@inproceedings{d13b767fb97e4fa68783c73a9d909ce2,
title = "Simultaneous Calibration and Stiffness Identification of Flexible Link Robots using Lumped Parameter Model",
abstract = "Elastic joints and/or links greatly influence the position and orientation accuracy of robots. Hence, standard geometric calibration might be insufficient for elastic robots and stiffness identification is also required for improved accuracy. This paper describes the simultaneous identification of geometric as well elasticity parameters of a 3-DoF flexible link robot using a lumped parameter model. These parameters were identified via the usage of 100 optimal poses and thoroughly verified with more than 9500 poses, which were distributed over the whole workspace and measured via a laser tracker. Experimental results for a standard geometric calibration as well as a combined geometric and stiffness identification approach are presented. The simultaneous identification approach leads to a maximum position error of 1.50 mm compared to 5.71 mm for geometric calibration only. The determined parameters as well as dependencies are shown and discussed for physical interpretability.",
author = "Stefan Gadringer and Patrick Klement and Hubert Gattringer and Andreas M{\"u}ller and Ronald Naderer",
year = "2022",
month = apr,
doi = "10.1007/978-3-031-04870-8\_7",
language = "English",
isbn = "978-3-031-04869-2",
volume = "120",
series = "Mechanisms and Machine Science",
pages = "52--59",
editor = "Andreas M{\"u}ller and Mathias Brandst{\"o}tter",
booktitle = "Advances in Service and Industrial Robotics - RAAD 2022",
}