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Distributed Time-Coordinated Guidance for Safe Fireline Deployment of UAV Swarms

Sep 2026 · Drones · Vol 10, pp. 735 · 0 citations

TL;DR

The proposed two-stage distributed guidance framework for time-coordinated fireline deployment achieves the smallest terminal timing error among the compared strategies and demonstrates effective and scalable time-coordinated deployment under the considered kinematic and communication conditions.

Abstract

Rapid wildfire response requires UAV swarms to approach a fire region from dispersed initial states, coordinate their arrival with limited information exchange, and adapt terminal deployment to updated fireline geometry. This paper proposes a two-stage distributed guidance framework for time-coordinated fireline deployment. In Stage I, a regularized closing-time variable is combined with bounded-degree topological interaction, proximity-based collision avoidance, and persistent longitudinal speed regulation to reduce rendezvous-time dispersion. In Stage II, the updated fireline is discretized into service points and assigned using a geometry-aware structured strategy, followed by distance-aware terminal synchronization and local safety control. Conditional analysis establishes convergence of the reduced Stage-I coordination dynamics under admissible switching topologies and sufficient separation conditions for ideal Stage-II deployment. In the 12-UAV Stage-I comparison, the proposed method reduces the arrival-time spread to 1.34 s, compared with 16.12 s for fixed-topology cooperative guidance and 4.20 s without longitudinal timing correction. Stage-I tests are further extended to 100 UAVs, while Stage-II assignment is evaluated with up to 60 UAVs and maintains low computational cost. In matched three-dimensional tests involving measurement noise, wind disturbance, and bounded communication delay, the proposed method achieves the smallest terminal timing error among the compared strategies, with a mean Stage-II spread of 2.654 s over the four tested conditions. The results demonstrate effective and scalable time-coordinated deployment under the considered kinematic and communication conditions.

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