Multi-UAV Path Planning and Guidance for Cooperative Hunting in a Cluttered Environment

This thesis presents a path planning and guidance algorithm for cooperative hunting by a group of multi-rotor Unmanned Aerial Vehicles (UAVs). A group of intelligent UAVs called pursuers work together to capture a single evader. The target is known to be within a certain region called the target zone. Particle Swarm Optimization is used to generate near-optimal safe paths for the pursuers to get from their base location to the target zone in the presence of static obstacles. Once the pursuers reach the target zone, Proportional Navigation guidance law is used in conjunction with the Potential Field algorithm and Rendezvous Law to simultaneously encircle the target. Previous work done in the cooperative hunting problem does not address the important aspect of rendezvous. Simulations as well as experimental results are shown to demonstrate the feasibility and effectiveness of this work after testing in different scenarios.M.A.S.2019-11-30 00:00:0