PATH PLANNING AND OBSTACLE AVOIDANCE OF UAV FOR CAGE CULTURE INSPECTION

This paper presents path planning and obstacle avoidance of an unmanned aerial vehicle (UAV) for cage culture inspection. The proposed system can automatically inspect cage farming environment that can cut manpower and reduce cost. The problem is similar to travelling salesman problem (TSP). Genetic algorithms are useful techniques for TSP and can also be used for cage culture inspection. In addition to path planning, an improved particle swarm optimization (IPSO) is applied to avoid obstacle between different cages. The IPSO is applicable to both stationary and dynamic environments with one or more obstacles. Simulation results show the effectiveness of the proposed method, comparison of other random search path planning methods is given.