Chujie Wu

Guangxi University, Precision Research (United States), The University of Tokyo

Papers

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About

Chujie Wu is a robotics researcher whose work bridges the gap between agricultural automation and underwater perception, tackling fundamental challenges in visual intelligence for dynamic environments. In precision agriculture, Wu developed a novel binocular vision system for sugarcane harvesting robots, using an improved YOLOv4 architecture to accurately locate sugarcane nodes even when obscured by leaves. This work, cited 21 times, addresses the critical challenge of spatial localization in complex field conditions, directly advancing the feasibility of autonomous harvesting. In underwater robotics, Wu has made significant contributions to 2D forward-looking sonar perception, addressing the inherent problem of missing elevation angle information. Their self-supervised learning approach for elevation estimation, cited 8 times, enables more reliable 3D mapping and navigation for underwater vehicles. Wu also developed a sonar simulation framework with ground echo modeling, cited 5 times, providing a valuable tool for testing perception algorithms without costly field deployments. By advancing both agricultural robotics and underwater perception, Wu demonstrates a versatile approach to solving real-world sensing challenges, with their work laying essential groundwork for more autonomous, intelligent robots operating in unstructured environments.