Mingxiang Zhu
Papers
1
Total Citations
5
H-Index
1
About
Dr. Mingxiang Zhu is a pioneering researcher in construction robotics and intelligent automation, with a specialized focus on integrating computer vision and machine learning for autonomous building systems. His work centers on developing robust perception algorithms that enable construction robots to interpret complex, unstructured environments. Dr. Zhu’s most notable contribution is his 2022 paper, "Object Segmentation by Spraying Robot Based on Multi-Layer Perceptron," which proposes a novel vision system that jointly analyzes construction environment characteristics, object properties, and robot structure to accurately segment and locate objects for automated spraying tasks. This approach has garnered 5 citations, establishing a foundation for practical robot deployment in dynamic construction sites. His research bridges the critical gap between theoretical computer vision and real-world construction applications, addressing challenges such as variable lighting, irregular object geometries, and spatial constraints. By advancing multi-layer perceptron-based segmentation for construction robots, Dr. Zhu is helping to pave the way for safer, more efficient automated building processes. His work is particularly valuable for students and researchers exploring the intersection of robotics, deep learning, and civil infrastructure automation.
Research Focus
Key Achievements
Top Papers
- 1Object Segmentation by Spraying Robot Based on Multi-Layer Perceptron5 citations · 2022