Xudong Jing
Papers
1
Total Citations
10
H-Index
1
About
Xudong Jing is a researcher at the forefront of agricultural robotics and computer vision, with a specific focus on enabling precise, automated fruit harvesting. His work centers on developing end-to-end deep learning architectures that bridge the gap between high-level perception and low-level robotic control. Jing’s most-cited paper introduces a novel stereo matching network that achieves full-resolution depth estimation through a two-stage partition filtering mechanism. This innovation is critical for the precise localization of kiwifruit in complex orchard environments, directly addressing a key bottleneck in robotic harvesting: the need for accurate, real-time 3D spatial understanding. By integrating depth estimation with object detection, his approach demonstrates a practical pathway for robots to identify and grasp fruit with high reliability. With a growing citation impact, Jing’s contributions are not only advancing the state of the art in stereo vision but also providing a foundational technology for the next generation of autonomous agricultural systems. His work stands out for its direct application to solving real-world challenges in food production.
Research Focus
Key Achievements
Top Papers
- 1