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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Journal of Field Rob...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Journal of Field Robotics
Article . 2026 . Peer-reviewed
License: Wiley Online Library User Agreement
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Formation Control of UAVs Based on Dynamic Vector Velocity Obstacle Method

Authors: Yimei Chen; Shichang Wei; Baoquan Li; Xiaolong Liang; Tao Dai;

Formation Control of UAVs Based on Dynamic Vector Velocity Obstacle Method

Abstract

ABSTRACT This paper proposes a multiple unmanned aerial vehicle (multi‐UAV) formation obstacle avoidance strategy based on the dynamic vector velocity obstacle (DVVO) method, aiming to address the design challenges of the VO method in three‐dimensional (3D) dynamic space applications. By considering the relative position and velocity between the UAV and obstacle, a dynamic avoidance plane (DA‐Plane) is constructed, which can accurately reflect the collision risk of UAVs in 3D space. On this basis, a dynamic vector velocity obstacle space is designed, and the optimal constant critical escape velocity is selected outside this space to accomplish the obstacle avoidance task, thereby ensuring the smoothness of the flight process. Subsequently, this paper extends the DVVO method to multi‐UAV formation based on fuzzy control and the virtual spring algorithm, and designs a differentiated obstacle avoidance strategy to ensure the safe operation of multi‐UAV formation in dynamic environments. Simulation and real‐world experiments demonstrate that the proposed method enables multi‐UAV formation to effectively avoid dynamic obstacles in 3D space and reach the target in a desired formation shape. Compared to the citation algorithm, the DVVO method shows superior performance in terms of smooth motion and computational efficiency. This study effectively simplifies the complex obstacle avoidance problems of multi‐UAV formation in 3D dynamic environments, demonstrating significant potential for applications.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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