Proceedings of the IEEK Conference (대한전자공학회:학술대회논문집)

The Institute of Electronics and Information Engineers (대한전자공학회)
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Obstacle Avoidance Using Modified Hopfield Neural Network for Multiple Robots

  • Ritthipravat, Panrasee (Center of Operation for Field Robotics Development(FIBO), King Mongkut′s University of Technology Thonburi) ;
  • Maneewarn, Thavida (Center of Operation for Field Robotics Development(FIBO), King Mongkut′s University of Technology Thonburi) ;
  • Laowattana, Djitt (Center of Operation for Field Robotics Development(FIBO), King Mongkut′s University of Technology Thonburi) ;
  • Nakayama, Kenji (Dept. of Information and System Engineering, Faculty of Engineering, Kanazawa University)
  • Published : 2002.07.01
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Abstract

In this paper, dynamic path planning of two mobile robots using a modified Hopfield neural network is studied. An area which excludes obstacles and allows gradually changing of activation level of neurons is derived in each step. Next moving step can be determined by searching the next highest activated neuron. By learning repeatedly, the steps will be generated from starting to goal points. A path will be constructed from these steps. Simulation showed the constructed paths of two mobile robots, which are moving across each other to their goals.

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