Abstract
We present a novel control scheme for robot swarms that exploits the computation layer of a blockchain to coordinate the actions of individual robots in real-time. To accomplish this, we deploy a blockchain smart contract that acts as a “decentralized supervisor” during a swarm foraging task. Our results show that using blockchain-based global coordination rules can improve the foraging behavior of robot swarms, while maintaining a decentralized, scalable, and democratic system in which every robot contributes homogeneously to the decision-making process.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Aswale, A., López, A., Ammartayakun, A., Pinciroli, C.: Hacking the colony: on the disruptive effect of misleading pheromone and how to defend against it. In: Proceedings of the 21st International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2022), pp. 27–34. International Foundation for Autonomous Agents and Multiagent Systems, Richland (2022)
Biesmeijer, J.C., de Vries, H.: Exploration and exploitation of food sources by social insect colonies: a revision of the scout-recruit concept. Behav. Ecol. Sociobiol. 49(2), 89–99 (2001). https://doi.org/10.1007/s002650000289
Buterin, V.: A next-generation smart contract and decentralized application platform. Technical report, Ethereum Foundation (2014). https://github.com/ethereum/wiki/wiki/White-Paper. Accessed 18 July 2019
Campo, A., et al.: Artificial pheromone for path selection by a foraging swarm of robots. Biol. Cybern. 103(5), 339–352 (2010). https://doi.org/10.1007/s00422-010-0402-x
Deneubourg, J.L., Aron, S., Goss, S., Pasteels, J.M.: The self-organizing exploratory pattern of the argentine ant. J. Insect Behav. 3(2), 159–168 (1990). https://doi.org/10.1007/BF01417909
Dorigo, M., Birattari, M., Brambilla, M.: Swarm robotics. Scholarpedia 9(1), 1463 (2014)
Ethereum Foundation: Ethereum project (2017). https://ethereum.org
Ethereum Foundation: ethereum/web3.py: A Python interface for interacting with the Ethereum blockchain and ecosystem (2022). https://github.com/ethereum/web3.py
Fernandes, M., Alexandre, L.A.: Robotchain: using tezos technology for robot event management. Ledger 4 (2019). https://doi.org/10.5195/ledger.2019.175. https://www.ledgerjournal.org/ojs/ledger/article/view/175
Font Llenas, A., Talamali, M.S., Xu, X., Marshall, J.A.R., Reina, A.: Quality-sensitive foraging by a robot swarm through virtual pheromone trails. In: Dorigo, M., Birattari, M., Blum, C., Christensen, A.L., Reina, A., Trianni, V. (eds.) ANTS 2018. LNCS, vol. 11172, pp. 135–149. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00533-7_11
Hasselmann, K., Parravicini, A., Pacheco, A., Strobel, V.: KenN7/argos-python: python wrapper for ARGoS3 simulator (2022). https://github.com/KenN7/argos-python
Hoff, N., Wood, R., Nagpal, R.: Distributed colony-level algorithm switching for robot swarm foraging. In: Martinoli, A., et al. (eds.) Distributed Autonomous Robotic Systems, vol. 83, pp. 417–430. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-32723-0_30
Houston, A.I., McNamara, J.M.: A general theory of central place foraging for single-prey loaders. Theor. Popul. Biol. 28(3), 233–262 (1985). https://doi.org/10.1016/0040-5809(85)90029-2
Merkel, D.: Docker: lightweight Linux containers for consistent development and deployment. Linux J. 2014(239) (2014)
Mondada, F., et al.: The e-puck, a robot designed for education in engineering. In: Gonçalves, P.J.S., Torres, P.J.D., Alves, C.M.O. (eds.) Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions, vol. 1, pp. 59–65. IPCB: Instituto Politécnico de Castelo Branco (2009)
Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system (2008). https://bitcoin.org/bitcoin.pdf
