Publication
Experimental Robot Inverse Dynamics Identification Using Classical and Machine Learning Techniques
Vinzenz Bargsten; José de Gea Fernández; Yohannes Kassahun
In: International Symposium on Robotics. International Symposium on Robotics (ISR), June 21-22, München, Germany, 2016.
Abstract
This paper shows the experimental identification of the inverse dynamics model of a KUKA iiwa lightweight robot.
We use experimental data from optimal identification experiments to evaluate and compare two different identification
approaches: a classical method using a parametrized robot dynamical model and a machine learning method. Both
methods accurately estimate the dynamics model and this paper will discuss the pros and cons of each method.