A Neural Network-Based Approach to Robot Motion Control

  • Uli Grasemann
  • Daniel Stronger
  • Peter Stone
Conference paper

DOI: 10.1007/978-3-540-68847-1_51

Volume 5001 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Grasemann U., Stronger D., Stone P. (2008) A Neural Network-Based Approach to Robot Motion Control. In: Visser U., Ribeiro F., Ohashi T., Dellaert F. (eds) RoboCup 2007: Robot Soccer World Cup XI. RoboCup 2007. Lecture Notes in Computer Science, vol 5001. Springer, Berlin, Heidelberg

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Uli Grasemann
    • 1
  • Daniel Stronger
    • 1
  • Peter Stone
    • 1
  1. 1.Department of Computer SciencesUniversity of Texas at AustinAustinUSA