Prediction of geometric errors of robot manipulators with Particle Swarm Optimisation method

  • Authors:

  • Gürsel Alıcı;Romuald Jagielski;Y. Ahmet Şekercioğlu;Bijan Shirinzadeh

  • Affiliations:

  • Faculty of Engineering, University of Wollongong, Australia;Department of Electrical and Computer Systems Engineering, Monash University, Australia;Centre for Telecommunication and Information Engineering, Monash University, Australia;Department of Mechanical Engineering, Monash University, Australia

  • Venue:
  • Robotics and Autonomous Systems
  • Year:
  • 2006

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Abstract

This paper reports on the prediction of the expected positioning errors of robot manipulators due to the errors in their geometric parameters. A Swarm Intelligence (SI) based algorithm, which is known as Particle Swarm Optimization (PSO), has been used to generate error estimation functions. The experimental system used is a Motoman SK120 manipulator. The error estimation functions are based on the robot position data provided by a high precision laser measurement system. The functions have been verified for three test trajectories, which contain various configurations of the manipulator. The experimental results demonstrate that the positioning errors of robot manipulators can be effectively predicted using some constant coefficient polynomials whose coefficients are determined by employing the PSO algorithm. It must be emphasized that once the estimation functions are obtained, there may be no need of any further experimental data in order to determine the expected positioning errors for a subsequent use in the error correction process.