Xiangming Lei
Papers
3
Total Citations
55
H-Index
3
About
Xiangming Lei is a leading researcher in agricultural robotics and precision automation, with a core focus on integrating multi-sensor systems for intelligent crop management. His work addresses critical challenges in greenhouse and field environments, particularly where traditional navigation and vision systems fail due to complex terrain or natural lighting. Lei’s major contributions include the development of an integrated indoor positioning system for greenhouse robots that fuses UWB, IMU, ODOM, and LIDAR data, effectively correcting wheel-slip errors on uneven ground—a breakthrough cited 42 times. He also pioneered a binocular stereo vision method for detecting and positioning Camellia oleifera fruit, employing YOLOv7 deep learning and LBP texture matching to enable rapid, accurate robotic picking. In pest control, Lei devised a 3D locating system using multi-constraint stereo matching to target pests like Pieris rapae with laser precision, overcoming color-similarity challenges. With over 55 citations across his top papers, Lei’s work is foundational for autonomous agriculture, reducing reliance on manual labor and chemical pesticides. His achievements position him at the forefront of smart farming innovation, inspiring future research in sensor fusion and real-time agricultural decision-making.
Research Focus
Key Achievements
Top Papers
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