Many collaborative robots use strain-wave-type transmissions due to their desirable characteristics of high torque capacity and low weight. However, their inherent complex and nonlinear behavior introduces significant errors and uncertainties in the robot dynamics calibration, resulting in decreased performance for motion and force control tasks and lead-through programming applications. This paper presents a new method for calibrating the dynamic model of collaborative robots. The method combines the known inverse dynamics identification model with the weighted least squares (IDIM-WLS) method for rigid robot dynamics with complex nonlinear expressions for the rotor-side dynamics to obtain increased calibration accuracy by reducing the modeling errors. The method relies on two angular position measurements per robot joint, one at each side of the strain-wave transmission, to effectively compensate the rotor inertial torques and nonlinear dynamic friction that were identified in our previous works. The calibrated dynamic model is cross-validated and its accuracy is compared to a model with parameters obtained from a CAD model. Relative improvements are in the range of 16.5% to 28.5% depending on the trajectory.

中文翻译：

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柔性关节协同工业机器人操纵器动力学参数化与标定

许多协作机器人由于具有所需的高扭矩能力和低重量特性而使用了应变波型变速器。但是，它们固有的复杂和非线性行为在机器人动力学校准中引入了重大的误差和不确定性，从而导致运动和力控制任务以及贯穿式编程应用程序的性能下降。本文提出了一种用于校准协作机器人动力学模型的新方法。该方法将已知的逆动力学辨识模型与用于刚性机器人动力学的加权最小二乘（IDIM-WLS）方法结合在一起，并具有针对转子侧动力学的复杂非线性表达式，以通过减少建模误差来提高校准精度。该方法依赖于每个机器人关节的两次角位置测量，在应变波传输的每一侧各加一个，以有效补偿我们先前工作中发现的转子惯性转矩和非线性动摩擦。校准后的动态模型经过交叉验证，并将其准确性与具有从CAD模型获得的参数的模型进行比较。取决于轨迹，相对改进在16.5％至28.5％的范围内。