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. In traditional ACC, imaginary ants convey imaginary objects for classifying them based on some similarities, but in our algorithm, we implemented the ants as actual mobile software agents that control the mobile robots which are corresponding to objects. The ant agent as a software agent guides the mobile robot (object) to which direction it should move. In the previous approach, we implemented not only the ant but also the pheromone as mobile software agents to assemble the mobile robots with as little energy consumption as possible. 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 particular applications such as gathering carts in airports. We achieve the property by allowing each ant agent to alternatively receive a pheromone agent. We have built a simulator based on our algorithm, and conducted numerical experiments to demonstrate the feasibility of our approach. The experimental results show the effectiveness of our algorithm.
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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)
Mizutani, M., Takimoto, M., Kambayashi, Y.: Ant colony clustering using mobile agents as ants and pheromone. In: Nguyen, N.T., Le, M.T., Świątek, J. (eds.) ACIIDS 2010. LNCS, vol. 5990, pp. 435–444. Springer, Heidelberg (2010)
Oikawa, R., Mizutani, M., Takimoto, M., Kambayashi, Y.: Distributed ant colony clustering using mobile agents and its effects. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds.) KES 2010. LNCS, vol. 6276, pp. 198–208. Springer, Heidelberg (2010)
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, Los Alamitos (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)
Wang, 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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Shintani, M., Lee, S., Takimoto, M., Kambayashi, Y. (2011). A Serialization Algorithm for Mobile Robots Using Mobile Agents with Distributed Ant Colony Clustering. In: König, A., Dengel, A., Hinkelmann, K., Kise, K., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2011. Lecture Notes in Computer Science(), vol 6881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23851-2_27
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DOI: https://doi.org/10.1007/978-3-642-23851-2_27
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