower algorithm in both mapping and search performance. This algorithm can be extended for multiple ground targets as well as other applications, e.g., mapping forest canopy for fire hazard detection or search-and-rescue operation in a natural disaster.

Biography:

Dr. Debdipta Goswami joined the Department of Mechanical and Aerospace Engineering, the Ohio State University, in 2022 as an assistant professor. He received his Ph.D. degree in Electrical and Computer Engineering from the University of Maryland in 2020 under the supervision of Prof. Derek A. Paley. Between 2020 and 2022, he has worked as a postdoctoral research associate at the Department of Mechanical and Aerospace Engineering in Princeton University where he worked with Prof. Clancy Rowley. His research interests lie at the intersection of control systems and machine learning with a focus on motion planning and agile control of aerial robots.

He has worked on data-driven discovery and control of dynamical systems using operator-theoretic methods and reservoir computers. His current research focuses on the structured learning of control systems from data with guaranteed performance and simultaneous learning and control of dynamical systems. He also works on model predictive control and motion planning for unmanned aerial vehicles.

Email:

Address:ECE Dept, Ohio State University, Columbus, Ohio, United States, 43210