Abstract
Task allocation in multi-robot teams is conventionally carried out using customized algorithms against individual distributions due to their NP-hard nature. The expanding range of autonomous multi-robot operations demands for a generic allocation scheme capable of working across a variety of problem distributions. This paper presents an intelligently crafted, novel, evolutionary algorithm based task allocation scheme capable of working across a range of multi-robot problem distributions. Qualitative analysis against exact optimal solutions and a state of the art auction based scheme verify the capabilities of the proposed algorithm.
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Gerkey, B.P., Matarić, M.J.: A formal analysis and taxonomy of task allocation in multi-robot systems. Int. J. Robot. Res. 23, 939–954 (2004)
Sen, S.D., Adams, J.A.: An influence diagram based multi-criteria decision making framework for multirobot coalition formation. Auton. Agent. Multi-Agent Syst. 29, 1061–1090 (2015)
Gerkey, B.P., Mataric, M.J.: Multi-robot task allocation: analyzing the complexity and optimality of key architectures. In: IEEE – ICRA, vol. 3, pp. 3862–3868 (2003)
Arif, M.U., Haider, S.: A flexible evolutionary algorithm for task allocation in multi-robot team. In: Nguyen, N.T., Pimenidis, E., Khan, Z., Trawiński, B. (eds.) ICCCI 2018. LNCS (LNAI), vol. 11056, pp. 89–99. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98446-9_9
Arif, M.U., Haider, S.: An evolutionary traveling salesman approach for multi-robot task allocation. In: 9th International Conference on Agents and Artificial Intelligence, pp. 567–574 (2017)
Koenig, S., et al.: The power of sequential single-item auctions for agent coordination. In: Proceedings of the National Conference on Artificial Intelligence. p. 1625. Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999 (2006)
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Arif, M.U. (2019). A Generic Evolutionary Algorithm for Efficient Multi-Robot Task Allocations. In: Meurs, MJ., Rudzicz, F. (eds) Advances in Artificial Intelligence. Canadian AI 2019. Lecture Notes in Computer Science(), vol 11489. Springer, Cham. https://doi.org/10.1007/978-3-030-18305-9_49
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DOI: https://doi.org/10.1007/978-3-030-18305-9_49
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