Path Planning and Control of a Drone Fleet

Abstract

In recent years, air pollution has damaged our environment and caused a serious threat to human and animal life. Therefore, it is necessary to locate and identify the sources of pollution. This thesis describes the planning and control of a fl of drones whose purpose is to gather at the location with the highest pollution concentration. A decentralized structure is employed to control the drone fl controllers are used to control each drone independently. Quadrotor’s trajectory planning is performed by the metaheuristic algorithm, which is particle swarm optimization by maximizing the air pollution dispersion function and avoiding collisions among the fl members.