摘要
由非完整约束定义提出一种改进RRT(快速搜索随机树)算法,解决受动力学约束的移动机器人运动规划问题.该算法将移动机器人的非完整约束条件与RRT搜索算法相结合.针对RRT算法在全局状态空间均匀随机搜索导致算法无谓耗费代价大的缺陷,引入目标偏向思想,并选择计算复杂度低的距离参数提高求解速度.通过几类典型的非完整约束下的机器人运动规划仿真实验,证实了该算法的有效性和高效性.
An improved RRT（rapidly-exploring random tree） algorithm is presented from the definition of nonholonomic constraints to solve the motion planning problem for mobile robots with dynamics constraints.The algorithm combines the nonholonomic constraints of mobile robot with RRTs.For RRTs,in order to reduce unnecessary costs caused by uniformly random searching in the global state space,the idea of goal bias is introduced and the distance parameter with low computational complexity is also selected to increase the calculation speed.Simulation experiments with several typical robot motion planning with nonholonomic constraints verify the validity and high efficiency of the algorithm.
出处
《机器人》
EI
CSCD
北大核心
2011年第6期666-672,共7页
Robot
基金
机器人学国家重点实验室基金资助项目(R2200703)
