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 implemented as a mobile software agent controls the robot corresponding to an objects, so that the object moves to the direction required by the ant agent. At this time, the process where an ant searches an object corresponds to some migrations of the ant agent, which are much more efficient than physically searching.
Also, the ACC uses a pheromone for making a cluster grown and stabilized. However, it is difficult to implement such a pheromone as an physical entity, because it can diffuse, mutually intensify its strength, and restrict its effect in its scope. In our approach, the pheromone is implemented as a mobile software agent as well as an ant. 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 strength as vector values, they can represent mutually intensifying 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 for centrally controlling robots. The new ACC approach decentralizes it, and makes a robot system free from special devices for checking locations.
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References
Kambayashi, Y., Takimoto, M.: Scheme implementation of the functional language for mobile agents with dynamic extension. In: Proceedings of IEEE International Conference on Intelligent Engineering Systems, pp. 151–156 (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, Los Alamitos (2009)
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)
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)
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)
Hulaas, G., Binder, W., Villazon, A.: Portable resource control in the j-seal2 mobile agent system. In: Proceedings of International Conference on Autonomous Agents, pp. 222–223 (2001)
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Mizutani, M., Takimoto, M., Kambayashi, Y. (2010). Ant Colony Clustering Using Mobile Agents as Ants and Pheromone. In: Nguyen, N.T., Le, M.T., Świątek, J. (eds) Intelligent Information and Database Systems. ACIIDS 2010. Lecture Notes in Computer Science(), vol 5990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12145-6_45
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DOI: https://doi.org/10.1007/978-3-642-12145-6_45
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