A new solution for inverse kinematics of 7-DOF manipulator based on neural network

被引:8
作者
Yang, Yugui [1 ]
Peng, Guangzheng [1 ]
Wang, Yifeng [1 ]
Zhang, Hongli [1 ]
机构
[1] Beijing Inst Technol, Sch Informat Sci & Technol, Dept Automat Control, Beijing 100081, Peoples R China
来源
2007 IEEE INTERNATIONAL CONFERENCE ON AUTOMATION AND LOGISTICS, VOLS 1-6 | 2007年
关键词
GA; neural network; redundant manipulator; joint compliance; inverse kinematics;
D O I
10.1109/ICAL.2007.4338894
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
For dealing with the complexity in gaining inverse kinematics solution of 7-DOF manipulator, a new approach based on RBF neural network is proposed. To solve the problem of multi-solution caused by redundancy, a rule for a joint of "best compliance" based on weighted Least Square Method is supposed at the beginning of this paper, which makes the multisolution a mono-one. And with application of genetic algorithm (GA) to search for all global optimum solution, the sample-data of artificial neural network training is gained successfully. In artificial neural network training and simulating, satisfactory result has been achieved. Simulation shows that the method proposed in the paper is feasible, provides a new approach for inverse kinematics solution of manipulator of any redundancy.
引用
收藏
页码:1958 / 1962
页数:5
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