Nouyan, S., Groß, R., Bonani, M., Mondada, F., Dorigo, M.: Teamwork in self-organized robot colonies. IEEE Trans. Evol. Comput. 13(4), 695–711 (2009). https://doi.org/10.1109/TEVC.2008.2011746
Pacheco, A., Strobel, V.: teksander/geth-argos at ANTS2022. https://github.com/teksander/geth-argos
Pacheco, A., Strobel, V., Dorigo, M.: A blockchain-controlled physical robot swarm communicating via an ad-hoc network. In: Dorigo, M., et al. (eds.) ANTS 2020. LNCS, vol. 12421, pp. 3–15. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-60376-2_1
Pinciroli, C., et al.: ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intell. 6(4), 271–295 (2012). https://doi.org/10.1007/s11721-012-0072-5
Pitonakova, L., Crowder, R., Bullock, S.: Understanding the role of recruitment in collective robot foraging. In: Proceedings of the 14th International Conference on the Synthesis and Simulation of Living Systems (ALIFE 2014), pp. 264–271 (2014). https://doi.org/10.7551/978-0-262-32621-6-ch043
Pitonakova, L., Crowder, R., Bullock, S.: The information-cost-reward framework for understanding robot swarm foraging. Swarm Intell. 12(1), 71–96 (2017). https://doi.org/10.1007/s11721-017-0148-3
Reina, A.: Robot teams stay safe with blockchains. Nat. Mach. Intell. 2, 240–241 (2020). https://doi.org/10.1038/s42256-020-0178-1
Salman, M., Garzón Ramos, D., Hasselmann, K., Birattari, M.: Phormica: photochromic pheromone release and detection system for stigmergic coordination in robot swarms. Front. Robot. AI 7 (2020). https://www.frontiersin.org/article/10.3389/frobt.2020.591402
Seeley, T.D.: Division of labor between scouts and recruits in honeybee foraging. Behav. Ecol. Sociobiol. 12(3), 253–259 (1983). https://www.jstor.org/stable/4599586
Strobel, V., Castelló Ferrer, E., Dorigo, M.: Managing Byzantine robots via blockchain technology in a swarm robotics collective decision making scenario. In: Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS 2018), pp. 541–549. International Foundation for Autonomous Agents and Multiagent Systems, Richland (2018)
Strobel, V., Castelló Ferrer, E., Dorigo, M.: Blockchain technology secures robot swarms: a comparison of consensus protocols and their resilience to Byzantine robots. Front. Robot. AI 7, 54 (2020). https://doi.org/10.3389/frobt.2020.00054
Dorigo, M., Birattari, M., Blum, C., Christensen, A.L., Reina, A., Trianni, V. (eds.): ANTS 2018. LNCS, vol. 11172. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-00533-7
Szilágyi, P.: EIP 225: clique proof-of-authority consensus protocol (2017). https://github.com/ethereum/EIPs/issues/225. Accessed 10 May 2020
Wilson, E.O.: Sociobiology: The New Synthesis, Twenty-Fifth Anniversary Edition. Harvard University Press, Cambridge (2000)
Acknowledgements
This work was partially supported by the program of Concerted Research Actions (ARC) of the Université libre de Bruxelles and by the Brussels-Capital Region via the Brussels International contract n. BI-MB-531-004021. A. Reina and M. Dorigo acknowledge support from the Belgian F.R.S.-FNRS, of which they are Chargé de Recherches and Research Director, respectively.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Pacheco, A., Strobel, V., Reina, A., Dorigo, M. (2022). Real-Time Coordination of a Foraging Robot Swarm Using Blockchain Smart Contracts. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2022. Lecture Notes in Computer Science, vol 13491. Springer, Cham. https://doi.org/10.1007/978-3-031-20176-9_16
Download citation
DOI: https://doi.org/10.1007/978-3-031-20176-9_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-20175-2
Online ISBN: 978-3-031-20176-9
eBook Packages: Computer ScienceComputer Science (R0)