摘要
针对快速扩展随机树算法(RRT)扩展无方向性且路径冗长曲折的问题,提出了一种改进的RRT算法并应用于机械臂的路径规划。该算法首先利用概率目标偏向与双采样点择优原则优化采样点,以增强算法的启发性;然后引入目标引力思想来改变新节点的扩展方向,并在此基础上提出了一种可变步长思想来增强避障的效果。在MATLAB中将改进算法与RRT算法和概率偏向RRT算法进行仿真,结果表明在三维环境中改进算法的执行时间比RRT和P-RRT分别减少54.7%和33.6%,路径长度也有较大的改善。
Aiming at the problem that the rapid expansion of random tree algorithm(RRT)has no directionality and long and tortuous paths,proposes an improved RRT algorithm and applies it to the path planning of manipulators.The principle of probability target bias and double sampling point selection are used to optimize the sampling points to enhance the heuristic of the algorithm;then the idea of target gravity is introduced to change the expansion direction of the new node,and on this basis,a variable step idea is proposed to enhance the effect of obstacle avoidance.The improved algorithm,RRT algorithm and the probability-biased RRT algorithm are simulated in MATLAB,the results show that the execution time of the improved algorithm is 54.7%and 33.6%less than that of RRT and P-RRT in a three-dimensional environment,respectively,and the path length is also greatly improved.
作者
赵惠
李庆党
张明月
Zhao Hui;Li Qingdang;Zhang Mingyue(School of Automation and Electronic Engineering,Qingdao University of Science and Technology,Qingdao 266061,China;Chinsisch-Deutsche Technische Fakultat,Qingdao University of Science and Technology,Qingdao 266061,China)
出处
《电子测量技术》
北大核心
2021年第16期45-49,共5页
Electronic Measurement Technology
基金
山东省科技厅项目(2017CXGC0607)资助。
