Dynamic Model Identification of Collaborative Robots Using a Three-Loop Iterative Method

Jie Deng, Weiwei Shang, Bin Zhang, Shengchao Zhen, S. Cong
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Abstract

Accurate dynamic model is of crucial importance for collaborative robot to achieve a satisfying performance in model-based control or other applications. Nevertheless, it is often difficult to identify dynamic parameters accurately due to the joint elasticity and nonlinear fricitonal impact. Considering viscous friction nonlinearity and a minor Stribeck effect commonly seen in the practical situations, we present a three-loop iterative method for the dynamic model identification of collaborative robots. The inner loop is well-designed to identify the mass-inertial parameters and linear friction parameters of the robot with a least-squares approach. As for the middle loop, a suitable nonlinear viscous friction model is applied to improve the identification results. The impact of the Stribeck effect is thoroughly studied in the outer loop. Experiments on a six-dof collaborative robot have proved the identification errors can be significantly reduced by our method.
基于三环迭代法的协作机器人动态模型辨识
精确的动力学模型对于协作机器人在基于模型的控制或其他应用中取得满意的性能至关重要。然而,由于关节的弹性和非线性摩擦冲击,动态参数的准确识别往往是困难的。考虑到实际情况中常见的粘性摩擦非线性和轻微的Stribeck效应,提出了一种用于协作机器人动态模型辨识的三环迭代方法。设计了内环,利用最小二乘法辨识机器人的质量-惯性参数和线性摩擦参数。对于中回路,采用合适的非线性粘性摩擦模型来改善辨识结果。在外环中对斯特里贝克效应的影响进行了深入的研究。在六自由度协作机器人上的实验证明,该方法能显著降低识别误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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