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http://dx.doi.org/10.5302/J.ICROS.2012.18.1.021

Energy Efficient Cooperative Foraging Swarm Robots Using Adaptive Behavioral Model  

Lee, Jong-Hyun (Sungkyunkwan University)
An, Jin-Ung (DGIST)
Ahn, Chang-Wook (Sungkyunkwan University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.18, no.1, 2012 , pp. 21-27 More about this Journal
Abstract
We can efficiently collect crops or minerals by operating multi-robot foraging. As foraging spaces become wider, control algorithms demand scalability and reliability. Swarm robotics is a state-of-the-art algorithm on wide foraging spaces due to its advantages, such as self-organization, robustness, and flexibility. However, high initial and operating costs are main barriers in performing multi-robot foraging system. In this paper, we propose a novel method to improve the energy efficiency of the system to reduce operating costs. The idea is to employ a new behavior model regarding role division in concert with the search space division.
Keywords
swarm intelligence; swarm robotics; cooperative swarm robots; foraging robots;
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1 N. Trawny, S. I. Roumeliotis, and G. B. Giannakis, "Cooperative multi-robot localization under communication constraints," International Conference on Robotics and Automation (ICRA'09), Kobe, Japan, pp. 4394-4400, 2009.
2 K. Lerman, "Mathematical model of foraging in a group of robots: Effect of interference," Autonomous Robots, vol. 13, no. 2, pp. 127-141, 2002.   DOI
3 J. Guerrero and G. Oliver, "Multi-robot task allocation strategies using auction-like mechanisms," Artificial Research and Development in Frontiers in Artificial Intelligence and Applications, pp. 111-122, 2003.
4 L. Li, A. Martinoli, and Y. Abu-Mostafa, "Learning and measuring specialization in collaborative swarm systems," Adaptive Behavior, special issue on Mathematics and Algorithms of Social Interactions, vol. 12, no. 3-4, pp. 199-212, 2004.
5 S. Garnier, J. Gautrais, and G. Theraulaz, "The biological principals of swarm intelligence," Swarm Intelligence, Springer Newyork, vol. 1, no. 1, pp. 3-31, 2007.   DOI   ScienceOn
6 D. H. Kim, "Self-organization for multi-agent groups," International Journal of Control, Automation and Systems, vol. 2, no. 3, pp. 333-342, Sep. 2004.
7 T. Balch and R. C. Arkin, "Behavior-based formation control for multirobot teams," IEEE Transactions on Robotics and Automation, vol. 14, pp. 926-939, Dec. 1998.   DOI
8 D. Lambrinos, R. Möller, T. Labhart, R. Pfeifer, and R. Wehner, "A mobile robot employing insect strategies for navigation," Robotics and Autonomous Systems, vol. 30, no. 1-2, pp. 39-64, 2000.   DOI
9 N. Lemmens and K. Tuyls, "Stigmergic landmark foraging," International conference on Autonomous Agents and Multi Agent Systems (AAMAS), 2009.
10 E. Bonabeau, M. Dorigo, and G. Theraulaz, Swarm Intelligence: from Natural to Artificial Systems, Oxford University Press, 1999.
11 Reynolds, "Flocks, herds, and schools: a distributed behavioral model," Computer Graphics, vol. 21, no. 4, pp. 25-34, 1987.   DOI
12 Alan F. T. Winfield, Foraging Robots, Springer, New York, pp. 3682-3700, 2009.
13 W. Liu, A. Winfield, J. Sa, J. Chen, and L. Dou, "Strategies for energy optimisation in a swarm of foraging robots," Second International Workshop, LNCS, vol. 4433, Springer, Heidelberg, 2006.
14 A. F. Winfield and O. E. Holland, "The application of wireless local area network technology to the control of mobile robots," Microprocessors and Microsystems, vol. 23, pp. 597-607, 2000.   DOI
15 G. Théraulaz, E. Bonabeau, and J.-L. Deneubourg, "Response threshold reinforcement and division of labour in insect societies," Biological Sciences, vol. 265, pp. 327-332, 1998.   DOI