Robust Vision-Based Control of a Rotorcraft UAV for Uncooperative Target Tracking

Area of Science:

• Robotics
• Computer Vision
• Control Systems

Background:

• Unmanned Aerial Vehicles (UAVs) require advanced capabilities for observing uncooperative targets.
• Existing methods often struggle with dynamic environments and target uncertainties.

Purpose of the Study:

• To develop and validate a vision-based strategy for UAVs to autonomously track and hover over uncooperative targets.
• To enhance the robustness and stability of UAV observation systems.

Main Methods:

• A virtual camera frame decouples image features from UAV rotation.
• Image centroid and optimal area regulate relative distances.
• Optic flow and gyro data estimate relative velocity.
• A gain-switching proportional-derivative (PD) controller addresses uncertainties.

Main Results:

• The proposed strategy enables independent control of horizontal and vertical distances.
• Relative UAV-to-target velocity is accurately estimated.
• The closed-loop system demonstrates exponential stability via Lyapunov analysis.
• Simulations confirm effectiveness in hovering and tracking scenarios.

Conclusions:

• The vision-based approach offers a robust solution for UAV target tracking and hovering.
• The integration of metrology and control ensures stable and precise observation.
• This strategy is effective for uncooperative targets in complex environments.