Abstract
This paper presents a new approach for controlling mobile multiple robots connected by communication networks. The control mechanism is based on a specific Ant Colony Clustering (ACC) algorithm. In traditional ACC, an ant convey an object, but in our approach, the ant is implemented as a mobile software agent that controls the robot which is corresponding to an object, so that the object moves to the direction ordered by the ant agent. In this time, the process in which an ant searches an object corresponds to a sequence of migrations of the ant agent, which is much more efficient than the search by a mobile robot. In our approach, not only the ant but also the pheromone is implemented as a mobile software agent. The mobile software agents can migrate from one robot to another, so that they can diffuse over robots within their scopes. In addition, since they have their strengths as vector values, they can represent mutual intensification as synthesis of vectors. We have been developing elemental techniques for controlling multiple robots using mobile software agents, and showed effectiveness of applying them to the previous ACC approach which requires a host computer that centrally controls mobile robots. The new ACC approach decentralizes the mobile robot system, and makes the system free from special devices for checking locations.
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References
Deneubourg, J., Goss, S., Franks, N.R., Sendova-Franks, A.B., Detrain, C., Chreien, L.: The dynamics of collective sorting: Robot-like ant and ant-like robot. In: Proceedings of the First Conference on Simulation of Adaptive Behavior: From Animals to Animats, pp. 356–363. MIT Press, Cambridge (1991)
Kambayashi, Y., Ugajin, M., Sato, O., Tsujimura, Y., Yamachi, H., Takimoto, M., Yamamoto, H.: Integrating ant colony clustering to a multi-robot system using mobile agents. Industrial Engineering and Management Systems 8(3), 181–193 (2009)
Kambayashi, Y., Takimoto, M.: Higher-order mobile agents for controlling intelligent robots. International Journal of Intelligent Information Technologies 1(2), 28–42 (2005)
Takimoto, M., Mizuno, M., Kurio, M., Kambayashi, Y.: Saving energy consumption of multi-robots using higher-order mobile agents. In: Nguyen, N.T., Grzech, A., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2007. LNCS (LNAI), vol. 4496, pp. 549–558. Springer, Heidelberg (2007)
Nagata, T., Takimoto, M., Kambayashi, Y.: Suppressing the total costs of executing tasks using mobile agents. In: Proceedings of the 42nd Hawaii International Conference on System Sciences. IEEE Computer Society CD-ROM (2009)
Dorigo, M., Birattari, M., Stützle, T.: Ant colony optimization–artificial ants as a computational intelligence technique. IEEE Computational Intelligence Magazine 1(4), 28–39 (2006)
Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman. IEEE Transaction on Evolutionary Computation 1(1), 53–66 (1996)
Wand, T., Zhang, H.: Collective sorting with multi-robot. In: Proceedings of the First IEEE International Conference on Robotics and Biomimetics, pp. 716–720 (2004)
Lumer, E.D., Faiesta, B.: Diversity and adaptation in populations of clustering ants, from animals to animats 3. In: Proceedings of the 3rd International Conference on the Simulation of Adaptive Behavior, pp. 501–508. MIT Press, Cambridge (1994)
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Oikawa, R., Mizutani, M., Takimoto, M., Kambayashi, Y. (2010). Distributed Ant Colony Clustering Using Mobile Agents and Its Effects. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15387-7_24
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DOI: https://doi.org/10.1007/978-3-642-15387-7_24
Publisher Name: Springer, Berlin, Heidelberg
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