Reduce Positioning Error for Robot Manipulator with Intelligent Technique

被引:0
|
作者
Barati, Maryam
Khoogar, Ahmad Reza
Nasiriyan, Mehrzad
机构
来源
MEMS, NANO AND SMART SYSTEMS, PTS 1-6 | 2012年 / 403-408卷
关键词
calibration; identification; genetic algorithm; PSO; least square; robot; manipulator; link parameter; CALIBRATION;
D O I
10.4028/www.scientific.net/AMR.403-408.697
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Using robot manipulators for high accuracy applications require precise value of the kinematics parameters. Since measurement of kinematics parameters are usually corrupted with errors and their accurate measurements are usually expensive, automatic calibration of robot link parameters makes the determination of kinematic parameters much simpler. In this paper a simple and easy to use algorithm is introduced for correction and calibration of robot kinematics parameters. Actually, at several end-effecter positions, the corresponding joint variables are measured simultaneously. This information is then used in three different algorithms; the Least Square (LS), the Particle Swarm Optimization (PSO) and the Genetic algorithms (GA) for automatic calibration and correction of the kinematics parameters. This process was also tested experimentally using a three degree of freedom manipulator which was actually built as a coordinate measuring machine (CMM). The experimental Results show that the intelligent algorithms provide better results for both parameter identification and calibration of the link parameters.
引用
收藏
页码:697 / 706
页数:10
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