Abstract
Swarm robotics is an innovative field that utilizes collective behavior principles to design systems where multiple robots coordinate through simple rules and interactions. It faces the challenges of decentralized governance, security, and scalability. Due to its decentralized optimization capabilities, Particle Swarm Optimization (PSO) has shown promise for controlling robot swarms. However, implementing PSO in a distributed manner still poses problems in achieving full scalability and fault-tolerant operation. Blockchain, a decentralized system that securely stores and distributes data, enables transparent and autonomous communication among robots. Integrating blockchain with PSO can potentially revolutionize swarm robotics by providing secure and decentralized coordination through Decentralized applications (Dapps). The work proposed here demonstrates the application of blockchain technology, utilizing ad-hoc techniques, to manage a swarm of robots in conjunction with particle swarm optimization for solving navigation paths. In particular, the emergent Tendermint platform is exploited as a lean blockchain infrastructure for supporting asynchronous swarm robotics applications by showing its main advantages compared to a more traditional blockchain platform.
This is a preview of subscription content, log in via an institution to check access.
References
Khaldi, B., Cherif, F.: An overview of swarm robotics: swarm intelligence applied to multi-robotics. Int. J. Comput. Appl. 3–10 (2015)
Spezzano, G. (ed.): Swarm Robotics, Applied Sciences. MPDI Books, Basel (2019)
Castro, M., Liskov, B.: Practical Byzantine fault tolerance and proactive recovery. ACM Trans. Comput. Syst. (TOCS) 20(4), 398–461 (2002)
Castelló, F.E.: The blockchain: a new framework for robotic swarm systems. arXiv (2016). http://arxiv.org/abs/1608.00695
Lopes, V., Alexandre, L.: An overview of blockchain integration with robotics and artificial intelligence. Ledger J. 4, 1–6 (2019)
Cai, W., Wang, Z., Ernst, J.B., Hong, Z., Feng, C., Leung, V.C.M.: Decentralized applications: the blockchain-empowered software system. IEEE Access 6, 53019–53033 (2018). https://doi.org/10.1109/ACCESS.2018.2870644
Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN 1995 - International Conference on Neural Networks, vol. 4, pp. 1942–1948 (1995). https://doi.org/10.1109/ICNN.1995.488968
Senanayake, M., Senthooran, I., Barca, J.C., Chung, H., Kamruzzaman, J., Murshed, M.: Search and tracking algorithms for swarms of robots: a survey. Robot. Auton. Syst. 75, 422–434 (2016)
Hereford, J.M., Siebold, M., Nichols, S.: Using the particle swarm optimization algorithm for robotic search applications. In: 2007 IEEE Swarm Intelligence Symposium, pp. 53–59 (2007). https://doi.org/10.1109/SIS.2007.368026
Gazi, V., Ordonez, R.: Particle swarm optimization based distributed agreement in multi-agent dynamic systems. In: IEEE Symposium on Swarm Intelligence, Orlando, FL, USA, pp. 1–7 (2014). https://doi.org/10.1109/SIS.2014.7011792
Adeoti, T., Olasoji, Y.: Control and path planning of mobile swarm robots using blockchain technology with particle swarm optimization. Eur. J. Electr. Eng. Comput. Sci. 6, 51–60 (2022). https://doi.org/10.24018/ejece.2022.6.4.456
Braithwaite, S., et al.: A tendermint light client. arXiv preprint arXiv:2010.07031 (2020)
Nakamoto, S.: Bitcoin: a peer-to-peer electronic cash system. Cryptography Mailing (2009). https://metzdowd.com
Ethan Buchman: Tendermint: Byzantine fault tolerance in the age of blockchains. Ph.D. thesis (2016). https://atrium.lib.uoguelph.ca/xmlui/handle/10214/9769
Vranken, H.: Sustainability of Bitcoin and blockchains. Curr. Opin. Environ. Sustain. 28, 1–9 (2017)
Castro, M., Liskov, B., et al.: Practical Byzantine fault tolerance. In: Proceedings of the Third Symposium on Operating Systems Design and Implementation (1999)
Heppner, F.: A stochastic nonlinear model for coordinated bird flocks. The ubiquity of chaos (1990)
Docker. https://www.docker.io
Tendermint Core 0.32.3. https://github.com/zlyzol/tendermint-0.32.3.git
Java OpenJDK. https://jdk.java.net/archive/
Acknowledgements
This work has been partially supported by European Union - NextGenerationEU - National Recovery and Resilience Plan (Piano Nazionale di Ripresa e Resilienza, PNRR) - Project: “SoBigData.it - Strengthening the Italian RI for Social Mining and Big Data Analytics” - Prot. IR0000013 - Avviso n. 3264 del 28/12/2021 and by the Italy-CNR, “Le Scienze per le TRansizioni Industriale, Verde ed Energetica”: Towards Sustainable Cognitive Buildings (ToSCoB) project.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Cicirelli, F., Greco, E., Guerrieri, A., Gentile, A.F., Spezzano, G., Vinci, A. (2024). Blockchain-Empowered PSO for Scalable Swarm Robotics. In: Villani, M., Cagnoni, S., Serra, R. (eds) Artificial Life and Evolutionary Computation. WIVACE 2023. Communications in Computer and Information Science, vol 1977. Springer, Cham. https://doi.org/10.1007/978-3-031-57430-6_17
Download citation
DOI: https://doi.org/10.1007/978-3-031-57430-6_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-57429-0
Online ISBN: 978-3-031-57430-6
eBook Packages: Computer ScienceComputer Science (R0)