Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866909517613105152 |
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| author | Abeywickrama, Dhaminda B. Lee, Suet Bennett, Chris Abu-Aisheh, Razanne Didiot-Cook, Tom Jones, Simon Hauert, Sabine Eder, Kerstin |
| author_facet | Abeywickrama, Dhaminda B. Lee, Suet Bennett, Chris Abu-Aisheh, Razanne Didiot-Cook, Tom Jones, Simon Hauert, Sabine Eder, Kerstin |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_15475 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation Abeywickrama, Dhaminda B. Lee, Suet Bennett, Chris Abu-Aisheh, Razanne Didiot-Cook, Tom Jones, Simon Hauert, Sabine Eder, Kerstin Robotics Artificial Intelligence I.2.9; D.2; I.6 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. |
| title | Autonomous Robotic Swarms: A Corroborative Approach for Verification and Validation |
| topic | Robotics Artificial Intelligence I.2.9; D.2; I.6 |
| url | https://arxiv.org/abs/2407.15475 |