Method of Constructing Autonomous Decentralized Systems Using Classifier Systems (Application to Gait Acquisition of 6-Legged Robot)

Yasuharu Yamada, Akio Ishiguro, Yoshiki Uchikawa

Research output: Contribution to journalArticle

Abstract

It is difficult to control large complex systems by centralized control. Therefore, autonomous decentralized systems which have variety, flexibility and fault tolerability, have been studied recently. In this paper, we propose an autonomous decentralized system comprised of classifier systems. Classifier systems are parallel, message-passing, rule-based systems that learn through credit assignment and rule discovery (the genetic algorithm). In our method, each subsystem is controlled by an individual classifier system, and it generates production rules autonomously by exchanging information with adjacent subsystems. We test the system on a 6-legged robot, in computer simulations, which learns how to coordinate its legs so as to walk forward, as a practical example.

Original languageEnglish
Pages (from-to)4245-4251
Number of pages7
Journaltransactions of the japan society of mechanical engineers series c
Volume60
Issue number580
DOIs
Publication statusPublished - 1994 Jan 1
Externally publishedYes

Keywords

  • 6-Legged Robot
  • Autonomous Decentralized System
  • Biomechanics
  • Classifier System
  • Gait Acquisition
  • Genetic Algorithm
  • Learning
  • Moving Robot

ASJC Scopus subject areas

  • Mechanics of Materials
  • Mechanical Engineering
  • Industrial and Manufacturing Engineering

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