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Vision-based control for landing an aerial vehicle on a marine vessel

Haohua Dong

TL;DR

This work tackles autonomous landing of a quadrotor on a moving marine platform using image-based visual servoing (IBVS) with only an onboard camera and an IMU. It develops a hierarchical controller: a fast inner-loop attitude PD controller combined with an outer-loop vision-based law that uses the centroid of landmark projections and translational optical flow to drive the vehicle toward the moving target while keeping a positive altitude. Key contributions include a full IBVS formulation with spherical image-kinematics, a convergence-guaranteed control law, and MATLAB/Gazebo validation across oscillatory and stochastic target motions. The results demonstrate the feasibility and robustness of vision-driven landings on moving surfaces, offering guidance for real-world SITL/PX4 deployments and future hardware experiments in maritime environments.

Abstract

This work addresses the landing problem of an aerial vehicle, exemplified by a simple quadrotor, on a moving platform using image-based visual servo control. First, the mathematical model of the quadrotor aircraft is introduced, followed by the design of the inner-loop control. At the second stage, the image features on the textured target plane are exploited to derive a vision-based control law. The image of the spherical centroid of a set of landmarks present in the landing target is used as a position measurement, whereas the translational optical flow is used as velocity measurement. The kinematics of the vision-based system is expressed in terms of the observable features, and the proposed control law guarantees convergence without estimating the unknown distance between the vision system and the target, which is also guaranteed to remain strictly positive, avoiding undesired collisions. The performance of the proposed control law is evaluated in MATLAB and 3-D simulation software Gazebo. Simulation results for a quadrotor UAV are provided for different velocity profiles of the moving target, showcasing the robustness of the proposed controller.

Vision-based control for landing an aerial vehicle on a marine vessel

TL;DR

This work tackles autonomous landing of a quadrotor on a moving marine platform using image-based visual servoing (IBVS) with only an onboard camera and an IMU. It develops a hierarchical controller: a fast inner-loop attitude PD controller combined with an outer-loop vision-based law that uses the centroid of landmark projections and translational optical flow to drive the vehicle toward the moving target while keeping a positive altitude. Key contributions include a full IBVS formulation with spherical image-kinematics, a convergence-guaranteed control law, and MATLAB/Gazebo validation across oscillatory and stochastic target motions. The results demonstrate the feasibility and robustness of vision-driven landings on moving surfaces, offering guidance for real-world SITL/PX4 deployments and future hardware experiments in maritime environments.

Abstract

This work addresses the landing problem of an aerial vehicle, exemplified by a simple quadrotor, on a moving platform using image-based visual servo control. First, the mathematical model of the quadrotor aircraft is introduced, followed by the design of the inner-loop control. At the second stage, the image features on the textured target plane are exploited to derive a vision-based control law. The image of the spherical centroid of a set of landmarks present in the landing target is used as a position measurement, whereas the translational optical flow is used as velocity measurement. The kinematics of the vision-based system is expressed in terms of the observable features, and the proposed control law guarantees convergence without estimating the unknown distance between the vision system and the target, which is also guaranteed to remain strictly positive, avoiding undesired collisions. The performance of the proposed control law is evaluated in MATLAB and 3-D simulation software Gazebo. Simulation results for a quadrotor UAV are provided for different velocity profiles of the moving target, showcasing the robustness of the proposed controller.
Paper Structure (22 sections, 1 theorem, 47 equations, 22 figures)

This paper contains 22 sections, 1 theorem, 47 equations, 22 figures.

Table of Contents

  1. Introduction
  2. Related Work
  3. UAV Modeling
  4. Inner-Loop Design
  5. Generating angle references from acceleration commands
  6. Image Features
  7. Spherical Camera Geometry
  8. Optical Flow
  9. Lucas-Kanade Algorithm
  10. Spherical Image Kinematics
  11. Visual Velocity Measurement --- Translational Optical Flow
  12. Visual Position Measurement --- Centroid Vector
  13. Vision-Based Control
  14. Simulation Architecture
  15. Results
  16. ...and 7 more sections

Key Result

Theorem V.1

Consider the closed-loop system of sect5:eq:image_dynamics_system with the control law where $(k_1, k_2, k_3)$ are positive scalar gains, $w_d>0$, and $\mu_m$ accounts for measurement noise, which is assumed to be bounded, $\eta$ the target plane direction, $q$ the landmark centroid vector in the camera frame and $W$ the translational optical flow. If the condition with $\epsilon>0$ arbitrarily

Figures (22)

  • Figure 1: Landing manoeuvre of an UAV on a moving target
  • Figure 2: Reference frames and force for schematic representation of a quadrotor
  • Figure 3: Hierarchical control design strategy
  • Figure 4: Pinhole camera model
  • Figure 5: Spherical image projection
  • ...and 17 more figures

Theorems & Definitions (2)

  • Theorem V.1
  • Remark 1