Market-Based Replanning for Safety-Critical UAV Swarms in Search and Rescue Missions
For safety-critical UAV swarm operations, this work provides a practical, empirically validated method for fault-tolerant coordination in resource-constrained environments.
The paper introduces IRDS, a distributed coordination architecture for UAV swarms in search and rescue that uses a reverse-auction market mechanism for replanning. Under 25% agent degradation, the swarm maintains a 93% mission success rate with low-latency task reallocation.
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.