Xiangyang Sun
Chinese Academy of Sciences, Shandong Agricultural University
Papers
2
Total Citations
78
H-Index
2
About
Xiangyang Sun is a pioneering researcher at the intersection of intelligent control systems and precision agricultural robotics. His work spans two critical domains: advanced nonlinear control for robotic manipulators and deep learning-based object detection for automated harvesting. Sun's most influential contribution is his 2022 paper on approximate continuous fixed-time terminal sliding mode control, which has garnered 51 citations for its novel approach to ensuring prescribed performance in uncertain robotic systems—a breakthrough that enhances both safety and precision in industrial automation. More recently, his 2024 study on S-YOLO, a lightweight model for enhanced tomato detection in greenhouses (27 citations), directly addresses the challenge of identifying occluded and small targets in complex environments. By dramatically improving recognition accuracy and processing speed, this work accelerates the path toward fully automated harvesting. Sun's dual expertise in robust control theory and efficient computer vision positions him as a key figure bridging fundamental robotics research with practical agricultural applications, making his work essential reading for engineers developing next-generation autonomous systems.
Research Focus
Key Achievements
Top Papers
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