Abstract
This paper focuses on the general problem of coordinating multiple robots. More specifically, it addresses the self-election of heterogeneous specialized tasks by autonomous robots, as opposed to the usual multi-tasks allocation problem in multi-robot systems in which an external controller distributes the existing tasks among the individual robots. In this work we are considering a specifically distributed or decentralized approach in which we are particularly interested on decentralized solution where the robots themselves autonomously and in an individual manner, are responsible of selecting a particular task so that all the existing tasks are optimally distributed and executed. In this regard, we have established an experimental scenario and we propose a solution through automata learning-based probabilistic algorithm, to solve the corresponding multi-tasks distribution problem. The paper ends with a critical discussion of experimental results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Farinelli, A., Locchi, L., Nardi, D.: Multirobot Systems: A Classification Focused on Coordination. IEEE Transactions on Systems, Man and Cybernetics, 2015–2028 (2004)
Gerkey, B., Mataric, M.: A formal analysis and taxonomy of task allocation in multi-robot systems. Intl. J. of Robotics Research, 939–954 (2004)
Price, R., Tiño, P.: Evaluation of Adaptive Nature Inspired Task Allocation Against Alternate Decentralised Multiagent Strategies. In: Yao, X., Burke, E.K., Lozano, J.A., Smith, J., Merelo-Guervós, J.J., Bullinaria, J.A., Rowe, J.E., Tiňo, P., Kabán, A., Schwefel, H.-P. (eds.) PPSN 2004. LNCS, vol. 3242, pp. 982–990. Springer, Heidelberg (2004)
Yang, Y., Zhou, C., Tian, Y.: Swarm Robots Task Allocation Based on Response Threshold Model. In: IEEE International Conference on Autonomous Robots and Agents, pp. 171–176 (2009)
Quiñonez, Y., De Lope, J., Maravall, D.: Bio-Inspired Decentralized Self-Coordination Algorithms for Multi-Heterogeneous Specialized Tasks Distribution in Multi-Robot Systems. In: Ferrández, J.M., Álvarez Sánchez, J.R., de la Paz, F., Toledo, F.J. (eds.) IWINAC 2011, Part I. LNCS, vol. 6686, pp. 30–39. Springer, Heidelberg (2011)
Dias, B., Stentz, A.: A Free Market Architecture for Distributed Control of a Multirobot System. In: 6th International Conference on Intelligent Autonomous Systems, pp. 115–122 (2000)
Dias, B.: Traderbots: A new Paradigm for Robust and Efficient Multirobot Coordination in Dynamics Environments. Ph.D. dissertation, Robotics Institute, Carnegie Mellon University, Pittsburgh (2004)
Jones, E., Browning, B., Dias, B., Argall, B., Veloso, M., Stentz, A.: Dynamically Formed Heterogeneous Robot Teams Performing Tightly-Coordinated Tasks. In: IEEE Conference on Robotics and Automation, pp. 570–575 (2006)
Song, T., Yan, X., Liang, A., Chen, K., Guan, H.: A Distributed Bidirectional Auction Algorithm for Multirobot Coordination. In: IEEE International Conference on Research Challenges in Computer Science, pp. 145–148 (2009)
Shiroma, P., Campos, M.: CoMutaR: A Framework for Multi-robot Coordination and Task Allocation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4817–4824 (2009)
Baglietto, M., Cannata, C., Capezio, F., Grosso, A., Sgorbissa, A.: A Multi-robot Coordination System Based on RFID Technology. In: IEEE International Conference on Advanced Robotics, pp. 1–6 (2009)
Huntsberger, T., Trebi-Ollennu, A., Aghazarian, H., Schenker, P.: Distributed Control of Multi-robot System Engaged in Tightly Coupled Tasks. Journal Autonomous Robots, 79–92 (2004)
Gerkey, B., Mataric, M.: Multi-Robot Task Allocation: Analyzing the Complexity and Optimality of Key Architectures. In: IEEE International Conference on Robotics and Automation, pp. 3862–3868 (2003)
Narendra, K., Thathachar, M.: Learning Automata: An Introduction. Prentice-Hall, Englewood Cliffs (1989)
Narendra, K., Thathachar, M.: Learning Automata: A Survey. IEEE Transactions on Systems, Man, and Cybernetics, 323–334 (1974)
Obaidat, M., Papadimitriou, G., Pomportsis, A.: Guest Editorial Learning Automata: Theory, Paradigms, and Applications. IEEE Transactions on Systems, Man, and Cybernetics–Part B: Cybernetics, 706–709 (2002)
Maravall, D., De Lope, J.: Fusion of Learning Automata Theory and Granular Inference Systems: ANLAGIS. Applications to Pattern Recognition and Machine Learning. Neurocomputing 74, 1237–1242 (2011)
Narendra, K., Wright, E., Mason, L.: Applications of Learning Automata to Telephone Traffic Routing and Control. IEEE Transactions on Systems, Man, and Cybernetics, 785–792 (1977)
Narendra, K., Viswanathan, R.: A Two-Level System of Schotastic Automata for Periodic Random Environments. IEEE Transactions on Systems, Man, and Cybernetics, 285–289 (1972)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Quiñonez, Y., Maravall, D., de Lope, J. (2011). Stochastic Learning Automata for Self-coordination in Heterogeneous Multi-Tasks Selection in Multi-Robot Systems. In: Batyrshin, I., Sidorov, G. (eds) Advances in Artificial Intelligence. MICAI 2011. Lecture Notes in Computer Science(), vol 7094. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25324-9_38
Download citation
DOI: https://doi.org/10.1007/978-3-642-25324-9_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25323-2
Online ISBN: 978-3-642-25324-9
eBook Packages: Computer ScienceComputer Science (R0)