精准建模UR10机器人动力学，提升控制与规划精度。
The Dynamic Model of the UR10 Robot and its ROS2 Integration
- 分三阶段识别参数：线性、非线性摩擦与电机增益。
- 电流预测精度提升最高达4.43倍，电机增益更精确。
- 支持任意负载配置，适合工业机器人开发与调试。
本文提出UR10工业机器人的完整动力学模型。采用三阶段辨识方法估算机械臂动态参数：首先用标准线性回归计算线性参数；随后基于指数函数模型估计非线性摩擦参数；最后设计电机驱动增益，将估算的关节电流映射为力矩。所建立的模型可用于控制与规划，配套的ROS2软件可轻松配置以适应任意负载。实验在多组激励轨迹上验证模型，与现有最优模型对比，电流预测精度最高提升4.43倍，电机增益更为准确。相关代码已开源，地址为 https://codeocean.com/capsule/8515919/tree/v2。
原文摘要 · Abstract (English)
This paper presents the full dynamic model of the UR10 industrial robot. A triple-stage identification approach is adopted to estimate the manipulator's dynamic coefficients. First, linear parameters are computed using a standard linear regression algorithm. Subsequently, nonlinear friction parameters are estimated according to a sigmoidal model. Lastly, motor drive gains are devised to map estimated joint currents to torques. The overall identified model can be used for both control and planning purposes, as the accompanied ROS2 software can be easily reconfigured to account for a generic payload. The estimated robot model is experimentally validated against a set of exciting trajectories and compared to the state-of-the-art model for the same manipulator, achieving higher current prediction accuracy (up to a factor of 4.43) and more precise motor gains. The related software is available at https://codeocean.com/capsule/8515919/tree/v2.
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