基于改进RRT算法的UAV航迹规划与优化研究

PATH PLANNING AND OPTIMIZATION OF UAV BASED ON IMPROVED RRT ALGORITHM

分析步长、搜索次数对UAV航迹生成的影响,给出一种改进RRT算法。结合目标信息给出启发因子、优话采样节点选择方法、选取合适的启发概率等方法,解决了扩展树生长过程中随机性较大的问题,提高了全局搜索能力和搜索速度,同时考虑局部搜索精度。针对航迹随机化造成的航迹不够优化的问题,提出一种航迹迭代优化方法。仿真结果表明:该算法和优化方法具有较快的收敛速度和更短的搜索时间;迭代优化方法减少了冗余规划点,缩短了规划航迹,提高了航迹规划效率。

This paper analyzes the impact of UAV track generation on the change of step size and search times,and proposes an improved RRT algorithm.By combining the target information to give the heuristic factor,the selection method of the sampling node and the appropriate heuristic probability,and the problem of large randomness was solved in the process of expanding the tree.We improved the global search ability and search speed,and considered the local search accuracy.Finally,aiming at the problem of track randomization and insufficient track optimization,we proposed a track iterative optimization method.The simulation results show that our algorithm and optimization method have faster convergence speed and shorter search time.The iterative optimization method reduces redundant planning points,shortens planning track and improves track planning effectiveness.