Authors:
Munehiro Shintani
1
;
Shawn Lee
1
;
Munehiro Takimoto
1
and
Yasushi Kambayashi
2
Affiliations:
1
Tokyo University of Science, Japan
;
2
Nippon Institute of Technology, Japan
Keyword(s):
Mobile agent, Ant colony clustering, Intelligent robot control.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Soft Computing
;
Swarm/Collective Intelligence
Abstract:
This paper presents effective extensions of our previously proposed algorithm for controlling multiple robots. The robots are connected by communication networks, and the controlling algorithm is based on a specific Ant Colony Clustering (ACC) algorithm. Unlike traditional ACC, we implemented the ants as actual mobile software agents that control the mobile robots which are corresponding to objects. The ant agent migrates among robots to look for an available one. Once the ant agent finds an available robot, the robot physically moves along the instructions of the ant agent, instead of being conveyed. We also implemented pheromone as mobile software agents, which attract many robots to some clusters by diffusing themselves through the migration, so that the pheromone agents enable the robots to be efficiently assembled. In our new approach, we take advantage of the pheromone agents not only to assemble the robots but also to serialize them. The serializing property is desirable for p
articular applications such as gathering carts in the airports. We achieve the property through migrations of the pheromone agents within a cluster and synthesizing them. We have built a simulator based on our algorithm, and conducted numerical experiments to demonstrate the feasibility of our approach.
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