基于改进RRT算法的6-DOF机器人路径规划

PATH PLANNING OF 6-DOF ROBOT BASED ON IMPROVED RRT ALGORITHM

针对传统快速扩展随机树(RRT)算法在机器人路径规划中随机性大、冗余节点多、无法生成最优路径这一系列问题,从引入权重系数、路径缩短、拐角平滑处理这三方面对传统RRT算法进行优化,使6-DOF机械臂能有效避开障碍物,并通过距离最短路径到达目标点。同时,在角速度不连续处根据机械臂曲率约束进行路径平滑过渡处理,消除初始路径中锯齿状部分,保证路径平稳性。仿真实验表明,改进RRT算法提高了路径搜寻成功率并将原始路径距离缩短25%,平均规划时间缩短75%。

The traditional rapidly exploring random tree(RRT)algorithm has a series of problems in robot path planning,such as large randomness,a lot of redundant nodes,and unable to generate the optimal path.Therefore,this paper optimizes the traditional RRT algorithm from the introduction of weight coefficients,path shortening,and corner smoothing processing.The 6-DOF manipulator could effectively avoid obstacles and reach the target point through the shortest path.According to the curvature constraints of the mechanical arm,the smooth transition of the path was performed at the position of the angular velocity discontinuity,so as to eliminate the serrated part of the initial path and ensure the path stability.The simulation experiments show that the improved RRT algorithm improves the success rate of the path search,shortens the original path distance by 25%,and reduces the average planning time by 75%.