Anthropomorphic motion planning for 7-degrees of freedom manipulator with task constraints

被引:0
|
作者
Xia J. [1 ]
Zhou S. [1 ]
Zhang H. [1 ]
Liu Z. [2 ]
机构
[1] School of Mechanical Engineering, Xi,an University of Science and Technology, Xi'an
[2] Hefei Harbinger Intelligent Robot Co. Ltd., Hefei
关键词
Gaussian process; humanoid manipulator; motion planning; self-motion manifold; task constraints;
D O I
10.13245/j.hust.230510
中图分类号
学科分类号
摘要
An anthropomorphic motion planning method for 7-degrees of freedom manipulator under task constraints was proposed to solve the problems of large computation,low efficiency and no consideration of anthropomorphism in motion planning under task constraints based on random sampling algorithm. The proposed method sampled in the task space. First,a collision-free path satisfying the task constraints was planned for the end of the manipulator,and the relationship between the end path point of the manipulator and the configuration of the anthropoid arm was obtained by using Gaussian process regression method. Then,a complete description of the robot arm self-motion manifolds was given,and a sub-anthropomorphic arm configuration was selected for the terminal path points corresponding to the anthropomorphic arm configuration that did not satisfy the joint limit or collision,and a mapping relationship between task space and joint space was obtained.Finally,this mapping relationship was combined with collision-free paths in task space for robotic arm anthropomorphic motion planning. Experiment results show that the proposed method reduces the path length by 55% and 38%,and increases the speed by 39% and 68% than the rapidly-exploring random trees star (RRT*) algorithm and projection-based methods,respectively,which satisfies the task constraint and is more anthropomorphic in motion. © 2023 Huazhong University of Science and Technology. All rights reserved.
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页码:60 / 66
页数:6
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