Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation

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.

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Publication Details

Published
2025-05-29
DOI
https://doi.org/10.1109/eras63351.2025.11135547
Citations
1
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.71

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article

Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation

Kerstin Eder, Suet Lee, Sabine Hauert, Dhaminda B. Abeywickrama et al.
1 citations
Modular Robots and Swarm Intelligence
0.71
article

Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation

Kerstin Eder, Suet Lee, Sabine Hauert, Dhaminda B. Abeywickrama, Chris Bennett, Razanne Abu-Aisheh, Simon Jones, Tom Didiot-Cook
article en
1 citations

Abstract

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.

University of Manchester (GB), University of Bristol (GB), Bristol Robotics Laboratory (GB)
UK Research and Innovation, Engineering and Physical Sciences Research Council
Openalex Percentile: Top 28%
Modular Robots and Swarm Intelligence
0.71
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Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation — Kerstin Eder, Suet Lee, et al. · (2025) | TGRS Research Map | TGRS