Abstract
The behaviours of a swarm are not explicitly engineered. Instead, they are an emergent consequence of the interactions of individual agents with each other and their environment. This emergent functionality poses a challenge to safety assurance. The main contribution of this paper is a process for the safety assurance of emergent behaviour in autonomous robotic swarms called AERoS, following the guidance on the Assurance of Machine Learning for use in Autonomous Systems (AMLAS). We explore our proposed process using a case study centred on a robot swarm operating a public cloakroom.
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
References
Abeywickrama, D.B., Bennaceur, A., Chance, G., et al: On specifying for trustworthiness (2022). http://arxiv.org/abs/2206.11421
Cheng, B.H.C., et al.: Using models at runtime to address assurance for self-adaptive systems. In: Bencomo, N., France, R., Cheng, B.H.C., Aßmann, U. (eds.) Models@run.time. LNCS, vol. 8378, pp. 101–136. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-08915-7_4
Hawkins, R., Paterson, C., Picardi, C., Jia, Y., Calinescu, R., Habli, I.: Guidance on the assurance of machine learning in autonomous systems (AMLAS). Guidance Version 1.1, University of York (2021)
Jia, Y., McDermid, J., Lawton, T., Habli, I.: The role of explainability in assuring safety of machine learning in healthcare. IEEE Trans. Emerg. Top. Comput. 10(4), 1746–1760 (2022)
Jones, S., Milner, E., Sooriyabandara, M., Hauert, S.: Distributed situational awareness in robot swarms. Adv. Intell. Syst. 2(11), 2000110 (2020)
Jones, S., Milner, E., Sooriyabandara, M., Hauert, S.: DOTS: an open testbed for industrial swarm robotic solutions (2022)
Jones, S., Studley, M., Hauert, S., Winfield, A.: Evolving behaviour trees for swarm robotics. In: Groß, R., et al. (eds.) Distributed Autonomous Robotic Systems. SPAR, vol. 6, pp. 487–501. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-73008-0_34
Kaakai, F., Dmitriev, K., Adibhatla, S., et al.: Toward a machine learning development lifecycle for product certification and approval in aviation. SAE Int. J. Aerosp. 15(2), 127–143 (2022). https://doi.org/10.4271/01-15-02-0009
Lee, S., Milner, E., Hauert, S.: A data-driven method for metric extraction to detect faults in robot swarms. IEEE Robot. Autom. Lett. 7(4), 10746–10753 (2022)
Mamalet, F., Jenn, E., Flandin, G., Delseny, H., Gabreau, C.: White paper machine learning in certified systems. Technical report HAL-03176080, IRT Saint Exupery (2021)
Milner, E., Sooriyabandara, M., Hauert, S.: Stochastic behaviours for retrieval of storage items using simulated robot swarms. Artif. Life Robot. 27(2), 264–271 (2022). https://doi.org/10.1007/s10015-022-00749-8
Winfield, A.F.T., Nembrini, J.: Safety in numbers: fault-tolerance in robot swarms. Int. J. Model. Identif. Control. 1(1), 30–37 (2006)
Acknowledgements
The authors would like to thank Alvin Wilby, John Downer, Jonathan Ives, and the AMLAS team for their fruitful comments. The work presented has been supported by the UKRI Trustworthy Autonomous Systems Node in Functionality under Grant EP/V026518/1. I.H. is supported by the Assuring Autonomy International Programme at the University of York.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Abeywickrama, D.B. et al. (2023). AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms. In: Guiochet, J., Tonetta, S., Schoitsch, E., Roy, M., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2023 Workshops. SAFECOMP 2023. Lecture Notes in Computer Science, vol 14182. Springer, Cham. https://doi.org/10.1007/978-3-031-40953-0_28
Download citation
DOI: https://doi.org/10.1007/978-3-031-40953-0_28
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-40952-3
Online ISBN: 978-3-031-40953-0
eBook Packages: Computer ScienceComputer Science (R0)