mlsanityData to 7 Oct 2026

Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation

arXiv 2407.15475 ↗First posted 22 Jul 2024cs.RO cs.AIcited by 1

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Abstract (arXiv)

The emergent behaviour of autonomous robotic swarms poses a significant challenge to their safety assurance. Assurance tasks encompass adherence to standards, certification processes, and the execution of verification and validation (V&V) methods, such as model checking. In this study, we propose a corroborative approach for formally verifying and validating autonomous robotic swarms, which are defined at the macroscopic formal modelling, low-fidelity simulation, high-fidelity simulation, and real-robot levels. Our formal macroscopic models, used for verification, are characterised by data derived from actual simulations to ensure both accuracy and traceability across different swarm system models. Furthermore, our work combines formal verification with simulations and experimental validation using real robots. In this way, our corroborative approach for V&V seeks to enhance confidence in the evidence, in contrast to employing these methods separately. We explore our approach through a case study focused on a swarm of robots operating within a public cloakroom.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 29 references that are in the map. First posted on arXiv 22 Jul 2024.

Builds on

6 of 29 references.

References · 6

  1. 2022Robot Operating System 2: Design, Architecture, and Uses In The Wildcited by 190
  2. 2021Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)cited by 40
  3. 2022On Specifying for Trustworthinesscited by 8
  4. 2016A Corroborative Approach to Verification and Validation of Human--Robot Teamscited by 6
  5. 2022DOTS: An Open Testbed for Industrial Swarm Robotic Solutionscited by 3
  6. 2023AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarmscited by 2

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