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A Time-efficient Prioritised Scheduling Algorithm to Optimise Initial Flock Formation of Drones

arXiv 2512.19914 ↗First posted 22 Dec 2025cs.RO cs.AI cs.SYcited by 0

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Abstract (arXiv)

Drone applications continue to expand across various domains, with flocking offering enhanced cooperative capabilities but introducing significant challenges during initial formation. Existing flocking algorithms often struggle with efficiency and scalability, particularly when potential collisions force drones into suboptimal trajectories. This paper presents a time-efficient prioritised scheduling algorithm that improves the initial formation process of drone flocks. The method assigns each drone a priority based on its number of potential collisions and its likelihood of reaching its target position without permanently obstructing other drones. Using this hierarchy, each drone computes an appropriate delay to ensure a collision-free path. Simulation results show that the proposed algorithm successfully generates collision-free trajectories for flocks of up to 5000 drones and outperforms the coupling-degree-based heuristic prioritised planning method (CDH-PP) in both performance and computational efficiency.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 37 references that are in the map. First posted on arXiv 22 Dec 2025.

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4 of 37 references.

References · 4

  1. 2020Unmanned Aerial Vehicle for Internet of Everything: Opportunities and Challengescited by 5
  2. 2016A Networked Swarm Model for UAV Deployment in the Assessment of Forest Environmentscited by 2
  3. 2022Constraint-based Formation of Drone Swarmscited by 1
  4. 2022In-Flight Energy-Driven Composition of Drone Swarm Servicescited by 1

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