Abstract
To improve the performance of multi-unmanned aerial vehicle path planning in plateau narrow area, a control strategy based on Cauchy mutant pigeon-inspired optimization algorithm is proposed in this article. The Cauchy mutation operator is chosen to improve the pigeon-inspired optimization algorithm by comparing and analyzing the changing trend of fitness function of the local optimum position and the global optimum position when dealing with unmanned aerial vehicle path planning problems. The plateau topography model and plateau wind field model are established. Furthermore, a variety of control constrains of unmanned aerial vehicles are summarized and modeled. By combining with relative positions and total flight duration, a cooperative path planning strategy for unmanned aerial vehicle group is put forward. Finally, the simulation results show that the proposed Cauchy mutant pigeon-inspired optimization method gives better robustness and cooperative path planning strategy which are effective and advanced as compared with traditional pigeon-inspired optimization algorithm.
Highlights
Path planning is the first step in a moving multi-agent mission system
Path management is necessary for most of the intelligent agents, for example, unmanned aerial vehicles (UAVs), which are unable to move along zigzags paths which are generated by connecting the waypoints
The cone represents the peak, the sphere areas near the peak represent the wind field, the solid line represents the optimal path planned by CM-pigeoninspired optimization (PIO) algorithm and the dash line represents the optimal path planned by particle swarm optimization (PSO) algorithm
Summary
Path planning is the first step in a moving multi-agent mission system. To distinguish from path management, path planning aims to find a set of waypoints from a start position to a target position to instruct agents moving.[1]. Multi-UAV co-operative path planning problem in plateau narrow area is defined. 2. For the reason that conventional PIO algorithm falls into a local optimal area when solving multi-UAV co-operative path planning problem in plateau narrow area, during PIO iteration process, Cauchy mutation operator is added into map and compass operator.
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