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On the Comparison of Trilinear, Cubic Spline, and Fuzzy Interpolation Methods in the High-Accuracy Measurements

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2 Author(s)
Ying Bai ; Computer Science and Engineering Department, Johnson C. Smith University, Charlotte, USA ; Dali Wang

This paper provides a comparison between a novel technique used for the pose-error measurements and compensations of robots based on a fuzzy-error interpolation method and some other popular interpolation methods. A traditional robot calibration implements either model or modeless methods. The measurement and compensation of pose errors in a modeless method moves the robot's end-effector to the target poses in the robot workspace and measures the target position and orientation errors using some interpolation techniques in terms of the premeasured neighboring pose errors around the target pose. For the measurement purpose, a stereo camera or other measurement devices, such as a coordinate-measurement machine (CMM) or a laser-tracking system (LTS), can be used to measure the pose errors of the robot's end-effector at predened grid points on a cubic lattice. By the use of the proposed fuzzy-error interpolation technique, the accuracy of the pose-error compensation can be improved in comparison with other interpolation methods, which is conrmed by the simulation results given in this paper. A comparison study among most popular interpolation methods used in modeless robot calibrations, such as trilinear, cubic spline, and the fuzzy-error interpolation technique, is also made and discussed via simulations. The simulation results show that more accurate measurement and compensation results can be achieved using the fuzzy-error interpolation technique compared with its trilinear and cubic-spline counterparts.

Published in:

IEEE Transactions on Fuzzy Systems  (Volume:18 ,  Issue: 5 )