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Landing control algorithm for gimbal-serviced UAVs based on field-of-view constraints
by
Mao, Wenlong
, Huo, Mingen
, Li, Zhanxiang
in
639/166
/ 639/705
/ Autonomous UAV landing
/ Cameras
/ Collaboration
/ Control algorithms
/ Energy consumption
/ Field-of-view constraint
/ Humanities and Social Sciences
/ multidisciplinary
/ Prescribed performance control
/ Science
/ Science (multidisciplinary)
/ Stability analysis
/ Unmanned aerial vehicles
/ Velocity
/ Velocity estimation
/ Visual servo control
2025
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Landing control algorithm for gimbal-serviced UAVs based on field-of-view constraints
by
Mao, Wenlong
, Huo, Mingen
, Li, Zhanxiang
in
639/166
/ 639/705
/ Autonomous UAV landing
/ Cameras
/ Collaboration
/ Control algorithms
/ Energy consumption
/ Field-of-view constraint
/ Humanities and Social Sciences
/ multidisciplinary
/ Prescribed performance control
/ Science
/ Science (multidisciplinary)
/ Stability analysis
/ Unmanned aerial vehicles
/ Velocity
/ Velocity estimation
/ Visual servo control
2025
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Do you wish to request the book?
Landing control algorithm for gimbal-serviced UAVs based on field-of-view constraints
by
Mao, Wenlong
, Huo, Mingen
, Li, Zhanxiang
in
639/166
/ 639/705
/ Autonomous UAV landing
/ Cameras
/ Collaboration
/ Control algorithms
/ Energy consumption
/ Field-of-view constraint
/ Humanities and Social Sciences
/ multidisciplinary
/ Prescribed performance control
/ Science
/ Science (multidisciplinary)
/ Stability analysis
/ Unmanned aerial vehicles
/ Velocity
/ Velocity estimation
/ Visual servo control
2025
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Landing control algorithm for gimbal-serviced UAVs based on field-of-view constraints
Journal Article
Landing control algorithm for gimbal-serviced UAVs based on field-of-view constraints
2025
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Overview
This paper presents a robust and adaptive visual servoing-based landing control method for unmanned aerial vehicles (UAVs) equipped with a three-axis gimbal camera. To address the limitations of fixed-camera configurations, the proposed approach integrates pixel-level field-of-view (FOV) constraints and leverages the gimbal’s agility for enhanced visual tracking. The landing task is formulated as a constrained image-based control problem, where tracking errors of image features are rigorously bounded using prescribed performance functions. A velocity observer is incorporated to estimate the time-varying motion of the landing platform in real time, enabling accurate autonomous landing without relying on external communication or infrastructure. Lyapunov-based stability analysis confirms the theoretical soundness of the control strategy. Simulation results validate the effectiveness and robustness of the proposed method, demonstrating improved accuracy, adaptability, and practical applicability in UAV landing scenarios.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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