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The Navigation Control for Intelligent Robot Using Genetic Algorithms

유전알고리즘을 이용한 지능형 로봇의 주행 제어

  • 주영훈 (군산대학교 전자정보공학부) ;
  • 조상균 (군산대학교 전자정보공학부)
  • Published : 2005.08.01

Abstract

In this paper, we propose the navigation control method for intelligent robot using messy genetic algorithm. The fuzzy controller design for navigation of the intelligent robot was dependant on expert's knowledge. But, the parameters of the fuzzy logic controller obtained from expert's control action may not be outimal. In this paper, to solve the above problem, we propose the identification method to automatically tune the number of fuzzy rule and parameters of memberships of fuzzy controller using mGA. Finally, to show and evaluate the generality and feasibility of the proposed method, we provides some simulations for wall following navigation of intelligent robot.

본 논문에서는 유전 알고리즘의 한 방법인 mGA를 이용하여 지능형 로봇의 주행제어 방법을 제안한다. 지능형 로봇의 주행에 필요한 퍼지 제어기의 설계는 전문가적 지식에 많이 의존한다. 이러한 전문가의 경험에 의해 설정된 퍼지 제어기의 여러 구성 요소들의 매개 변수 값들이 최적의 값이라는 보장이 없다. 상기 문제를 해결하기 위해 본 논문에서는 퍼지 제어 기의 구성 요소인 퍼지 규칙의 수와 멤버쉽 함수의 매개 변수들을 mGA를 이용하여 동정하는 방법을 제안한다. 제안된 방법에 의해 동정된 매개 변수들의 정확성과 효율성을 평가하기 위하여 지능형 로봇의 벽면 주행에 대한 모의실험을 수행한다.

Keywords

References

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