无人机航迹规划算法分析

Analysis of Unmanned Aerial Vehicle Trajectory Planning Algorithm

为实现安全、高效的无人机飞行,需要进行航迹规划,避免与障碍物发生碰撞,从而保证航行安全。无人机的航迹规划问题主要通过智能体的路径规划算法,在一定的约束条件下进行解决,如人工势场法、快速搜索随机树法、A*算法以及跳点搜索算法。文中分析了这些常用算法的原理,通过仿真对比这些算法在求解质量与计算效率方面的性能表现,总结了每种算法的特点、局限性及适用范围。

In order to achieve safe and efficient drone flight,it is necessary to carry out path planning to avoid collisions with obstacles,so as to ensure navigation safety.The path planning problem of drone is mainly solved by the path planning algorithm of the agent under certain constraints,such as artificial potential field method,fast search random tree method,A*algorithm and jump point search algorithm.This paper analyzes the principles of these commonly used algorithms,and compares the performance of the four algorithms in terms of solution quality and computational efficiency through simulation.The characteristics,limitations and application scope of each algorithm are summarized.