| Bibliography | Oubbati, M.; Levi, P.; Schanz, M.: Recurrent Neural Network for wheeled mobile Robot Control.
In: 4th WSEAS International on Robotics, Distance Learning and Intelligent Communication Sytems: Izmir-Turkey; September 2004. Vol. 3(6).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 2460-2467, english.
WSEAS, September 2004.
Article in Proceedings (Conference Paper).
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| Corporation | WSEAS |
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| CR-Schema | I.2.9 (Robotics)
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| Keywords | Mobile robots; Recurrent neural network; velocity tracking control; Omni-direction. |
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| Abstract | In the problem of motion control for mobile robots, typically only the kinematic model is used, assuming that there is a dynamic controller that can produce perfect velocity tracking. However, when the dynamic model of the robot is considered, exact knowledge about its parameters is almost unattainable in practical situations. In this paper, a novel recurrent neural network called Echo-State Network is used to develop a dynamic-level controller, without knowledge about the robot parameters. The control approach has been experimentally tested on an omnidirectional mobile robot available at the Robotics Lab of the University of Stuttgart.
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| Department(s) | University of Stuttgart, Institute of Parallel and Distributed Systems, Image Understanding
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| Project(s) | COPS
SFB-627
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| Entry date | March 11, 2005 |
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