4.7 Article

Simultaneous and on-line calibration of a robot-based inspecting system

Journal

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
Volume 49, Issue -, Pages 349-360

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rcim.2017.08.006

Keywords

Kinematics identification; On-line calibration; Self-calibration; Hand-eye calibration

Funding

  1. National Natural Science Foundation of China [51575354]
  2. National Key Technology Research and Development of the Ministry of Science and Technology of China (973 Program) [2014CB046604]
  3. Shanghai Municipal Science and Technology project [16111106102]

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For a robot-based inspecting system calibration procedure in the production environment, it is desirable that the calibration technique should be automatic, time-saving and convenient to implement. The paper presents a new self-calibration method to calibrate and compensate for the robot-based inspecting system's kinematic errors. Compared with traditional calibration methods, this calibration approach has several unique features. First, the inspecting system can be calibrated without external measurement devices since an optical sensor is mounted to the robot end-effector as its integral part, so it can make the inspecting system realizing on-line calibration. Second, it simultaneously calibrates all the kinematic parameters of the inspecting system in one step to avoid error propagation rather than calibrate the hand-eye relationship, the robot itself and the robot exterior relationship separately. Third, the paper analyzes and eliminates redundant kinematic parameters in the inspecting system's kinematic model and derives a MDH model without redundancy. These features not only realize the automatic calibration of the inspecting system but also greatly reduce the number of identified parameters and avoid error propagation, therefore, enhance the efficiency and accuracy of parameter estimation. Experiments are conducted on a 6 DOF serial robot-based inspecting system to validate the good performance of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.

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