Abstract
One of the challenges in developing multi-robot systems is the design of appropriate coordination strategies in such a way that robots perform their operations efficiently. In particular, efficient coordination requires judicious task allocation. Without appropriate task allocation, the use of multi-robot systems in complex scenarios becomes limited or even unfeasible. Real-world scenarios usually require the use of heterogeneous robots and task fulfillment with different structures, constraints, and degrees of complexity. In such scenarios, decentralised solutions seem to be appropriate for task allocation, since centralised solutions represent a single point of failure for the system. During the allocation process, in decentralised approaches, there are often communication requirements, as participants need to share information. Maintaining data integrity, resilience, and security in data access are some of the important features for this type of solution. In that direction, we propose an architecture for dynamic and decentralised allocation of tasks built on the idea of having communication and coordination in a multi-agent system through a private blockchain.
T. L. Basegio—Partly supported by Federal Institute of Rio Grande do Sul (IFRS) – Campus Feliz.
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References
Basegio, T.L., Bordini, R.H.: An algorithm for allocating structured tasks in multi-robot scenarios. In: Jezic, G., Kusek, M., Chen-Burger, Y.-H.J., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2017. SIST, vol. 74, pp. 99–109. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-59394-4_10
Bogner, A., Chanson, M., Meeuw, A.: A decentralised sharing app running a smart contract on the ethereum blockchain. In: Proceedings of the 6th International Conference on the Internet of Things, pp. 177–178 (2016)
Das, G.P., McGinnity, T.M., Coleman, S.A.: Simultaneous allocations of multiple tightly-coupled multi-robot tasks to coalitions of heterogeneous robots. In: 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 1198–1204 (2014)
Dias, M.B., Zlot, R., Kalra, N., Stentz, A.: Market-based multirobot coordination: a survey and analysis. Proc. IEEE 94(7), 1257–1270 (2006)
Ferrer, E.: The blockchain: a new framework for robotic swarm systems (2016). https://arxiv.org/pdf/1608.00695.pdf
Gerkey, B., Mataric, M.: A formal analysis and taxonomy of task allocation in multi-robot systems. Int. J. Robot. Res. 23(9), 939–954 (2004)
Gernert, B., Schildt, S., Wolf, L., Zeise, B., Fritsche, P., Wagner, B., Fiosins, M., Manesh, R.S., Müller, J.P.: An interdisciplinary approach to autonomous team-based exploration in disaster scenarios. In: 2014 IEEE International Symposium on Safety, Security, and Rescue Robotics, pp. 1–8, October 2014
Gunn, T., Anderson, J.: Effective task allocation for evolving multi-robot teams in dangerous environments. In: 2013 IEEE/WIC/ACM International Joint Conference on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), vol. 2, pp. 231–238 (2013)
Hardjono, T., Smith, N.: Cloud-based commissioning of constrained devices using permissioned blockchains. In: Proceedings of the 2nd ACM International Workshop on IoT Privacy, Trust, and Security, pp. 29–36 (2016)
Lee, B., Lee, J.: Blockchain-based secure firmware update for embedded devices in an Internet of Things environment. J. Supercomput. 73, 1–16 (2016)
Luo, L., Chakraborty, N., Sycara, K.: Provably-good distributed algorithm for constrained multi-robot task assignment for grouped tasks. IEEE Trans. Robot. 31(1), 19–30 (2015)
Murphy, R.R.: Disaster Robotics. The MIT Press, Cambridge (2014)
Murphy, R.R., et al.: Search and Rescue Robotics. In: Siciliano, B., Khatib, O. (eds.) Springer Handbook of Robotics. Springer, Berlin, Heidelberg (2008). https://doi.org/10.1007/978-3-540-30301-5_51
Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system (2008). https://bitcoin.org/bitcoin.pdf
Ramchurn, S.D., Huynh, T.D., Ikuno, Y., Flann, J., Wu, F., Moreau, L., Jennings, N.R., Fischer, J.E., Jiang, W., Rodden, T., Simpson, E., Reece, S., Roberts, S.J.: HAC-ER: A disaster response system based on human-agent collectives. In: International Conference on Autonumous Agents and Multiagent Systems, AAMAS 2015, pp. 533–541. International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC (2015)
Rao, A.S., Georgeff, M.P.: BDI agents: from theory to practice. In: Proceedings of the International Conference on Multi-Agent Systems (ICMAS 1995), pp. 312–319 (1995)
Scerri, P., Kannan, B., Velagapudi, P., Macarthur, K., Stone, P., Taylor, M., Dolan, J., Farinelli, A., Chapman, A., Dias, B., Kantor, G.: Flood disaster mitigation: a real-world challenge problem for multi-agent unmanned surface vehicles. In: Dechesne, F., Hattori, H., ter Mors, A., Such, J.M., Weyns, D., Dignum, F. (eds.) AAMAS 2011. LNCS (LNAI), vol. 7068, pp. 252–269. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-27216-5_16
Sleiman, M.D., Lauf, A.P., Yampolskiy, R.: Bitcoin message: data insertion on a proof-of-work cryptocurrency system. In: 2015 International Conference on Cyberworlds (CW), pp. 332–336 (2015)
Settimi, A., Pallottino, L.: A subgradient based algorithm for distributed task assignment for heterogeneous mobile robots. In: 52nd IEEE Conference on Decision and Control, pp. 3665–3670 (2013)
Urakawa, K., Sugawara, T.: Task allocation method combining reorganization of agent networks and resource estimation in unknown environments. In: 2013 Third International Conference on Innovative Computing Technology (INTECH), pp. 383–388 (2013)
Yan, Z., Jouandeau, N., Cherif, A.A.: A survey and analysis of multi-robot coordination. Int. J. Adv. Robot. Syst. 10, p. 399 (2013)
Zlot, R.M.: An auction-based approach to complex task allocation for multirobot teams. Ph.D. thesis. Robotics Institute, Carnegie Mellon University, 5000 Forbes Ave (2006)
Watanabe, H., Fujimura, S., Nakadaira, A., Miyazaki, Y., Akutsu, A., Kishigami, J.: Blockchain contract: securing a blockchain applied to smart contracts. In: 2016 IEEE International Conference on Consumer Electronics (ICCE), pp. 467–468 (2016)
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Basegio, T.L., Michelin, R.A., Zorzo, A.F., Bordini, R.H. (2018). A Decentralised Approach to Task Allocation Using Blockchain. In: El Fallah-Seghrouchni, A., Ricci, A., Son, T. (eds) Engineering Multi-Agent Systems. EMAS 2017. Lecture Notes in Computer Science(), vol 10738. Springer, Cham. https://doi.org/10.1007/978-3-319-91899-0_5
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