A Time-efficient Prioritised Scheduling Algorithm to Optimise Initial Flock Formation of Drones
This work addresses a domain-specific challenge for drone applications by improving flock formation efficiency, though it appears incremental as it builds on existing prioritised planning methods.
The paper tackles the problem of inefficient and unscalable initial formation in drone flocks by proposing a time-efficient prioritised scheduling algorithm that assigns priorities based on collision risks and target reachability, resulting in collision-free trajectories for up to 5000 drones and outperforming an existing method in performance and computational efficiency.
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.