Combat Mission Planning for Consumable Unmanned Aerial Vehicles in Complex Threat Environment
Gaofeng Wu, Chuchao He · 2022 International Conference on Cyber-Physical Social Intelligence (ICCSI) · 2022
Unmanned aerial vehicle (UAV) combat mission planning mainly consists of mission allocation and path planning. Existing mission planning models intend to achieve optimal benefits in the constraint of UAV safety guarantees. However, with the rapid reduction in UAV cost and application of low-cost UAV, some members of the UAV team are allowed to be damaged in realistic mission. Therefore, this work proposes a novel mission planning model with allowed UAV loss rate for reduced earliest arrival time (ETA) in point target surveillance mission. Considering the difficulties caused by the coupling of planned path and UAV damage probability, an approximated algorithm (C-Astar) is proposed by iteratively adding waypoints generated by classical Astar algorithm to the line-of-sight path. Simulation results show that the proposed model and algorithm could achieve lower flight time, and also demonstrate the necessity of considering the allowance of UAV damage, thus feasibility and effectiveness of the proposed work are proved.