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Precise Interception Flight Targets by Image-based Visual Servoing of Multicopter

Hailong Yan, Kun Yang, Yixiao Cheng, Zihao Wang, Dawei Li

TL;DR

Non-cooperative, low-altitude interception with monocular vision presents challenges from camera motion and processing delays. The paper introduces a PNG-based IBVS controller complemented by a delayed Kalman filter for fast 2D target estimation and a field-of-view holding strategy to maintain target visibility, with Lyapunov-based stability considerations. It demonstrates centimeter-level interception accuracy in SITL (CEP of 0.089 m) and robust real-flight performance under moderate winds (over 80% success below 4 m/s). This approach enables precise, low-overhead interception using affordable monocular sensing and improves final-stage tracking reliability for dynamic targets.

Abstract

Vision-based interception using multicopters equipped strapdown camera is challenging due to camera-motion coupling and evasive targets. This paper proposes a method integrating Image-Based Visual Servoing (IBVS) with proportional navigation guidance (PNG), reducing the multicopter's overload in the final interception phase. It combines smoother trajectories from the IBVS controller with high-frequency target 2D position estimation via a delayed Kalman filter (DKF) to minimize the impact of image processing delays on accuracy. In addition, a field-of-view (FOV) holding controller is designed for stability of the visual servo system. Experimental results show a circular error probability (CEP) of 0.089 m (72.8% lower than the latest relevant IBVS work) in simulations and over 80\% interception success under wind conditions below 4 m/s in real world. These results demonstrate the system's potential for precise low-altitude interception of non-cooperative targets.

Precise Interception Flight Targets by Image-based Visual Servoing of Multicopter

TL;DR

Non-cooperative, low-altitude interception with monocular vision presents challenges from camera motion and processing delays. The paper introduces a PNG-based IBVS controller complemented by a delayed Kalman filter for fast 2D target estimation and a field-of-view holding strategy to maintain target visibility, with Lyapunov-based stability considerations. It demonstrates centimeter-level interception accuracy in SITL (CEP of 0.089 m) and robust real-flight performance under moderate winds (over 80% success below 4 m/s). This approach enables precise, low-overhead interception using affordable monocular sensing and improves final-stage tracking reliability for dynamic targets.

Abstract

Vision-based interception using multicopters equipped strapdown camera is challenging due to camera-motion coupling and evasive targets. This paper proposes a method integrating Image-Based Visual Servoing (IBVS) with proportional navigation guidance (PNG), reducing the multicopter's overload in the final interception phase. It combines smoother trajectories from the IBVS controller with high-frequency target 2D position estimation via a delayed Kalman filter (DKF) to minimize the impact of image processing delays on accuracy. In addition, a field-of-view (FOV) holding controller is designed for stability of the visual servo system. Experimental results show a circular error probability (CEP) of 0.089 m (72.8% lower than the latest relevant IBVS work) in simulations and over 80\% interception success under wind conditions below 4 m/s in real world. These results demonstrate the system's potential for precise low-altitude interception of non-cooperative targets.
Paper Structure (20 sections, 34 equations, 17 figures, 2 tables)

This paper contains 20 sections, 34 equations, 17 figures, 2 tables.

Table of Contents

  1. Introduction
  2. MODELS AND FRAMEWORK
  3. Coordinate systems and relative motion models
  4. Multicopter Dynamics Model
  5. Camera Image Model
  6. Framework overview
  7. CONTROLLER DESIGN AND ANALYSIS
  8. Guidance Algorithm Design
  9. Field of View Holding Controller
  10. Attitude Loop Controller
  11. Stability Analysis of the Proposed Controller
  12. SITL EXPERIMENTS
  13. Platform Introduction and Experimental Design
  14. Static Target Intercept Simulation Experiments
  15. Moving Target Intercept Simulation Experiments
  16. ...and 5 more sections

Figures (17)

  • Figure 1: Intercepting flight target with multicopter.
  • Figure 2: Coordinate system frames and description of the interception problem. In the earth coordinate system, vector $\mathbf{n}_{\mathrm{t}}$ (red vector) represents the LOS direction, while vector $\mathbf{n}_{\mathrm{v}}$ (green vector) represents the velocity direction. This information is obtained from sensors carried by the drone.
  • Figure 3: Framework of proposed IBVS controller based on PNG.
  • Figure 4: SITL Platform and Simulation Scenario.
  • Figure 5: Experiment results of static target interception simulation: (a) multicopter trajectories, (b) boxplots of interception error, (c) initial tagert positions in image plane, and (d) interception error distribution.
  • ...and 12 more figures