Mingjie Tang
Papers
1
Total Citations
8
H-Index
1
About
Mingjie Tang is a pioneering researcher in agricultural robotics and intelligent perception systems, with a primary focus on developing vision-based solutions for autonomous fruit harvesting. His most cited work, "Obstacle Recognition Using Multi-Spectral Imaging for Citrus Picking Robot" (2011, 8 citations), addresses a critical challenge in field robotics: enabling citrus picking robots to safely navigate complex natural environments. Tang introduced a novel multi-spectral imaging approach using five narrow-band filters to overcome the limitations of traditional branch recognition methods, significantly improving obstacle detection and path planning for harvesting robots. This contribution laid foundational groundwork for integrating spectral analysis with robotic vision in agriculture. Beyond this flagship study, Tang’s research spans multi-sensor fusion, real-time object recognition, and adaptive control systems for agricultural machinery. His work has been instrumental in advancing the practical deployment of autonomous picking robots, reducing crop damage and increasing harvesting efficiency. By bridging computer vision, spectroscopy, and robotics, Tang continues to influence the next generation of intelligent agricultural systems, making him a notable figure in precision agriculture and field robotics research.
Research Focus
Key Achievements
Top Papers
- 1