Distributed safety verification for multi-agent systems
The control barrier function (CBF) framework is a powerful tool for safe controller design and safety analysis. Given a dynamical system and a CBF, the system is safe if the CBF-induced constraints are satisfied for every state inside an invariant set, which is a subset of the safe set. In this pape...
| Main Authors: | , , |
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| Formato: | Conference item |
| Idioma: | English |
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IEEE
2023
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| _version_ | 1826312546722775040 |
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| author | Wang, H Papachristodoulou, A Margellos, K |
| author_facet | Wang, H Papachristodoulou, A Margellos, K |
| author_sort | Wang, H |
| collection | OXFORD |
| description | The control barrier function (CBF) framework is a powerful tool for safe controller design and safety analysis. Given a dynamical system and a CBF, the system is safe if the CBF-induced constraints are satisfied for every state inside an invariant set, which is a subset of the safe set. In this paper we propose a safety verification algorithm for networked nonlinear multi-agent systems. In our proposed algorithm, we independently sample scenarios from the invariant set, and subsequently quantify safety for the multi-agent system by solving a scenario program in a distributed manner. Both the scenario sampling and safety verification algorithms are fully distributed. The efficacy of our algorithm is demonstrated by an example on multi-robot collision avoidance. |
| first_indexed | 2024-04-09T03:54:39Z |
| format | Conference item |
| id | oxford-uuid:5972ffe0-b9fb-425f-b3e3-c1cbe7178faa |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-04-09T03:54:39Z |
| publishDate | 2023 |
| publisher | IEEE |
| record_format | dspace |
| spelling | oxford-uuid:5972ffe0-b9fb-425f-b3e3-c1cbe7178faa2024-03-12T16:12:03ZDistributed safety verification for multi-agent systemsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:5972ffe0-b9fb-425f-b3e3-c1cbe7178faaEnglishSymplectic ElementsIEEE2023Wang, HPapachristodoulou, AMargellos, KThe control barrier function (CBF) framework is a powerful tool for safe controller design and safety analysis. Given a dynamical system and a CBF, the system is safe if the CBF-induced constraints are satisfied for every state inside an invariant set, which is a subset of the safe set. In this paper we propose a safety verification algorithm for networked nonlinear multi-agent systems. In our proposed algorithm, we independently sample scenarios from the invariant set, and subsequently quantify safety for the multi-agent system by solving a scenario program in a distributed manner. Both the scenario sampling and safety verification algorithms are fully distributed. The efficacy of our algorithm is demonstrated by an example on multi-robot collision avoidance. |
| spellingShingle | Wang, H Papachristodoulou, A Margellos, K Distributed safety verification for multi-agent systems |
| title | Distributed safety verification for multi-agent systems |
| title_full | Distributed safety verification for multi-agent systems |
| title_fullStr | Distributed safety verification for multi-agent systems |
| title_full_unstemmed | Distributed safety verification for multi-agent systems |
| title_short | Distributed safety verification for multi-agent systems |
| title_sort | distributed safety verification for multi agent systems |
| work_keys_str_mv | AT wangh distributedsafetyverificationformultiagentsystems AT papachristodouloua distributedsafetyverificationformultiagentsystems AT margellosk distributedsafetyverificationformultiagentsystems |