Yun Shi

Tokyo University of Information Sciences, Institute of Agricultural Resources and Regional Planning

Papers

Total Citations

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About

Yun Shi is a researcher whose work bridges the critical gap between autonomous navigation and precision agriculture. Their early, highly influential research focused on GPS-supported Visual SLAM (Simultaneous Localization and Mapping) using a panoramic camera, a foundational contribution to the fields of robot navigation and urban mapping. This work, which has garnered 42 citations, introduced a rigorous sensor model that dramatically improved the accuracy of moving sensor localization, a core challenge for autonomous systems. More recently, Shi has applied their expertise in computer vision to the pressing problem of agricultural automation. Their 2024 paper on an unstructured orchard grape detection method using YOLOv5s (16 citations) directly addresses the global labor shortage in the grape industry. By achieving rapid and accurate fruit identification, this work provides a crucial component for the development of intelligent harvesting robots. This shift from robust outdoor localization to targeted agricultural perception demonstrates a versatile and impactful career, tackling fundamental challenges in robotics to create practical solutions for modern industry.