Shangpeng Sun
University of Georgia, McGill University, Zaozhuang University
Papers
6
Total Citations
187
H-Index
4
About
Shangpeng Sun is a researcher at the forefront of agricultural robotics and precision phenotyping, with impactful contributions spanning autonomous navigation, computer vision, and environmental sensing. His work centers on developing robotic platforms and advanced algorithms to automate high-throughput field phenotyping—a critical need for accelerating crop breeding programs. Sun’s most cited paper (96 citations) introduces a LiDAR-based autonomous mobile robot for in-field phenotyping and navigation, addressing the labor-intensive bottleneck of manual data collection. He has also pioneered image processing for single cotton boll counting and yield prediction (68 citations), and developed LiDAR-based height estimation for blueberry bushes using a field robotic platform. More recently, Sun has advanced fruit detection with an improved DEtection Transformer (DETR) model for multi-size peach detection using RGB-D cameras, and explored jujube tree trunk detection for robotic harvesting. Notably, his work extends beyond agriculture into atmospheric science, where he developed an aerosol data assimilation system using Fengyun-4A and Himawari-8 satellite data to improve air quality simulations during dust storms. This interdisciplinary breadth underscores Sun’s versatility, while his cumulative citations reflect a growing influence in both agricultural robotics and environmental monitoring.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6