AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 6 of its 20 references that are in the map. First posted on arXiv 20 Feb 2023.
Builds on
6 of 20 references.
References · 6
- 2021Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)cited by 40
- 2021The Role of Explainability in Assuring Safety of Machine Learning in Healthcarecited by 26
- 2020Towards a Framework for Certification of Reliable Autonomous Systemscited by 12
- 2022On Specifying for Trustworthinesscited by 8
- 2022DOTS: An Open Testbed for Industrial Swarm Robotic Solutionscited by 3
- 2015Using Models at Runtime to Address Assurance for Self-Adaptive Systemscited by 2
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.