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Application of joint error maximum mutual compensation for hexapod robots

Published online by Cambridge University Press:  01 January 2008

Yauheni Veryha  and
Henrik Gordon Petersen
Yauheni Veryha*
Affiliation:
Department of Industrial Software and Applications, ABB Corporate Research, 68526, Ladenburg, Germany.
Henrik Gordon Petersen
Affiliation:
The Maersk Mc-Kinney Moller Institute for Production Technology, University of Southern Denmark, 5230 Odense M.
*
*Corresponding author. E-mail: yauheni.veryha@de.abb.com
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Summary

A good practice to ensure high-positioning accuracy in industrial robots is to use joint error maximum mutual compensation (JEMMC). This paper presents an application of JEMMC for positioning of hexapod robots to improve end-effector positioning accuracy. We developed an algorithm and simulation framework in MatLab to find optimal hexapod configurations with JEMMC. Based on a real hexapod model, simulation results of the proposed approach are presented. Optimal hexapod configurations were found using the local minimum of the infinity norm of hexapod Jacobian inverse. JEMMC usage in hexapod robots can improve hexapod end-effector positioning accuracy by two times and more.

Keywords

HexapodRobot calibrationPositioning accuracyJoint error maximum mutual compensationWorst-case error
Type
Article
Information
Robotica , Volume 26 , Issue 1 , January 2008 , pp. 63 - 73
Copyright
Copyright © Cambridge University Press 2007

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