Integrating Ant Colony Clustering Method to a Multi-Robot System Using Mobile Agents
This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making "carts," such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.
- Ugajin, M., Sato, O., Tsujimura,Y., Yamamoto, H., Takimoto, M., and Kambayashi, Y. (2007), Integrating Ant Colony Clustering Method to Multi-Robots Using Mobile Agents, Proceedings of the Eigth Asia Pacific Industrial Engineering and Management System, CD-ROM
- Wang T. and Zhang, H. (2004). Collective Sorting with Multi-Robot, Proceedings of the First IEEE International Conference on Robotics and Biomimetics, 716-720
- Satoh, I. (1999), A Mobile Agent-Based Framework for Active Networks, Proceedings of IEEE System, Man and Cybernetics Conference, 71-76
- Becker M. and Szczerbicka, H. (2005), Parameters Influencing the Performance of Ant Algorithm Applied to Optimisation of Buffer Size in Manufacturing, Industrial Engineering and Management Systems, 4(2), 184-191
- Chen, L., Xu, X., and Chen, Y. (2004), An adaptive ant colony clustering algorithm, Proceedings of the Third IEEE International Conference on Machine Learning and Cybernetics, 1387-1392
- Dorigo, M. and Gambardella, L. M. (1996), Ant Colony System: a Cooperative Learning Approach to the Traveling Salesman, IEEE Transaction on Evolutionary Computation, 1(1), 53-66
- Sato, O., Ugajin, M., Tsujimura, Y., Yamamoto, H., and Kambayashi, Y. (2007), Analysis of the Behaviors of Multi-Robots that Implement Ant Colony Clustering Using Mobile Agents, Proceedings of the Eigth Asia Pacific Industrial Engineering and Management System, CD-ROM
- Deneuburg, J., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C. and Chretien, L. (1991). The Dynamics of Collective Sorting: Robot-Like Ant and Ant-Like Robot, Proceedings of First Conference on Simulation of Adaptive Behavior: From Animals to Animats, MIT Press, 356-363
- Kambayashi, Y., Tsujimura, Y., Yamachi, H., Takimoto M., and Yamamoto, H. (2009b), Design of a Multi-Robot System Using Mobile Agents with Ant Colony Clustering, Proceedings of Hawaii International Conference on System Sciences, IEEE Computer Society, CD-ROM
- Nagata, T., Takimoto, M., and Kambayashi, Y. (2009), Suppressing the Total Costs of Executing Tasks Using Mobile Agents, Proceedings of the 42nd Hawaii International Conference on System Sciences, IEEE Computer Society, CD-ROM
- Lumer, E. D. and Faieta, B. (1994), Diversity and Adaptation in Populations of Clustering Ants, From Animals to Animats 3: Proceedings of the 3rd International Conference on the Simulation of Adaptive Behavior, MIT Press, 501-508
- Kambayashi, Y. and Takimoto, M. (2005), Higher-Order Mobile Agents for Controlling Intelligent Robots, International Journal of Intelligent Information Technologies, 1(2), 28-42
- Evolution Robotics Ltd. Homepage (2008), http://www. evolution.com/
- Kambayashi, Y., Sato O., Harada, Y., and Takimoto, M., (2009a), Design of an Intelligent Cart System for Common Airports, Proceedings of 13th International Symposium on Consumer Electronics, CDROM
- Takimoto, M., Mizuno, M., Kurio, M., and Kambayashi, Y. (2007), Saving Energy Consumption of Multi-Robots Using Higher-Order Mobile Agents, Proceedings of the First KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications, Lecture Notes in Artificial Intelligence 4496, Springer-Verlag, 549-558
- Toyoda, Y. and Yano, F. (2004). Optimizing Movement of a Multi-Joint Robot Arm with Existence of Obstracles Using Multi-Purpose Genetic Algorithm, Industrial Engineering and Management Systems, 3(1), 78-84
- Binder, W. J. and Villazon, G. H. (2001), Portable Resource Control in the J-Seal 2 Mobile Agent System, Proceedings of International Conference on Autonomous Agents, 222-223
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