Xu Zhining, Zhang Long, Ma Xiaoshan, Liu Yang, Yang Lin, Yang Feng
National Key Laboratory of Science and Technology on Information System Security, Systems Engineering Institute, Academy of Military Science, Beijing 100141, China.
Postgraduate College, Air Force Engineering University, Xi'an 710043, China.
Sensors (Basel). 2022 Mar 10;22(6):2151. doi: 10.3390/s22062151.
Considering that the actual operating environment of UAV is complex and easily disturbed by the space environment of urban buildings, the RoutE Planning Algorithm of Resilience Enhancement (REPARE) for UAV 3D route planning based on the A* algorithm and artificial potential fields algorithm is carried out in a targeted manner. First of all, in order to ensure the safety of the UAV design, we focus on the capabilities of the UAV body and build a risk identification, assessment, and modeling method such that the mission control parameters of the UAV can be determined. Then, the three-dimensional route planning algorithm based on the artificial potential fields algorithm is used to ensure the safe operation of the UAV online and in real time. At the same time, by adjusting the discriminant coefficient of potential risks in real time to deal with time-varying random disturbance encountered by the UAV, the resilience of the UAV 3D flight route planning can be improved. Finally, the effectiveness of the algorithm is verified by the simulation. The simulation results show that the REPARE algorithm can effectively solve the traditional route planning algorithm's insufficiency in anti-disturbance. It is safer than a traditional A* route planning algorithm, and its running time is shorter than that of the traditional artificial potential field route planning algorithm. It solves the problems of local optimization, enhances the UAV's ability to tolerate general uncertain disturbances, and eventually improves resilience of the system.
考虑到无人机的实际运行环境复杂，容易受到城市建筑空间环境的干扰，针对性地开展了基于A算法和人工势场算法的无人机三维航线规划的增强弹性航线规划算法（REPARE）。首先，为确保无人机设计的安全性，聚焦无人机机体的能力，构建风险识别、评估和建模方法，以便确定无人机的任务控制参数。然后，采用基于人工势场算法的三维航线规划算法，确保无人机在线实时安全运行。同时，通过实时调整潜在风险的判别系数，应对无人机遇到的时变随机干扰，提高无人机三维飞行航线规划的弹性。最后，通过仿真验证算法的有效性。仿真结果表明，REPARE算法能有效解决传统航线规划算法在抗干扰方面的不足。它比传统A航线规划算法更安全，运行时间比传统人工势场航线规划算法更短。它解决了局部优化问题，增强了无人机耐受一般不确定干扰的能力，最终提高了系统的弹性。
