Xiaohai He
Papers
2
Total Citations
17
H-Index
1
About
Xiaohai He is a robotics and computer vision researcher whose work focuses on integrating perception and automation for real-world applications. His primary research areas include machine vision, robotic manipulation, and deep learning for autonomous systems. He is best known for developing a rebar-tying robot that combines machine vision with coverage path planning, a practical innovation that has already garnered 16 citations since its 2024 publication. This work addresses critical challenges in construction automation by enabling robots to navigate complex environments and perform precise tying tasks. More recently, He proposed YOLO-FS, a unified framework that jointly performs object detection and semantic segmentation, bridging the gap between object localization and pixel-level scene understanding. This model enhances environmental awareness for robot navigation and autonomous driving, representing a significant step toward more intelligent perception systems. Though early in his career, He’s contributions demonstrate a clear trajectory toward impactful, application-driven research that merges theoretical advances with tangible robotic solutions.
Research Focus
Key Achievements
Top Papers
- 1Rebar-tying Robot based on machine vision and coverage path planning16 citations · 2024
- 2