摘要
针对管道与洞穴等狭窄空间下传统hRRT算法难以有效扩展而导致路径无解的问题,提出了一种融合切线段的hRRT狭窄通道路径规划算法。首先凭借hRRT算法偏向目标扩展到障碍物附近,然后利用切线段寻找狭窄空间入口并且保证随机树在狭窄空间中有效扩展,同时删除切线段确定的重复切点促使算法快速跳出局部收敛,如果随机树中存在节点与目标点间无障碍,则路径搜索成功。仿真实验结果表明,与传统hRRT算法和切线算法相比,该算法在普通空间环境与狭窄空间环境中,获得的路径长度相对较短,搜索时间减少了89%。
In order to solve the problem that the traditional hRRT algorithm is difficult to expand effectively in narrow space such as pipeline and cave,a path planning algorithm based on tangent segment is proposed.First the hRRT algorithm is adopted to target expanded near the obstacles,and then use tangents for narrow space entrance and ensure effective extension in random tree in narrow space,at the same time delete tangents of repeated cutting force algorithm quickly jump out of local convergence,if random tree nodes exist in the barrier-free between with the target point,the path search is successful.The experimental results show that compared with the traditional hRRT algorithm and tangent algorithm,the path length obtained by this algorithm is relatively short in the ordinary space environment and the narrow space environment,and the search time is reduced by 89%.
作者
周飞龙
甘屹
ZHOU Fei-long;GAN Yi(School of Mechanical Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《软件导刊》
2021年第10期154-158,共5页
Software Guide
