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About

Yuzhi Tan is a pioneering researcher in agricultural robotics, specializing in computer vision and robotic harvesting systems for greenhouse environments. Their work focuses on developing intelligent machines that can autonomously identify, locate, and harvest crops—addressing critical labor shortages and improving agricultural efficiency. Tan’s most influential contribution is the development and evaluation of a watermelon-harvesting robot prototype, which integrates a sophisticated vision system and end-effector, garnering 36 citations. This work represents a significant step toward practical, automated harvesting in complex greenhouse settings. Earlier foundational research includes a highly cited method for recognizing greenhouse cucumber fruit using a three-layer backpropagation neural network (30 citations), which segmented plant images using blue and saturation color components. Tan also advanced the field by employing near-infrared imaging for cucumber detection and spatial localization, enabling quality discrimination and precise picking. Additional contributions include navigation line detection for agricultural vehicles in vegetation-embraced environments and fuzzy control-based visual navigation for cucumber picking robots. With over 98 total citations across their most-cited works, Tan’s research has laid essential groundwork for the next generation of autonomous agricultural robots, directly impacting the future of precision farming.