Abstract
Robot foraging, a frequently used test application for collective robotics, consists in a group of robots retrieving a set of opportunely defined objects to a target location. A commonly observed experimental result is that the retrieving efficiency of the group of robots, measured for example as the number of units retrieved by a robot in a given time interval, tends to decrease with increasing group sizes. In this paper we describe a biology inspired method for tuning the number of foraging robots in order to improve the group efficiency. As a result of our experiments, in which robots use only locally available information and do not communicate with each other, we observe self-organised task allocation. This task allocation is effective in exploiting mechanical differences among the robots inducing specialisation in the robots activities.
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References
W. Agassounon and A. Martinoli. Efficiency and robustness of thresholdbased distributed allocation algorithms in multi-agent systems. In C. Castelfranchi and W.L. Johnson, editors, Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-02), pages 1090–1097. ACM Press, New York, NY, USA, 2002.
T. Balch. The impact of diversity on performance in multi-robot foraging. In O. Etzioni, J.P. Müller, and J.M. Bradshaw, editors, Proceedings of the Third International Conference on Autonomous Agents (Agents’99), pages 92–99. ACM Press, New York, NY, USA, 1999.
T. Balch and R.C. Arkin. Communication in reactive multiagent robotic systems. Autonomous Robots, 1(1):27–52, 1994.
E. Bonabeau, M. Dorigo, and G. Theraulaz. Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press, New York, USA, 1999.0
E. Bonabeau, G. Theraulaz, and J.-L. Deneubourg. Quantitative study of the fixed threshold model for the regulation of division of labor in insect societies. Proceedings of the Royal Society of London, Series B-Biological Sciences, 263:1565–1569, 1996.
S. Camazine, J.-L. Deneubourg, N.R. Pranks, J. Sneyd, G. Theraulaz, and E. Bonabeau. Self-Organisation in Biological Systems. Princeton University Press, Princeton, NJ, USA, 2001.
Y.U. Cao, A.S. Fukunaga, and A.B. Kahng. Cooperative mobile robotics: Antecedents and directions. Autonomous Robots, 4(1):7–27, 1997.
J.-L. Deneubourg, S. Goss, J.M. Pasteels, D. Fresneau, and J.-P. Lachaud. Self-organization mechanisms in ant societies (II): Learning in foraging and division of labor. In J.M. Pasteels and J.-L. Deneubourg, editors, From Individual to Collective Behavior in Social Insects, volume 54 of Experientia Supplementum, pages 177–196. Birkhäuser Verlag, Basel, Switzerland, 1987.
M. Dorigo, E. Bonabeau, and G. Theraulaz. Ant algorithms and stigmergy. Future Generation Computer Systems, 16(8):851–871, 2000.
B.P. Gerkey and M.J. Matarić. A framework for studying multi-robot task allocation. In A.C. Schultz, L.E. Parker, and F.E. Schneider, editors, Multi-Robot Systems, pages 15–26. Kluwer Academic Publishers, Dordrecht, The Netherlands, 2003.
D. Goldberg and M.J. Matarić. Interference as a tool for designing and evaluating multi-robot controllers. In Proceedings of the 14th National Conference on Artificial Intelligence (AAAI-97), pages 637–642. MIT Press, Cambridge, MA, USA, 1997.
P. P. Grassé. La reconstruction du nid et les coordinations inter-individuelles chez Bellicositermes natalensis et Cubitermes. La théorie de la stigmergie: essai d’interpretation des termites constructeurs. Insectes Sociaux, 6:41–83, 1959.
M.J.B. Krieger and J.-B. Billeter. The call of duty: Self-organised task allocation in a population of up to twelve mobile robots. Robotics and Autonomous Systems, 30(1–2):65–84, 2000.
T.H. Labella, M. Dorigo, and J.-L. Deneubourg. Efficiency and task allocation in prey retrieval. In A.J. Ijspeert, D. Mange, M. Murata, and S. Nishio, editors, Proceedings of the First International Workshop on Biologically Inspired Approaches to Advanced Information Technology (Bio-ADIT2004), Lecture Notes in Computer Science, pages 32–47. Springer Verlag, Heidelberg, Germany, 2004.
M. Schneider-Fontán and M.J. Matarić. A study of territoriality: The role of critical mass in adaptive task division. In P. Maes, M.J. Matarić, J.-A. Meyer, J. Pollack, and S.W. Wilson, editors, From Animals to Animats 4, Fourth International Conference on Simulation of Adaptive Behavior (SAB-96), pages 553–561. MIT Press/Bradford Books, Cambridge, MA, USA, 1996.
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Labella, T.H., Dorigo, M., Deneubourg, JL. (2007). Self-Organised Task Allocation in a Group of Robots. In: Alami, R., Chatila, R., Asama, H. (eds) Distributed Autonomous Robotic Systems 6. Springer, Tokyo. https://doi.org/10.1007/978-4-431-35873-2_38
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DOI: https://doi.org/10.1007/978-4-431-35873-2_38
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-35869-5
Online ISBN: 978-4-431-35873-2
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