Metaheuristic Optimization-Based Path Planning and Tracking of Quadcopter for Payload Hold-Release Mission

Under harsh geographical conditions where manned flight is not possible, the ability of unmanned aerial vehicle (UAV) to successfully carry out payload hold–release mission by avoiding obstacles depends on optimal path planning and tracking performance UAV. The UAV plan track with minimum energy time consumption possible using parameters. This study performs optimum Harris hawk optimization (HHO)–grey wolf (GWO), a hybrid metaheuristic algorithm, enable actualize obstacles. In study, HHO–GWO which stands its avoidance local minima speed convergence, used obtain feasible effective path. addition, effect mass change uncertainty determined. effectiveness proposed approach tested comparing it swarm algorithms such as particle (PSO) GWO. experimental results obtained indicate that algorithm generates fast safe without becoming stuck minima, quadcopter tracks generated consumption.