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A Rule-based Integration of Neural Network Modules based on Cellular Automata for Sensory-Motor Controller

센서-모터 제어기를 위한 셀룰라 오토마타 기반 신경망 모듈의 규칙기반 결합

  • 김경중 (연세대학교 검퓨터과학과) ;
  • 송금범 (연세대학교 검퓨터과학과) ;
  • 조성배 (연세대학교 검퓨터과학과)
  • Published : 2002.02.01

Abstract

There are some difficulties to construct a sensory-motor controller for an autonomous mobile robot such as coordinating the mechanics and control system parts of the robot, and managing interaction with external environments. In previous research, we evolve the CAM-Brain, neural networks based on cellular automata, to control an autonomous mobile robot. In this paper, we propose the method of combining multi-modules evolved to do simple behavior in order to making more sophisticated behaviors because the controller composed of one neural network module is difficult to make complex behaviors. In experimental results, we can get the controller adapting to more complex environments by combining CAM-Brain modules evolved to do simple behavior by rule-based approach.

자율이동로봇의 센서-모터 제어기를 구축하는데 있어 로봇의 기계적인 부분과 제어기 부분을 조화시키는 것이나 외부환경과 로봇의 상호작용을 처리하는 것 등이 가장 큰 문제점이다. 이러한 문제점들을 해결하기 위해서 진화적 접근방법이 많이 사용되고 있다. 이전 연구에서는 이러한 연구선상에서 셀룰라 오토마타 기반 신경망인 CAM-Brain을 이동로봇 제어기로 진화시켰다. 그러나, 하나의 모듈로 이루어진 제어기로는 복잡한 행동을 하도록 만들기 어렵기 때문에 본 논문에서는 하위 수준의 간단한 행동을 하도록 진화된 모듈들을 결합하여 보다 상위 수준의 복잡한 행동을 하도록 하는 다중 모듈 결합방법을 제안한다. 실험결과, 간단한 행동들을 하도록 진화된 CAM-Brain 모듈들을 규칙기반 방법으로 결합하여 주어진 좀더 환경에 적응할 수 있는 제어기를 얻을 수 있었다.

Keywords

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