UAV Route Planning Based on QPSO Algorithm under Rolling Time Domain Control

Aiming at the path planning problem of UAVs in complex environments, a RHC-QPSO path planning algorithm is proposed based on the quantum particle swarm optimization algorithm. The algorithm uses a quadtree to establish an environment model to reduce the storage of environmental information when there are many obstacles. Based on the QPSO algorithm, the UAV path optimization is performed. Combined with the RHC method, the active evasive strategy is adopted for the obstacles. The minimization of and are selected as the process performance index and used as the rolling optimization window. Optimize the indicator and change it to offline calculation for real-time online calculation. The simulation results show that the proposed algorithm can not only realize the dynamic path planning of UAVs with certain prior knowledge of the map in real time and effectively, but also prevent the UAV from making large maneuvers to avoid obstacles during the planning process. The smoothness of the path improves the safety of the drone.