Image-based Visual Servoing Control of UAV Dynamic Landing under Field of View Constraints

GUO Hanyu; SONG Tao; YE Jianchuan; ZHU Hai; ZHOU Jiexin; ZHU Xiaozhou

doi:10.12382/bgxb.2025.0132

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Image-based Visual Servoing Control of UAV Dynamic Landing under Field of View Constraints

更新时间：2026-04-24

- Image-based Visual Servoing Control of UAV Dynamic Landing under Field of View Constraints
- Acta Armamentarii Vol. 47, Issue 2, Pages: 250132(2026)
- 作者机构：
  
  北京理工大学空天科学与技术学院，北京 100081
  军事科学院国防科技创新研究院，北京 100071
  智能博弈与决策实验室，北京 100071
- 作者简介：
- 基金信息：
- DOI：10.12382/bgxb.2025.0132
  CLC： V249.122
- Received：28 February 2025，
  
  Online First：25 December 2025，
  
  Published：28 February 2026
- 稿件说明：
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GUO Hanyu, SONG Tao, YE Jianchuan, et al. Image-based Visual Servoing Control of UAV Dynamic Landing under Field of View Constraints[J]. Acta Armamentarii, 2026, 47(2): 250132.
DOI：

GUO Hanyu, SONG Tao, YE Jianchuan, et al. Image-based Visual Servoing Control of UAV Dynamic Landing under Field of View Constraints[J]. Acta Armamentarii, 2026, 47(2): 250132. DOI： 10.12382/bgxb.2025.0132.

摘要

基于图像视觉伺服（Image-Based Visual Servoing，IBVS）的四旋翼无人机（Unmanned Aerial Vehicle，UAV）系统是一个具有耦合特性的非线性系统，其在降落及跟踪过程中的姿态变化会造成地面目标脱离视场（Field of View，FOV），导致控制失效。为解决此问题，提出一种考虑FOV约束的控制方法，并设计高阶滑模观测器（Higher Order Sliding Mode Observer，HOSMO）估计集总扰动。基于虚拟图像平面和图像矩特征构建系统模型，设计基于IBVS及HOSMO补偿的模型预测控制方法，并分析稳定性。结合FOV约束条件得到姿态动态边界，进而引入FOV约束，并分析约束的有效性。仿真结果表明，所提方法实现了UAV对机动目标的稳定跟踪，高度方向的跟踪误差降低约49%，同时在FOV约束下，实现了UAV对位于FOV边缘的机动目标的稳定跟踪和准确降落，对比现有方法扩展了基于IBVS的跟踪及降落包线。

Abstract

The quadrotor unmanned aerial vehicle(UAV)system based on image-based visual servoing(IBVS)is a nonlinear system with coupling characteristics. Its attitude change during landing and tracking will cause the ground target to move out of the field of view(FOV)

resulting in control failure. To solve this problem

a control method considering the FOV constraint is proposed

and a high-order sliding mode observer(HOSMO)is designed to estimate the lumped disturbance. A system model is constructed based on the virtual image plane and image moment features

and a model predictive control(MPC)method based on IBVS and HOSMO compensation is designed

and the stability is analyzed. The attitude dynamic boundary is obtained based on the FOV constraint condition. Then the FOV constraint is introduced

and the effectiveness of the constraint is analyzed. The simulated results show that the UAV can stably track the maneuvering target through the proposed method

and the tracking error in the height direction is reduced by about 49%. At the same time

under the constraint of the FOV

the UAV can stably track and accurately land on a maneuvering target that is at the edge of the FOV. The proposed method is used to expand the tracking and landing envelope based on IBVS compared with the existing methods.

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Keywords

references

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