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A Neural Network-Based Approach to Robot Motion Control

Uli Grasemann, Daniel Stronger, and Peter Stone. A Neural Network-Based Approach to Robot Motion Control. In Ubbo Visser, Fernando Ribeiro, Takeshi Ohashi, and Frank Dellaert, editors, RoboCup-2007: Robot Soccer World Cup XI, Lecture Notes in Artificial Intelligence, pp. 480–87, Springer Verlag, Berlin, 2008.

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Abstract

The joint controllers used in robots like the Sony Aibo are designed for the task of moving the joints of the robot to a given position. However, they are not well suited to the problem of making a robot move through a desired trajectory at speeds close to the physical capabilities of the robot, and in many cases, they cannot be bypassed easily. In this paper, we propose an approach that models both the robot's joints and its built-in controllers as a single system that is in turn controlled by a neural network. The neural network controls the entire trajectory of a robot instead of just its static position. We implement and evaluate our approach on a Sony Aibo ERS-7.

BibTeX

@incollection{LNAI2007-grasemann,
        author="Uli Grasemann and Daniel Stronger and Peter Stone",
        title="A Neural Network-Based Approach to Robot Motion Control",
        booktitle= "{R}obo{C}up-2007: Robot Soccer World Cup {XI}",
        Editor="Ubbo Visser and Fernando Ribeiro and Takeshi Ohashi
        and Frank Dellaert",
        Publisher="Springer Verlag",
        address="Berlin",
        year="2008",
        series="Lecture Notes in Artificial Intelligence",      
	volume="5001",
	pages="480--87",
        abstract="The joint controllers used in robots like the Sony
        Aibo are designed for the task of moving the joints of the
        robot to a given position. However, they are not well suited
        to the problem of making a robot move through a desired
        trajectory at speeds close to the physical capabilities of the
        robot, and in many cases, they cannot be bypassed easily.  In
        this paper, we propose an approach that models both the
        robot's joints and its built-in controllers as a single system
        that is in turn controlled by a neural network.  The neural
        network controls the entire trajectory of a robot instead of
        just its static position.  We implement and evaluate our
        approach on a Sony Aibo ERS-7.",
	wwnote = {Official version from <a href="http://dx.doi.org/10.1007/978-3-540-68847-1_51">Publisher's Webpage</a>&copy Springer-Verlag},
}

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