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

TL;DR

This paper introduces a prioritised scheduling algorithm that enhances initial drone flock formation by reducing collisions and improving efficiency, capable of managing large swarms of up to 5000 drones.

Contribution

The paper proposes a novel time-efficient prioritised scheduling method based on collision potential, significantly improving initial flock formation in drone swarms.

Findings

Successfully generates collision-free trajectories for up to 5000 drones.

Outperforms existing heuristic methods in performance and computational efficiency.

Demonstrates scalability and effectiveness through simulation results.

Abstract

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.