Papers
38
Total Citations
1,519
H-Index
17
About
Gu Fang is a versatile robotics and computer vision researcher whose work spans autonomous systems, robotic welding automation, and intelligent sensing. He is perhaps best known for his pioneering contributions to human object recognition using RGB-D sensing, with his 2013 study on Kinect-based human tracking accumulating an impressive 365 citations — a testament to its relevance across robotics and automation communities. Alongside this, Gu Fang has made substantial strides in robotic arc welding, developing vision-based systems for autonomous weld seam detection, tracking, and path planning. His suite of highly cited papers in this domain — spanning stereo vision, real-time image processing, and adaptive seam detection algorithms — has helped define modern approaches to robotic GMAW and GTAW processes, collectively attracting hundreds of citations. Earlier in his career, Gu Fang tackled fundamental challenges in mobile robotics, contributing a notable investigation into multi-step look-ahead trajectory planning for EKF-based SLAM. He has also applied evolutionary computation to image enhancement, demonstrating a breadth of expertise that bridges perception, planning, and intelligent optimization — making him a significant contributor to applied robotics research.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Computer vision technology for seam tracking in robotic GTAW and GMAW137 citations · 2014
- 4Real-time image processing for vision-based weld seam tracking in robotic GMAW116 citations · 2014
- 5Welding seam tracking in robotic gas metal arc welding96 citations · 2017
- 6Multi-Step Look-Ahead Trajectory Planning in SLAM: Possibility and Necessity82 citations · 2006
- 7
- 8
- 9Passive vision based seam tracking system for pulse-MAG welding59 citations · 2012
- 10Automatic Seam Detection and Path Planning in Robotic Welding35 citations · 2011