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Vol: 61(75) No: 1 / March 2016 Abstraction of the Laser Scanner Measurements for Mobile Robot Navigation Oikawa Ryotaro Department of Information Sciences, Tokyo University of Science, 2641 Yamazaki, Noda 278-8510, Japan, e-mail: oikawa@cs.is.noda.tus.ac.jp Munehiro Takimoto Department of Information Sciences, Tokyo University of Science , 2641 Yamazaki, Noda 278-8510, Japan, e-mail: mune@cs.is.noda.tus.ac.jp Yasushi Kambayashi Department of Computer and Information Engineering, Nippon Institute of Technology, 4-1 Gakuendai, Miyashiro-machi, Minamisaitama-gun 345-8501, Japan, e-mail: yasushi@nit.ac.jp Keywords: mobile agent, formation control, multiple robots, swarm intelligence Abstract This paper presents a new distributed control algorithm for composing specific formations of swarm robots. The swarm robots are expected to compose formations that represent certain symbols. We previously proposed a decentralized formation control algorithm for robots that were connected by communication networks and did not have any control program to compose the symbols. Control programs that implement our algorithm are introduced later from outside as mobile software agents, which are able to migrate from one robot to another robot through the network. Our control algorithm is based on the indirect pheromone communication of social insects such as ants. We have implemented the ant and the pheromone as mobile software agents. Ant agents control the robots and generate pheromone agents to control other ant agents. In this paper, we propose an approach considering the time lag that pheromone agents cause. When an ant agent receives a pheromone agent, the ant agent that generated that pheromone agent may have moved because of the time lag. Thus the pheromone agent may misguide the other attracted ant agents. In this new approach, the attracted ant agent predicts the location of attracting ant agent and migrates or drives a robot to the predicted location that is revised by the prediction. We have implemented a simulator based on our new algorithm, and conducted numerical experiments to demonstrate the feasibility of our new approach. We have shown that our new approach saves total mileages of moving robots in over 10 percent compared with our previous approach. References [12] T. Nagata, M. Takimoto, and Y. Kambayashi, “Suppressing the total costs of executing tasks using mobile agents,” in System Sciences, 2009. (HICSS ’09). 42nd Hawaii International Conference on, Jan 2009, pp. 1–10. [13] T. Abe, M. Takimoto, and Y. Kambayashi, “Searching targets using mobile agents in a large scale multi-robot environment,” in Proceedings of the first KES International Symposium on Agent and Multi-Agent Systems (KES-AMSTA 2011), ser. 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