Abstract For collaborative robots, the ability to accurately predict the actuator torques required to realize the desired task is highly important. This will improve and guarantee the safety, motion and force control performance, and smooth lead-through programming experience. Thus, this paper presents the investigation towards comprehensive modeling and identification of nonlinear joint dynamics for collaborative robots. The proposed joint dynamics model and identification describes the most dominant dynamic characteristics of robot joints that comprise strain-wave transmissions, such as nonlinear friction, nonlinear stiffness, hysteresis, and kinematic error. Position-dependent backlash characteristics is observed and quantified using our proposed identification method and the Generalized Maxwell-Slip friction model is extended to describe the observed phenomena. The developed dynamic modeling and identification procedures provides insightful guidance for the design and model-based control of collaborative robots.

中文翻译：

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协同工业机器人机械手非线性关节动力学综合建模与辨识

摘要 对于协作机器人，准确预测实现所需任务所需的致动器扭矩的能力非常重要。这将提高和保证安全、运动和力控制性能，以及流畅的引导式编程体验。因此，本文提出了对协作机器人非线性关节动力学综合建模和识别的研究。所提出的关节动力学模型和识别描述了机器人关节最主要的动态特性，包括应变波传输，例如非线性摩擦、非线性刚度、滞后和运动误差。使用我们提出的识别方法观察和量化位置相关的齿隙特性，并扩展广义麦克斯韦滑动摩擦模型来描述观察到的现象。开发的动态建模和识别程序为协作机器人的设计和基于模型的控制提供了深刻的指导。