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On the comparison of model-based and modeless robotic calibration based on a fuzzy interpolation method

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Abstract

Traditional robot calibrations implement either model-based or modeless methods. A model-based calibration method normally involves four steps: kinematic model definition of the robot, measurement process of the robot’s positions, identification of the kinematic model of the robot and compensation of the position errors. This type of method can be both time consuming and complicated because of the identification and compensation processes. Most traditional modeless methods are relatively simple and practical, but their calibration accuracy is relatively low and most of them are only suitable for the robot’s calibration in the 2D domain and in relative small workspaces. This paper provides a novel modeless fuzzy interpolation method to improve the compensation accuracy for robot calibration in the 3D workspace. A comparison between the model-based and modeless fuzzy interpolation calibration method is made. The simulated results show that the modeless fuzzy interpolation method is compatible with the model-based calibration method, and even outperforms a model-based counterpart in terms of accuracy and complexity in a relatively compact workspace.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Johnson C. Smith University, Charlotte, NC, 28216, USA

    Ying Bai

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  1. Ying Bai
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Correspondence to Ying Bai.

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Bai, Y. On the comparison of model-based and modeless robotic calibration based on a fuzzy interpolation method. Int J Adv Manuf Technol 31, 1243–1250 (2007). https://doi.org/10.1007/s00170-005-0278-4

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  • DOI: https://doi.org/10.1007/s00170-005-0278-4

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