Papers
1
Total Citations
21
H-Index
1
About
Xiao Bing Wu is a leading researcher in agricultural robotics, with a focus on enabling robust autonomous navigation in complex orchard environments. His work addresses critical challenges such as uneven terrain, variable lighting, and unreliable GPS signals by developing innovative perception and control systems. Wu’s most cited paper, “Deep-Learning-Based Trunk Perception with Depth Estimation and DWA for Robust Navigation of Robotics in Orchards” (2023, 21 citations), introduces a novel approach that combines deep learning for trunk detection with depth estimation and the Dynamic Window Approach (DWA) for real-time path planning. This work provides a reliable landmark-based navigation solution, significantly improving robot operability under harsh field conditions. By integrating advanced computer vision and adaptive control, Wu’s contributions help bridge the gap between laboratory research and practical agricultural applications, offering a scalable framework for precision farming. His research is highly relevant for students and engineers working on field robotics, sensor fusion, and AI-driven automation in unstructured environments.
Research Focus
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Top Papers
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