基于Laguerre图的自优化A-Star无人机航路规划算法

为了降低无人机航路规划的运算量,减少规划时间,确保算法对于任意形状威胁区域和地形的适应性以及所规划航路的准确性,提出了一种新颖的LA-Star算法用于无人机航路规划。首先把威胁区域和禁飞区域简化为圆形,利用Laguerre图算法进行航路预规划,在此基础上简化二次规划空间的范围,之后恢复威胁区域和禁飞区域的真实形状,在简化后的规划空间内使用改进A Star算法实施二次航路规划,最后对生成的航路进行自优化处理。仿真结果证明了LA-Star算法满足航路规划的实时性和准确性要求。

Self-optimization A-Star algorithm for UAV path planning based on Laguerre diagram

In order to relieve the operation burden and time consume for unmanned aerial vehicle (UAV) path planning, a novel UAV path planning method named LA Star algorithm is proposed which as well guarantees the adaption in scenarios of various threat areas and terrains. Under the roundness assumption of all threat areas and no-fly-zones, the Laguerre diagram algorithm is applied to pre-plan the flight path which largely benefits path re-plan because of shrunk operation space. With the original shape of threat areas, improved A-Star algorithm is then applied in path re planning with reference to pre-planned path. Finally, optimize the path planned above. Simulations show the LA-Star algorithm satisfies time and veracity requirements.