基于自适应步长RRT的双机器人协同路径规划

Cooperation Path Planning of Dual-robot Based on Self-adaptive Stepsize RRT

针对快速随机扩展树(Rapidly exploring-random tree,RRT)方法的步长确定过分依赖于程序调试,需耗费大量时间,且固定步长存在碰撞检测失效问题,提出了自适应步长RRT方法。通过建立构型空间与工作空间的范数相容不等式,把工作空间中产生的步长约束在允许范围内,进而实现有效的碰撞检测;提出了随机树被动生长方法,实现了双机器人在各自构型空间中的协同路径规划。仿真对比结果表明,采用自适应步长RRT方法进行双机器人路径规划时,随机树的每一次生长所产生的位移不超过设定值,保证了碰撞检测的有效性,相比传统的固定步长RRT,自适应步长RRT方法无需多次调试就能确定步长,提高了机器人的路径规划速度。

An appropriate stepsize is required to be set up when using rapidly exploring-random tree(RRT)to perform path planning of a robot,which needs user to proceed debugging the program and it’s generally time-consuming,also a fixed stepsize in RRT always resulting in invalid collision-test.Aiming at solving the above problems existing in RRT,a self-adaptive stepsize RRT was proposed.The matrix operator norm induced from configuration space norm and work space norm was founded based on Jacobi matrix and the norm inequality of configuration space and work space was established,by the means of which the displacement of robot caused by each stepsize in configuration space was limited in allowed magnitude which validated collision test.In order to coordinate dual-robot,passive growing of random tree algorithm was put forward.The algorithm can control the growth of random tree of dual-robot in different configuration spaces,and then the motion of dual-robot was coordinated to ensure generating cooperation path in work space.Numerical experiment indicated that the self-adaptive stepsize RRT can bound the displacement of each step within the value set up at beginning of algorithm which guaranteed the effectiveness of collision test.Compared with standard fixed stepsize RRT,self-adaptive stepsize RRT omitted the process of determining stepsize only needed to set maximum value of stepsize in work space which improved the efficiency of path planning.The algorithm proposed can provide a new perspective on the path planning of dual-arm robot.