Aerial Tracking

Aerial tracking focuses on enabling unmanned aerial vehicles (UAVs) to autonomously follow moving targets, often in complex and cluttered environments, prioritizing safety and maintaining target visibility. Current research emphasizes robust object detection and tracking algorithms, often leveraging deep learning architectures like transformers and YOLO-family models, alongside trajectory planning methods employing techniques such as Bernstein polynomials, quadratic programming, and model predictive control to generate collision-free paths. These advancements are crucial for improving the safety and autonomy of UAVs in various applications, including search and rescue, surveillance, and advanced air mobility.