Papers
1
Total Citations
7
H-Index
1
About
Duo Wang is a robotics researcher whose work centers on human-robot interaction, computer vision, and autonomous navigation. His most cited paper, "Person detection, tracking and following using stereo camera" (2018, 7 citations), addresses a critical enabling technology for mobile robots: the ability to detect, track, and follow humans in real-world environments. By integrating YOLO-based visual detection with stereo camera data and video tracking algorithms, Wang developed a robust system that allows robots to maintain persistent, safe following behavior—a foundational capability for applications in service robotics, healthcare, and collaborative manufacturing. This work demonstrates his strength in combining deep learning with classical robotics pipelines to solve practical perception and control challenges. While his citation count is modest, the paper’s focus on a widely needed functionality positions it as a useful reference for researchers building interactive robotic systems. Wang’s contributions highlight the importance of reliable person-following as a stepping stone toward more natural and autonomous human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1Person detection, tracking and following using stereo camera7 citations · 2018