Formation Maintenance Control of Unmanned Aerial Vehicle Swarms based on Simulated Visual Perception

Traditional formation control methods relied on inter-agent communication are inadequate in increasingly complex electromagnetic environments. Inspired by flocking behaviors observed in biological systems, bio-inspired visual formations present a solution to overcome the limitations of conventional communication. This paper focuses on the formation maintenance control of unmanned aerial vehicle (UAV) swarms using simulated visual perception. A pairwise leader-follower three-dimensional (3D) formation control approach is proposed. The approach utilizes visual information with noise and time delays to replace the front-end vision recognition algorithm. Visual-dominant behavioral rules are designed, and an accumulated error elimination mechanism is incorporated to enhance long-term formation stability. The 3D formation maintenance algorithm was tested in software-in-the-loop simulations by changing formation sizes, flight paths, and failure conditions, proving its stability and robustness. Ablation experiments further confirmed the effectiveness of the accumulated error elimination mechanism.

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Publication Details

Published
2025-05-17
DOI
https://doi.org/10.1109/yac66630.2025.11150132
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

Formation Maintenance Control of Unmanned Aerial Vehicle Swarms based on Simulated Visual Perception

Geochemistry and Geologic Mapping
article

Formation Maintenance Control of Unmanned Aerial Vehicle Swarms based on Simulated Visual Perception

article en

Abstract

Traditional formation control methods relied on inter-agent communication are inadequate in increasingly complex electromagnetic environments. Inspired by flocking behaviors observed in biological systems, bio-inspired visual formations present a solution to overcome the limitations of conventional communication. This paper focuses on the formation maintenance control of unmanned aerial vehicle (UAV) swarms using simulated visual perception. A pairwise leader-follower three-dimensional (3D) formation control approach is proposed. The approach utilizes visual information with noise and time delays to replace the front-end vision recognition algorithm. Visual-dominant behavioral rules are designed, and an accumulated error elimination mechanism is incorporated to enhance long-term formation stability. The 3D formation maintenance algorithm was tested in software-in-the-loop simulations by changing formation sizes, flight paths, and failure conditions, proving its stability and robustness. Ablation experiments further confirmed the effectiveness of the accumulated error elimination mechanism.

Beijing Institute of Technology (CN), Shenzhen Technology University (CN), Shenzhen MSU-BIT University
Openalex Percentile: Top 25%
Geochemistry and Geologic Mapping
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