Wenning Huang
Papers
1
Total Citations
4
H-Index
1
About
Wenning Huang is a researcher at the forefront of intelligent infrastructure inspection, specializing in the integration of mobile robotics, computer vision, and deep learning for civil engineering applications. His most-cited work, "Road Crack Acquisition and Analysis System Based on Mobile Robot and Deep Learning" (2021), introduces a novel system that combines a virtual reality-controlled omnidirectional mobile robot with advanced deep learning algorithms to autonomously capture and analyze road crack images. This contribution addresses a critical need for efficient, remote, and accurate pavement distress detection, reducing reliance on manual inspection. With 4 citations, this paper has laid foundational groundwork for automated infrastructure health monitoring. Huang’s research bridges the gap between robotics and structural assessment, offering scalable solutions for smart city maintenance. His achievements include developing a remote data acquisition framework that enhances safety and precision in road evaluation, positioning him as an emerging innovator in the field of intelligent transportation systems and robotic sensing.
Research Focus
Key Achievements
Top Papers
- 1