Estimation and Calibration of Robot Link Parameters with Intelligent Techniques

Using robot manipulators for high accuracy applications require precise value of the kinematics parameters. since measurement of kinematics parameters are usually associated with errors and accurate measurement of them is an expensive task, automatic calibration of robot link parameters makes the task of kinematics parameters determination much easier. 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 joint variables are measured simultaneously. this information is then used in five different algorithms; least square (ls), particle swarm optimization (pso) , genetic algorithms (ga), quadratic particle swarm optimization (qpso) and simulated annealing particle swarm optimization (sa_pso) for automatic calibration and correction of the kinematics parameters. this process was also tested experimentally via a three degree of freedom manipulator which is actually used as a coordinate measuring machine (cmm). the experimental results prove that the intelligent algorithms are useful for both parameter identification and calibration of link parameters.