Papers
13
Total Citations
403
H-Index
10
About
Xuhui Ye is a prominent researcher specializing in intelligent inspection systems, computer vision, and robotics for high-voltage power transmission infrastructure. His work sits at the intersection of LiDAR sensing, deep learning, and autonomous robotic systems, with a consistent focus on solving real-world challenges in power grid monitoring and maintenance. Ye's most influential contributions include pioneering methods for reconstructing and autonomously inspecting overhead power lines using LiDAR point cloud data, works that have garnered 64 and 65 citations respectively, establishing him as a key voice in remote sensing applications for energy infrastructure. His 2022 deep learning framework for detecting transmission line targets and defects has already accumulated 102 citations, underscoring the field's rapid embrace of AI-driven inspection approaches. Beyond detection, Ye has advanced RGB-D semantic segmentation for mobile robots, robust motion control for live-line maintenance arms, and wireless sensor network integration for smart grids. What distinguishes Ye's body of work is its consistent practical orientation — addressing hazardous, labor-intensive tasks in complex environments such as mountains and forests through automation. With over 390 cumulative citations across his key publications, his research has meaningfully shaped how the power industry approaches the safety, reliability, and efficiency of transmission line inspection.
Research Focus
Key Achievements
Top Papers
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- 6Dynamic Barrier Coverage in a Wireless Sensor Network for Smart Grids26 citations · 2018
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