Zhanpeng Liang
Papers
2
Total Citations
12
H-Index
2
About
Zhanpeng Liang is a rising researcher in agricultural robotics and precision farming, with a focus on autonomous navigation for field robots. His work centers on vision-based perception and control systems that enable robots to operate reliably in complex, unstructured agricultural environments. Liang’s major contributions include developing a trajectory generation and tracking algorithm for paddy field robots, which integrates real-time visual feedback to maneuver through flooded, uneven terrain—a critical challenge for mechanized rice farming. This work has already garnered 10 citations since its 2024 publication, signaling its practical relevance. More recently, Liang introduced PRSGNet, a robust deep learning framework for crop row detection in challenging field conditions such as variable lighting, occlusions, and irregular planting patterns. Although published in 2025, this framework has quickly attracted attention for its potential to improve autonomous guidance in weeding, spraying, and harvesting. Liang’s research bridges computer vision and agricultural engineering, offering scalable solutions for sustainable farming. His achievements highlight a promising trajectory in smart agriculture, where his algorithms are poised to reduce labor costs and increase precision in crop management.
Research Focus
Key Achievements
Top Papers
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- 2