沈艳河,韩林善,王帑

• 1:黄河水利职业技术大学
• 2:濮阳技师学院
• 3:西安理工大学

摘要(Abstract)：

针对运动学参数的不准确、关节柔顺性以及其它非线性因素对工业机器人绝对精度的影响，提出了一种误差综合校准方法。首先基于局部指数乘积（LPOE）公式和力雅可比映射，建立了负载串联机器人的正向运动学模型。通过矩阵微分和伴随映射，建立了统一的运动静态误差模型，该模型能够同步校准几何误差和变形误差。对于具有不确定性和复杂性的残差误差，采用高斯过程（GPR）对其进行建模和预测，通过补偿残余误差来提升机器人的姿态精度。与传统的分步策略不同，该方法只需一轮迭代即可同时确定运动学参数，且仅需一组负载姿态数据即可实现，无需空载姿态数据。在ABB-IRB4400工业机器人上进行了校准实验，结果表明在不同负载条件下，与最典型方法相比，所提方法可将校准精度提高约（8.1～54.8）%，验证所提校准方法的有效性。

关键词(KeyWords)： 工业机器人;机器人校准;高斯过程回归(GPR);残余误差;姿态精度

Abstract:

Keywords:

基金项目(Foundation): 2024年产学合作协同育人项目—六自由度机器人结构设计及集成作业关键技术研究（24A35028）

作者(Author): 沈艳河,韩林善,王帑

DOI: 10.19356/j.cnki.1001-3997.20260403.023

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