Market-Based Replanning for Safety-Critical UAV Swarms in Search and Rescue Missions
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arXiv
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| Autores principales: | , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866910281208168448 |
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| author | Giacomossi, Luiz Haglund, Andrea Namatovu, Claire Zainali, Emily Målqvist, Esaias Beyene, Yonatan M. Tomasic, Ivan Çürüklü, Baran Forsberg, Håkan |
| author_facet | Giacomossi, Luiz Haglund, Andrea Namatovu, Claire Zainali, Emily Målqvist, Esaias Beyene, Yonatan M. Tomasic, Ivan Çürüklü, Baran Forsberg, Håkan |
| contents | Reliable autonomous UAV swarms in Search and Rescue (SAR) missions require fault-tolerant coordination capable of sustaining operations despite agent degradation. This paper introduces the Intelligent Replanning Drone Swarm (IRDS), a distributed coordination architecture designed for resource-constrained environments. The proposed framework employs a Reverse-Auction market mechanism where agents bid to service search sectors based on a distance-weighted cost function, coupled with a geometric consensus protocol for target verification. We evaluate the approach through physics-based simulations (N=8 agents, 8x8 grid) subjected to stochastic fault injection. Results indicate that the swarm autonomously reallocates tasks from failed agents with low latency relative to the total mission duration, maintaining a mission success rate of 93% under 25% workforce degradation. The proposed framework demonstrates a robust, empirically tested method for self-healing aerial robotic coordination. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2606_01970 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Market-Based Replanning for Safety-Critical UAV Swarms in Search and Rescue Missions Giacomossi, Luiz Haglund, Andrea Namatovu, Claire Zainali, Emily Målqvist, Esaias Beyene, Yonatan M. Tomasic, Ivan Çürüklü, Baran Forsberg, Håkan Robotics Multiagent Systems Systems and Control Reliable autonomous UAV swarms in Search and Rescue (SAR) missions require fault-tolerant coordination capable of sustaining operations despite agent degradation. This paper introduces the Intelligent Replanning Drone Swarm (IRDS), a distributed coordination architecture designed for resource-constrained environments. The proposed framework employs a Reverse-Auction market mechanism where agents bid to service search sectors based on a distance-weighted cost function, coupled with a geometric consensus protocol for target verification. We evaluate the approach through physics-based simulations (N=8 agents, 8x8 grid) subjected to stochastic fault injection. Results indicate that the swarm autonomously reallocates tasks from failed agents with low latency relative to the total mission duration, maintaining a mission success rate of 93% under 25% workforce degradation. The proposed framework demonstrates a robust, empirically tested method for self-healing aerial robotic coordination. |
| title | Market-Based Replanning for Safety-Critical UAV Swarms in Search and Rescue Missions |
| topic | Robotics Multiagent Systems Systems and Control |
| url | https://arxiv.org/abs/2606.01970 |