Limitations of Boid Algorithms in UAV Swarm Control: A Simulation-Based Analysis

International Journal of Computer Science and Engineering

© 2025 by SSRG - IJCSE Journal

Volume 12 Issue 9

Year of Publication : 2025

Authors : Hridank Bhagath

10.14445/23488387/IJCSE-V12I9P104

How to Cite?

Hridank Bhagath, "Limitations of Boid Algorithms in UAV Swarm Control: A Simulation-Based Analysis," SSRG International Journal of Computer Science and Engineering , vol. 12,  no. 9, pp. 24-27, 2025. Crossref, https://doi.org/10.14445/23488387/IJCSE-V12I9P104

Abstract:

This paper presents a comprehensive analysis of the limitations of boid algorithms when applied to Unmanned Aerial Vehicle (UAV) swarm control through extensive simulation studies. While boid algorithms have served as foundational models for collective behaviour since Reynolds’ 1987 work, this research demonstrates critical shortcomings in real-world UAV applications, through a custom 3D physics-based simulation incorporating realistic constraints, including limited perception (120° field of view), collision dynamics, energy efficiency trade-offs, and physical flight limitations. Performance degradation is qualified across multiple metrics. Results show collision rates exceeding 30% in moderate-density scenarios, formation maintenance failures above 15 UAVs, and energy inefficiencies resulting in 40% reduced operational time. The simulation reveals that fundamental boid assumptions, instantaneous velocity changes, omnidirectional perception, and simplified interaction rules fail to address the complex requirements of autonomous UAV swarms. These limitations have been compared to modern alternatives, including consensus algorithms, potential field methods, and learning-based approaches, demonstrating 50-70% performance improvements. This work provides quantitative evidence supporting the transition from classical boid algorithms to advanced control methods for practical UAV swarm deployments.

Keywords:

Autonomous navigation, Boid algorithm, Collision avoidance, Distributed systems, Swarm intelligence, UAV swarm control.

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