Papers
5
Total Citations
119
H-Index
5
About
Dongxu Pan is a rising researcher at the forefront of intelligent construction automation, specializing in machine vision, deep learning, and robotic control for concrete vibration processes. His work addresses critical challenges in construction quality control by developing advanced algorithms that enable precise, automated monitoring and manipulation of concrete during placement. Pan’s most influential contribution is the **SDS-YOLO** algorithm (2024), an improved object detection framework based on YOLOv11 that achieves 74 citations for its robust vibratory position detection. He further advanced the field with a **temporal fusion strategy** for monitoring vibration quality (14 citations) and a **precise control mode** using attention-enhanced vision (20 citations), demonstrating how deep learning can replace subjective manual inspection. His recent work on **Euclidean Signed Distance Fields** and **vector safety flight corridors** (2025) introduces efficient collision-avoidance path planning for construction robots, enabling flexible and safe autonomous operation. With a cumulative citation count exceeding 120 in just two years, Pan’s research is rapidly shaping the next generation of intelligent construction equipment, offering scalable solutions for safer, more consistent concrete work.
Research Focus
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