Application of genetic algorithms to robot kinematics calibration

Abstract

Position and orientation accuracy of an end-effector is affected by the precision of kinematics parameters of the robot manipulator. Thus, good precision requires good knowledge of robot physical parameter values. However, this condition can be difficult to meet in practice. Hence, calibration techniques can be devised in order to improve the robot accuracy through estimation of these particular parameters. In this article, the genetic algorithm is used to calibrate the robot kinematics accuracy. A kinematics model is formulated and conducted as an optimisation problem for ABB Irb 6000 robot manipulator. The objective is to analyse and evaluate the performance of the GA in optimising such robot kinematics accuracy. In this algorithm, small changes in the kinematics parameters values represent the parent and offspring population and the end-effector error represents the fitness functions. A numerical example has been used to demonstrate the convergence and effectiveness of the given model.

Keywords:

• genetic algorithms
• robot manipulators
• robot kinematics
• robot calibration

Acknowledgements

I would like to thank Per Kristian, Trygve Thomessen and Jonathan Lienhardt from PPM Company for supporting the project and testing the program.