Researchers have developed a novel control framework for fixed-wing UAVs equipped with a pan-tilt camera, designed for end-to-end target tracking and engagement. The system integrates a three-phase strategy: initial target acquisition, NMPC-based tracking using a UKF to fuse YOLO detections with inertial data, and a final guidance phase. A key innovation is the use of Control Barrier Functions within the NMPC to prevent UAV self-occlusion during tracking. Simulations confirm the framework's ability to achieve stable tracking and precise interception while adhering to vehicle and camera constraints. AI
IMPACT Enhances autonomous capabilities for aerial vehicles in complex tracking and engagement scenarios.
RANK_REASON The cluster contains a research paper detailing a new control framework for UAVs.
- Biased Proportional Navigation Guidance (BPNG)
- Control Barrier Functions (CBFs)
- Fixed-Wing UAVs
- Nonlinear Model Predictive Control (NMPC)
- Pan-Tilt (PT) camera
- Unscented Kalman Filter (UKF)
- YOLO
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