This work proposes a path planning algorithm based on A and DWA to achieve global path optimization while satisfying security and speed requirements for unmanned aerial vehicles (UAV). The algorithm first preprocesses the map for irregular obstacles encountered by a UAV in flight, including grid preprocessing for arc-shaped obstacles and convex preprocessing for concave obstacles. Further, the standard A algorithm is improved based on UAV’s flight environment information and motion constraints. Further, the DWA algorithm’s limitations regarding local optimization and long planning time are mitigated by adaptively adjusting the evaluation function according to the UAV’s safety threshold, obstacles, and environment information. As a result, the global optimal path evaluation subfunction is constructed. Finally, the key points of the global path are selected as the subtarget points of the local path planning. Under the premise of the optimal path, the UAV real-time path’s efficiency and safety are effectively improved. The experimental results demonstrate that the path planning based on improved A and DWA algorithms shortens the path length, reduces the planning time, improves the UAV path smoothness, and enhances the safety of UAV path obstacle avoidance.

中文翻译：

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基于改进A和DWA算法的无人机路径规划

这项工作提出了一种基于 A和 DWA的路径规划算法，以实现全局路径优化，同时满足无人机 (UAV) 的安全性和速度要求。该算法首先对无人机在飞行中遇到的不规则障碍物进行地图预处理，包括对弧形障碍物的网格预处理和对凹形障碍物的凸面预处理。此外，标准 A基于无人机的飞行环境信息和运动约束改进算法。此外，通过根据无人机的安全阈值、障碍物和环境信息自适应调整评估函数，减轻了 DWA 算法在局部优化和长规划时间方面的局限性。从而构建了全局最优路径评估子函数。最后，选取全局路径的关键点作为局部路径规划的子目标点。在路径最优的前提下，有效提高了无人机实时路径的效率和安全性。实验结果表明，基于改进A的路径规划 DWA算法缩短了路径长度，减少了规划时间，提高了无人机路径平滑度，增强了无人机路径避障的安全性。