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Identifying the dynamic model used by the KUKA LWR: A reverse engineering approach

机译:识别KUKA LWR使用的动态模型:逆向工程方法

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An approach is presented for the model identification of the so-called link dynamics used by the KUKA LWR-IV, a lightweight manipulator with elastic joints that is very popular in robotics research but for which a complete and reliable dynamic model is not yet publicly available. The control software interface of this robot provides numerical values of the link inertia matrix and the gravity vector at each configuration, together with link position and joint torque sensor data. Taking advantage of this information, a general procedure is set up for determining the structure and identifying the value of the relevant dynamic coefficients used by the manufacturer in the evaluation of these robot model terms. We call this a reverse engineering approach, because our main goal is to match the numerical data provided by the software interface, using a suitable symbolic model of the robot dynamics and the inertial and gravity coefficients that are being estimated. Only configuration-dependent terms are involved in this process, and thus static experiments are sufficient for this task. The main issues of dynamic model identification for robots with elastic joints are discussed in general, highlighting the pros and cons of the approach taken for this class of KUKA lightweight manipulators. The main identification results, including training and validation tests, are reported together with additional dynamic validation experiments that use the complete identified model and joint torque sensor data.
机译:提出了一种模型识别方法,用于模型识别由KUKA LWR-IV使用的所谓链接动力学,该模型是具有弹性关节的轻型机械手,在机器人研究中非常流行,但尚未公开提供完整而可靠的动力学模型。 。该机器人的控制软件界面提供每种配置下的连杆惯性矩阵和重力矢量的数值,以及连杆位置和关节扭矩传感器数据。利用此信息,建立了一个通用程序来确定结构并确定制造商在评估这些机器人模型项时使用的相关动态系数的值。我们称其为逆向工程方法,因为我们的主要目标是使用合适的机器人动力学符号模型以及估计的惯性和重力系数来匹配软件界面提供的数值数据。在此过程中仅涉及与配置有关的术语,因此静态实验足以完成此任务。一般讨论了具有弹性关节的机器人的动态模型识别的主要问题,突出了此类KUKA轻型机械手所采用方法的优缺点。报告主要的识别结果,包括培训和验证测试,以及使用完整的已识别模型和关节扭矩传感器数据的其他动态验证实验。

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