Multi-Agent Cooperative Transportation Control Based on Control Barrier Functions

Multi-UAV cooperative transportation in confined environments requires coordinated turning, collision avoidance, and mitigation of gust-induced payload motion. This paper develops a task-specific control framework that coordinates formation-geometry adaptation, payload-offset feedback, and safety filtering. A virtual-leader-based steering mechanism rotates the formation configuration with the reference-path tangent to reduce geometric mismatch during turns. A payload-offset feedback law adjusts the formation radius in response to gust-induced displacement, modifying the towing geometry to reduce residual oscillations. Inter-UAV and UAV–obstacle distance constraints are enforced by an HOCBF-based QP safety filter that modifies nominal acceleration commands subject to componentwise limits. In simulations with four UAVs and three static obstacles, the minimum inter-UAV and UAV–obstacle surface distances are 0.6905 m and 1.2851 m, respectively, satisfying the prescribed 0.6 m and 1.0 m limits; the mean computation time, including QP setup and solver execution, is 0.9309 ms. Under the baseline gust, adaptive formation expansion reduces the late-recovery peak of an offset-derived swing-angle indicator by 11.2% compared with fixed-radius control. The results illustrate how task-specific formation adaptation and payload-offset feedback can be coordinated with established safety filtering for cooperative transportation.

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Publication Details

Journal
Aerospace
Published
2026-11-10
DOI
https://doi.org/10.3390/aerospace13111053
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
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article

Multi-Agent Cooperative Transportation Control Based on Control Barrier Functions

Weilin LI, Jinwen Hu, 宋传琳, 昱飞 宋 et al.
Aerospace
Distributed Control Multi-Agent Systems
article

Multi-Agent Cooperative Transportation Control Based on Control Barrier Functions

Weilin LI, Jinwen Hu, 宋传琳, 昱飞 宋, Lu Han, Zhihang Chen, Wendi Shang, Ming Huang, Haoran Zhang
article en

Abstract

Multi-UAV cooperative transportation in confined environments requires coordinated turning, collision avoidance, and mitigation of gust-induced payload motion. This paper develops a task-specific control framework that coordinates formation-geometry adaptation, payload-offset feedback, and safety filtering. A virtual-leader-based steering mechanism rotates the formation configuration with the reference-path tangent to reduce geometric mismatch during turns. A payload-offset feedback law adjusts the formation radius in response to gust-induced displacement, modifying the towing geometry to reduce residual oscillations. Inter-UAV and UAV–obstacle distance constraints are enforced by an HOCBF-based QP safety filter that modifies nominal acceleration commands subject to componentwise limits. In simulations with four UAVs and three static obstacles, the minimum inter-UAV and UAV–obstacle surface distances are 0.6905 m and 1.2851 m, respectively, satisfying the prescribed 0.6 m and 1.0 m limits; the mean computation time, including QP setup and solver execution, is 0.9309 ms. Under the baseline gust, adaptive formation expansion reduces the late-recovery peak of an offset-derived swing-angle indicator by 11.2% compared with fixed-radius control. The results illustrate how task-specific formation adaptation and payload-offset feedback can be coordinated with established safety filtering for cooperative transportation.

AerospaceVol. 13(11)
Northwestern Polytechnical University (CN)
Distributed Control Multi-Agent Systems
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