Abstract

Non-geometric errors mainly caused by the joint compliance should be identified and compensated as well as geometric errors to improve the accuracy. This paper presents a new comprehensive error model consisting of both geometric and compliance parameters. A new approach is proposed for intelligent selection and optimization of measurement poses based on interference detection method and linearly decreasing weight particle swarm optimization (LinWPSO) algorithm. Simulation results on a 6-DOF serial industrial robot demonstrate that using the optimal measurement poses can significantly improve the calibration accuracy and measurement efficiency.

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