Heterogeneous UAV Swarm Collaborative Search Mission Path Optimization Scheme for Dynamic Targets

Abstract

To solve the problem of collaborative search mission planning (CSMP) for a heterogeneous unmanned aerial vehicle (UAV) swarm for dynamic targets, this paper proposes a new CSMP scheme for a heterogeneous UAV swarm. First, a new polar coordinate system motion method is used to establish the UAV motion model and decision input solution model, which effectively solves the path-unified coding problem of a heterogeneous UAV swarm. Then, in the mission area, a dynamically updated multisearch situation map model is established. Finally, to improve the global searching capability of a UAV, an improved path optimization algorithm PSO-Rolling Horizon Control (PSO-RHC) is designed. Multiple Monte Carlo simulations are performed for three time-sensitive moving target types and three constraint types. The simulation results show that the task execution efficiency indexes of the proposed scheme for the decision input solution model, pheromone update mechanism, and optimization algorithm are improved by 188%, 72%, and 102%, respectively, and the overall performance is improved by 227%.