Generation of fuzzy rules and DNA coding method for cooperative behavior of Autonomouse Mobile Robots(AMRs)

Jang Hyun Kim, Jin Bae Park, Hyun Seok Yang, Yong Pil Park

Research output: Contribution to journalConference article

Abstract

Complex "lifelike" behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, "flocking" and "arrangement" of multiple autonomouse mobile robots were represented by a small number of fuzzy rules by Subtractive clustering algorithm and DNA coding method. Fuzzy rules in Sugeno type and their related parameters were automatically generated from clustering input-output data obtained from the algorithms for the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.

Original languageEnglish
Article number60423J
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume6042 II
DOIs
Publication statusPublished - 2005 Dec 1
EventICMIT 2005: Control Systems and Robotics - Chongging, China
Duration: 2005 Sep 202005 Sep 23

Fingerprint

Cooperative Behavior
Fuzzy rules
Fuzzy Rules
robots
Mobile Robot
Mobile robots
coding
DNA
deoxyribonucleic acid
Coding
group dynamics
Flocking
Artificial Life
Local Interaction
Clustering algorithms
Clustering Algorithm
Arrangement
Clustering
intelligence
Output

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Cite this

@article{015ab7c50a524203b3197060a6b7f36e,
title = "Generation of fuzzy rules and DNA coding method for cooperative behavior of Autonomouse Mobile Robots(AMRs)",
abstract = "Complex {"}lifelike{"} behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, {"}flocking{"} and {"}arrangement{"} of multiple autonomouse mobile robots were represented by a small number of fuzzy rules by Subtractive clustering algorithm and DNA coding method. Fuzzy rules in Sugeno type and their related parameters were automatically generated from clustering input-output data obtained from the algorithms for the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.",
author = "Kim, {Jang Hyun} and Park, {Jin Bae} and Yang, {Hyun Seok} and Park, {Yong Pil}",
year = "2005",
month = "12",
day = "1",
doi = "10.1117/12.664708",
language = "English",
volume = "6042 II",
journal = "Proceedings of SPIE - The International Society for Optical Engineering",
issn = "0277-786X",
publisher = "SPIE",

}

TY - JOUR

T1 - Generation of fuzzy rules and DNA coding method for cooperative behavior of Autonomouse Mobile Robots(AMRs)

AU - Kim, Jang Hyun

AU - Park, Jin Bae

AU - Yang, Hyun Seok

AU - Park, Yong Pil

PY - 2005/12/1

Y1 - 2005/12/1

N2 - Complex "lifelike" behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, "flocking" and "arrangement" of multiple autonomouse mobile robots were represented by a small number of fuzzy rules by Subtractive clustering algorithm and DNA coding method. Fuzzy rules in Sugeno type and their related parameters were automatically generated from clustering input-output data obtained from the algorithms for the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.

AB - Complex "lifelike" behaviors are composed of local interactions of individuals under fundamental rules of artificial life. In this paper, fundamental rules for cooperative group behaviors, "flocking" and "arrangement" of multiple autonomouse mobile robots were represented by a small number of fuzzy rules by Subtractive clustering algorithm and DNA coding method. Fuzzy rules in Sugeno type and their related parameters were automatically generated from clustering input-output data obtained from the algorithms for the group behaviors. Simulations demonstrate the fuzzy rules successfully realize group intelligence of mobile robots.

UR - http://www.scopus.com/inward/record.url?scp=33644938798&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33644938798&partnerID=8YFLogxK

U2 - 10.1117/12.664708

DO - 10.1117/12.664708

M3 - Conference article

VL - 6042 II

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

SN - 0277-786X

M1 - 60423J

ER -