Cooperative Path Planning of Multiple Unmanned Aerial Vehicles Using Cylinder Vector Particle Swarm Optimization With Gene Targeting

Cooperative route planning is crucial to ensure safe and effective flight of unmanned aerial vehicle (UAV) formation. Complicated scenarios, however, put forward new challenges for path planning of multiple UAVs; therefore, a novel cylindrical coordinate particle swarm optimization (PSO) planner with gene targeting (GTCPSO) is presented to obtain feasible and accurate flight routes for multiple UAVs. In the GTCPSO planner, to satisfy UAV dynamic characteristics, the cylindrical coordinate is exploited to represent the flight route; the PSO algorithm with cylindrical coordinates can quickly find a feasible trajectory in a complex environment. Meanwhile, by incorporating gene targeting (GT) operation into improved cylindrical coordinate PSO, the bottleneck waypoint in the global best trajectory is found by waypoint detection, and then the detected bottleneck waypoint is modified by the adjustment operation based on two-phase the updating strategy. A series of experiments based on real map examples on multi-sensors are designed to test the search capability of this GTCPSO planner. The simulation results indicate that the proposed planner GTCPSO has the potential to handle multi-UAV cooperative planning problems under complex constraints.