Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation

Dhaminda Abeywickrama, Suet Lee, Chris Bennett, Razanne Abu-Aisheh, Tom Didiot-Cook, Simon Jones, Sabine Hauert, Kerstin Eder

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

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.
Original languageEnglish
Title of host publicationIEEE International Conference on Engineering Reliable Autonomous Systems
PublisherIEEE
Publication statusAccepted/In press - 31 Mar 2025

Fingerprint

Dive into the research topics of 'Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation'. Together they form a unique fingerprint.

Cite this