Development and Implementation of Optimal Strategies for Constraint Motion Planning of Autonomous Vehicles 

Abstract: The deployment of autonomous aerial vehicles requires efficient planning and tracking of trajectories that can satisfy constraints pertaining to the operating environment and the vehicle’s kinematics, while minimizing a suitable performance index. Catering to it, we will present optimal planning and tracking of trajectories with a primary focus on problems like collision avoidance, surveillance, and autonomous delivery of packages. The talk will begin with the characterization and computation of an exact time-optimal trajectory between two oriented points via a moving circle for a Dubins vehicle model. The choice of Dubins model is owing to the fact that it is a simple yet sufficiently realistic model to depict a simplified kinematics of fixed-wing aerial vehicles. Thereafter, catering to vehicles with rotating turret, we present optimal strategies for joint motion planning of pursuer-turret systems. Such vehicle models are useful in applications such mobile air-defense systems, surveillance aircraft, and vehicles with directed sensors. Finally, for tracking a planned trajectory, the application of game-theoretic approaches for precise and robust tracking of aggressive trajectories by multirotor model will be presented. The applicability of the approach for the Dubins model will also be shown.

Bio: Bhargav Jha received his B.E. (Hons) degree in Electronics and Instrumentation Engineering from Birla Institute of Technology & Science Pilani, India in 2016. He obtained a master’s degree and a Ph.D. degree in Aerospace Engineering, Technion – Israel Institute of Technology in 2019 and 2022, respectively. He is currently a postdoctoral researcher at Electrical and Computer Engineering (ECE), Michigan State University. After his postdoctoral tenure at MSU, he will be joining as an Assistant Professor at the Department of Electrical Engineering, Indian Institute of Technology (IIT), Kharagpur, India. His current research interests lies in developing practically implementable motion control strategies using tools from guidance, optimal control theory, and game theory.