Behavior analysis of genetic fuzzy controller for an autonomous robot

Sung Bae Cho, Seung Ik Lee

Research output: Contribution to journalArticle

Abstract

To program an autonomous robot so that it acts reliably in a dynamic environment is a very hard task. Towards a promising approach to this problem, we have developed a genetic fuzzy controller for a mobile robot, and showed the possibility by applying it to a simulated robot called Khepera. The robot gets input from eight infrared sensors and operates two motors according to the fuzzy inference based on the sensory input. This paper attempts to analyze the adaptive behaviors of the controller by using automata, which indicates the emergence of several strategies to make the robot to navigate the complex space without bumping agains the walls and obstacles.

Original languageEnglish
Pages (from-to)578-591
Number of pages14
JournalControl and Cybernetics
Volume27
Issue number4
Publication statusPublished - 1998 Dec 1

Fingerprint

Autonomous Robots
Fuzzy Controller
Robot
Robots
Controllers
Adaptive Behavior
Infrared Sensor
Fuzzy Inference
Dynamic Environment
Mobile Robot
Automata
Fuzzy inference
Mobile robots
Controller
Infrared radiation
Sensors

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Modelling and Simulation
  • Applied Mathematics

Cite this

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Behavior analysis of genetic fuzzy controller for an autonomous robot. / Cho, Sung Bae; Lee, Seung Ik.

In: Control and Cybernetics, Vol. 27, No. 4, 01.12.1998, p. 578-591.

Research output: Contribution to journalArticle

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