Effectiveness of the DIDIM method with respect to the usual CLOE method. Application to the dynamic parameters identification of an industrial robot

A. Jubien, M. Gautier, A. Janot
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引用次数: 1

Abstract

The Usual Closed Loop Output Error (CLOE) method for dynamic parameters identification of robots has several drawbacks: slow convergence, sensitivity to initial conditions and the calculation of significant parameters is not easy-to-run. Recently a new CLOE method called as DIDIM for Direct and Inverse Identification Model needing only actual forces/torques data was validated on rigid robots. This method avoids the drawbacks of the usual CLOE method. With the DIDIM method, the optimal parameters minimize the 2-norm of the error between the actual forces/torques and the simulated ones. It is based on a closed-loop simulation of the robot using the direct dynamic model, the same structure of control-law and the same reference trajectory for both the actual robot and the simulated one. The DIDIM method simplifies dramatically the non-linear Least Squares problem by using the Inverse Dynamic Model in order to obtain an analytical expression of the simulated forces/torques which are linear in the parameters. This explains why the DIDIM method has a fast convergence. In this paper, the DIDIM method is compared with the usual CLOE method which uses the actual positions as output. Experiments are performed on a 6 degrees of freedom robot Stäubli TX40.
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DIDIM方法相对于通常的CLOE方法的有效性。应用于工业机器人的动态参数辨识
常用的闭环输出误差(CLOE)方法用于机器人动态参数辨识,存在收敛速度慢、对初始条件敏感、重要参数计算不方便等缺点。最近在刚性机器人上验证了一种仅需要实际力/力矩数据的DIDIM正逆识别方法。这种方法避免了通常CLOE方法的缺点。采用DIDIM方法,优化参数使实际力/力矩与模拟力/力矩误差的2范数最小。它是基于机器人的闭环仿真,使用直接动力学模型,对实际机器人和仿真机器人使用相同的控制律结构和相同的参考轨迹。DIDIM方法利用逆动力学模型极大地简化了非线性最小二乘问题,得到仿真力/力矩在参数上呈线性关系的解析表达式。这就解释了DIDIM方法收敛速度快的原因。本文将DIDIM方法与通常使用实际位置作为输出的CLOE方法进行了比较。实验在6自由度机器人Stäubli TX40上进行。
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