A Novel Method for the Motion Planning of Hyper-redundant Manipulators Based on Monte Carlo
The motion planning of hyper-redundant manipulator has been viewed as the most challenging for computing the inverse kinematics due to its enormous work space and a large or infinite degree of freedom.In this paper,we introduce a new approach to solve the inverse kinematics problem that uses the Monte Carlo method to search manipulator configurations.We simulate thousands of random manipulator positions without any lookahead search.For the purpose of solving the problem of expending a great deal of time,an improvement search method was applied that combines Monte Carlo simulation with establish cubes in the reachable workspace of a hyper-redundant manipulator.Using this method,the simulation experiment expends approximate half of time than Monte Carlo method,and has the less positional errors.
Hyper-redundant manipulators Motion planning Monte Carlo Random searching
Jingdong Zhao Liangliang Zhao Yan Wang
State Key Laboratory of Robotics and System, Harbin Institute of Technology,Harbin 150001, China
国际会议
广州
英文
11-22
2016-12-15（万方平台首次上网日期，不代表论文的发表时间）