Papers
8
Total Citations
36
H-Index
3
About
Xiaojie Chai’s research is centered on the intersection of computer vision, robotics, and autonomous navigation, with a particular focus on enabling intelligent perception and motion for mobile and industrial robots. A key contribution is the development of the MR (Mobile Robot) code, a novel artificial landmark system that provides a practical, paper-based solution for indoor robot localization and visual SLAM. This work, detailed in her most-cited paper (2009, 10 citations), laid the foundation for robust topological navigation. Chai has also pioneered vision-based techniques for industrial automation, including a fast 3D surface reconstruction method using Time-of-Flight cameras for spraying robots (2013, 7 citations) and an algorithm for rapid, automatic generation of spraying instructions from 3D models (2014, 3 citations). Her research extends to natural landmark detection via fast object segmentation (2011, 7 citations) and motion planning for vision-based stevedoring tasks (2015, 2 citations). With over 36 total citations across her published works, Chai’s contributions are particularly notable for bridging the gap between theoretical computer vision algorithms and practical, real-world robotic applications in manufacturing and logistics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6Motion planning for vision-based stevedoring tasks on industrial robots2 citations · 2015
- 7An improved visual SLAM algorithm based on mixed data association2 citations · 2011
- 8A visual SLAM algorithm based on a novel artificial landmark system2 citations · 2010