基于多旋翼无人机的输气管道巡检路径规划研究

Research on Path Planning of Gas Pipeline Inspection Based on Multi-rotor UAV

为了解决多旋翼无人机在工业输气管道巡检的过程中快速规避障碍物问题,提出了一种基于快速扩展随机树(Rapidly-exploring Random Tree,RRT)的改进算法,针对传统RRT算法的随机性高、收敛速度慢和规划路径长且曲折问题,结合空间环境特点在随机点采样方式和路径优化两个方面做出了改进。首先,设置随机采样点的取值范围;然后引入目标偏向采样策略对随机树的扩展方向进行引导;最后对生成的路径进行裁剪和平滑处理,并通过在不同的数字模拟地图中与传统RRT算法、带路径修正的启发式RRT算法进行仿真实验比较。实验结果表明:改进后的RRT算法在执行输气管道巡检任务时能够快速地生成一条路径短且平滑的避障路径。

In order to solve the problem of multi-rotor UAV quickly avoiding obstacles during the inspection process of industrial gas pipelines,an improved algorithm based on Rapidly-exploring Random Tree(RRT)is proposed,aiming at the problems of high randomness,slow convergence speed and long and tortuous planning paths of traditional RRT algorithms,combined with the characteristics of the space environment.Two aspects including random point sampling and path optimization have been improved.First,this paper sets the value range of random sampling points,then introduces the target bias sampling strategy to guide the expansion direction of the random tree,and finally cuts and smoothes the generated path.The simulation experiment is compared with traditional RRT algorithm and heuristic RRT algorithm with path correction in different digital analog maps.The experimental result shows that the improved RRT algorithm can quickly generate a short and smooth obstacle avoidance path when performing gas pipeline inspection tasks.