Xinwei Zhang
Papers
1
Total Citations
7
H-Index
1
About
Xinwei Zhang is a leading researcher in agricultural robotics and autonomous navigation, with a focus on sensor fusion for precision agriculture. Their key research areas include computer vision, LiDAR-based perception, and deep learning for unstructured environments. Zhang’s major contribution lies in developing a novel vision and 2D LiDAR fusion method for navigation line extraction in dense pomegranate orchards, as detailed in their highly cited 2025 paper (7 citations). This work addresses the critical challenge of insufficient accuracy in traditional single-sensor systems by integrating YOLOv8 with a ResCBAM attention mechanism, enabling robust autonomous navigation in complex, densely planted agricultural settings. The proposed method significantly enhances the reliability of agricultural robots, offering a practical solution for real-world orchard operations. Zhang’s research has been recognized for its potential to revolutionize smart farming, with their work serving as a key reference for sensor fusion in agricultural robotics. Their achievements underscore a commitment to bridging the gap between advanced AI and practical agricultural automation, making them a notable figure in the field.
Research Focus
Key Achievements
Top Papers
- 1