An ART-based fuzzy controller for the adaptive navigation of a quadruped robot

Xuedong Chen, Keigo Watanabe, Kazuo Kiguchi, Kiyotaka Izumi

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)


An adaptive-resonance theory (ART)-based fuzzy controller is presented for the adaptive navigation of a quadruped robot in cluttered environments, by incorporating the capability of ART in stable category recognition into fuzzy-logic control for selecting the adequate rule base. The environment category and the navigation mechanism are first described for the quadruped robot. The ART-based fuzzy controller, including an ART-based environment recognizer, a comparer, combined rule bases, and a fuzzy inferring mechanism, is next introduced for the purpose of the adaptive navigation of the quadruped robot. Unlike classical/conventional adaptive-fuzzy controllers, the present adaptive-control scheme is implemented by the adaptive selection of fuzzy-rule base in response to changes of the robot environment, which can be categorized and recognized by the proposed environment recognizer. The results of simulation and experiment show that the adaptive-fuzzy controller is effective.

Original languageEnglish
Pages (from-to)318-328
Number of pages11
JournalIEEE/ASME Transactions on Mechatronics
Issue number3
Publication statusPublished - Sept 2002
Externally publishedYes


  • Adaptive control
  • Adaptive-resonance theory (ART)
  • Fuzzy controller
  • Navigation
  • Obstacle avoidance
  • Quadruped robot

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering


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