Maximum likelihood identification of a dynamic robot model: Implementation issues
Maximum likelihood identification of a dynamic robot model: Implementation issues
复制标题
DOI：
10.1177/027836402760475379
复制
发表时间：
2002-02-01
影响因子：
9.2
通讯作者：
Verdonck, W
中科院分区：
文献类型：
--
作者：
Olsen, MM;Swevers, J;Verdonck, W
本文认为，实际执行的一个新的最大似然机器人识别方法，奥尔森和彼得森开发。特别是实际问题的联合速度和加速度的估计，从联合角度测量，其后果的参数估计和精度，被认为是。KUKA IR 361工业机器人的仿真和实验结果进行了讨论，并与使用更简单的加权最小二乘法获得的模型进行了比较。
This paper considers the practical implementation of a new maximum likelihood robot identification method, developed by Olsen and Petersen. In particular the practical issue concerning the estimation of the joint velocities and accelerations from joint angle measurements, and its consequence on the parameter estimation and accuracy, is considered. Simulation and experimental results on a KUKA IR 361 industrial robot are discussed, and compared with models obtained using a much simpler weighted least squares method.