Robot Collision Detection based on Fuzzy Identification and Time Series Modelling





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Published on Sep 19, 2013

Fotios Dimeas
L.D. Avendano-Valencia
Elpida Nasiopoulou
Nikos Aspragathos

Robotics Group, Dept. of Mechanical Engineering & Aeronautics
University of Patras, Rio 26504, Greece

Robots that share workspace with humans require safety capabilities to identify possible collisions and perform appropriate reactions in order to eliminate the potential injury of a human. For this purpose, an intelligent fuzzy identification method and a time series method are proposed and implemented in this paper. These systems are trained to the robot dynamics with and without collision to be able to detect contacts along the links of the robot. Since the speed of the detection is of critical importance to avoid injuries, attention is paid to recognise a collision as soon as possible. The proposed methods are evaluated in an experimental setup by using a KUKA LWR manipulator and their performance is compared with a model-based approach.

Paper appeared in RAAD 2013 Conference
22nd International Workshop on Robotics in Alpe-Adria-Danube Region
September 11-13, 2013, Portoroz, Slovenia


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