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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.8 No.3 pp.181-193
DOI :

Integrating Ant Colony Clustering Method to a Multi-Robot System Using Mobile Agents

Yasushi Kambayashi, 1Masataka Ugajin, 2Osamu Sato, 3Yasuhiro Tsujimura, 4Hidemi Yamachi, 5Munehiro Takimoto, 6Hisashi Yamamoto
Department of Computer and Information Engineering Nippon Institute of Technology 4-1 Gakuendai, Miyashiro-cho, Minamisaitama-gun Saitama, 345-8501, Japan
1Department of Computer and Information Engineering Nippon Institute of Technology 4-1 Gakuendai, Miyashiro-cho, Minamisaitama-gun Saitama, 345-8501, Japan

2Department of Computer and Information Engineering Nippon Institute of Technology 4-1 Gakuendai, Miyashiro-cho, Minamisaitama-gun Saitama, 345-8501, Japan

3Department of Computer and Information Engineering Nippon Institute of Technology 4-1 Gakuendai, Miyashiro-cho, Minamisaitama-gun Saitama, 345-8501, Japan

4Department of Computer and Information Engineering Nippon Institute of Technology 4-1 Gakuendai, Miyashiro-cho, Minamisaitama-gun Saitama, 345-8501, Japan

5Department of Information Sciences Tokyo University of Science 2641 Yamazaki, Noda, Chiba, 278-0022, Japan

6Faculty of System Design Tokyo Metropolitan University 6-6 Asahigaoka, Hino, Tokyo, 191-0065, Japan
Received Date, January 22, 2008; Received Date, August 7, 2009; Accepted Date, August 10, 2009 (Selected from APIEMS 2007)

Abstract

This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making “carts,” such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.

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