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<p>In response to the critical need for enhanced positioning accuracy of industrial robots within manufacturing, this paper introduces a novel calibration technique predicated on visual pose measurement. This approach, designed for high precision within a constrained operational range, marks a significant advance over traditional methods by integrating multi-point pose constraints and accounting for hysteresis losses associated with joint currents. The study’s cornerstone is the utilization of the Levenberg–Marquardt (LM) iterative algorithms for the precise identification of the robot’s kinematic parameters, a method that represents a substantial innovation in robotic calibration protocol. Empirical validation of the proposed method yielded a remarkable improvement in endpoint positioning accuracy, with a reduction from 2.77 to 0.284&#xa0;mm. These results not only underscore the method’s efficacy but also its applicability to real-world industrial contexts, where such improvements in accuracy can lead to substantial enhancements in manufacturing precision and efficiency.</p>

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A method for kinematic calibration of robots using visual multi-point pose constraints considering hysteresis loss

  • 期刊论文

  • 发表日期：

    2025年7月4日

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  • Yongxing Liu,
  • Xiaoqi Tang,
  • Yixuan Guo,
  • Xiangdong Zhou,
  • Bao Song,
  • Tianhang Chen

摘要

In response to the critical need for enhanced positioning accuracy of industrial robots within manufacturing, this paper introduces a novel calibration technique predicated on visual pose measurement. This approach, designed for high precision within a constrained operational range, marks a significant advance over traditional methods by integrating multi-point pose constraints and accounting for hysteresis losses associated with joint currents. The study’s cornerstone is the utilization of the Levenberg–Marquardt (LM) iterative algorithms for the precise identification of the robot’s kinematic parameters, a method that represents a substantial innovation in robotic calibration protocol. Empirical validation of the proposed method yielded a remarkable improvement in endpoint positioning accuracy, with a reduction from 2.77 to 0.284 mm. These results not only underscore the method’s efficacy but also its applicability to real-world industrial contexts, where such improvements in accuracy can lead to substantial enhancements in manufacturing precision and efficiency.