Yibin Tian
Papers
11
Total Citations
142
H-Index
5
About
Yibin Tian is an emerging researcher whose work sits at the dynamic intersection of agricultural robotics, intelligent control systems, and computer vision. His research centers on developing advanced autonomous systems for precision agriculture, with particular emphasis on robotic fruit harvesting, UAV-based farm monitoring, and deep learning-powered object detection. Tian has made notable contributions to cherry tomato detection, pioneering a series of increasingly refined neural network architectures — including DCFA-YOLO, StarBL-YOLO, and LEFF-YOLO — that leverage multimodal RGB-D sensing to improve harvesting robot accuracy in complex field environments. His work on UAV control systems, incorporating fuzzy sliding mode observers and actuator fault detection, has garnered 42 citations, reflecting strong community interest in robust agrobot platforms. Equally significant is his research on flexible robot trajectory control using hybrid Fuzzy ADRC and input shaping techniques (41 citations), bridging soft computing and industrial robotics. Beyond agriculture, Tian has explored surgical navigation systems and underwater image restoration, demonstrating impressive breadth. With over 140 cumulative citations across recent publications, his rapidly growing scholarly footprint marks him as a rising force in intelligent robotics and smart agricultural technology.
Research Focus
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Top Papers
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