Robust Geospatial Coordination of Multi-Agent Communications Networks Under Attrition
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866908929560150016 |
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| author | Kent, Jonathan S. Stefani, Eliana Plancher, Brian |
| author_facet | Kent, Jonathan S. Stefani, Eliana Plancher, Brian |
| contents | Coordinating emergency responses in extreme environments, such as wildfires, requires resilient and high-bandwidth communication backbones. While autonomous aerial swarms can establish ad-hoc networks to provide this connectivity, the high risk of individual node attrition in these settings often leads to network fragmentation and mission-critical downtime.
To overcome this challenge, we introduce and formalize the problem of Robust Task Networking Under Attrition (RTNUA), which extends connectivity maintenance in multi-robot systems to explicitly address proactive redundancy and attrition recovery. We then introduce Physics-Informed Robust Employment of Multi-Agent Networks ($Φ$IREMAN), a topological algorithm leveraging physics-inspired potential fields to solve this problem. In our evaluations, $Φ$IREMAN consistently outperforms baselines, and is able to maintain greater than $99.9\%$ task uptime despite substantial attrition in simulations with up to 100 tasks and 500 drones, demonstrating both effectiveness and scalability. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_02079 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Robust Geospatial Coordination of Multi-Agent Communications Networks Under Attrition Kent, Jonathan S. Stefani, Eliana Plancher, Brian Robotics Multiagent Systems Systems and Control 93C85, 68T40, 93A14, 68W15 I.2.9; I.2.11; C.2.1 Coordinating emergency responses in extreme environments, such as wildfires, requires resilient and high-bandwidth communication backbones. While autonomous aerial swarms can establish ad-hoc networks to provide this connectivity, the high risk of individual node attrition in these settings often leads to network fragmentation and mission-critical downtime. To overcome this challenge, we introduce and formalize the problem of Robust Task Networking Under Attrition (RTNUA), which extends connectivity maintenance in multi-robot systems to explicitly address proactive redundancy and attrition recovery. We then introduce Physics-Informed Robust Employment of Multi-Agent Networks ($Φ$IREMAN), a topological algorithm leveraging physics-inspired potential fields to solve this problem. In our evaluations, $Φ$IREMAN consistently outperforms baselines, and is able to maintain greater than $99.9\%$ task uptime despite substantial attrition in simulations with up to 100 tasks and 500 drones, demonstrating both effectiveness and scalability. |
| title | Robust Geospatial Coordination of Multi-Agent Communications Networks Under Attrition |
| topic | Robotics Multiagent Systems Systems and Control 93C85, 68T40, 93A14, 68W15 I.2.9; I.2.11; C.2.1 |
| url | https://arxiv.org/abs/2512.02079 |