Yanran Long
Papers
1
Total Citations
3
H-Index
1
About
Yanran Long’s research centers on human-robot interaction, assistive robotics, and sensor-based control systems, with a particular focus on medical care applications. Their most cited work, “Kinect-based Human Body Tracking System Control of Medical Care Service Robot” (2018), introduces a novel approach to enabling service robots to follow human targets in real time. By integrating Kinect v2 depth sensors with an improved Gaussian filter for noise reduction and a Kalman filter for motion prediction, Long developed a robust tracking system that enhances robot autonomy in clinical environments. This contribution addresses critical challenges in healthcare robotics, such as safe and responsive patient monitoring. Although early in their career, Long’s work has already garnered attention, with this paper receiving 3 citations—a meaningful start for a specialized technical contribution. Their research bridges computer vision, sensor fusion, and control engineering, offering practical solutions for elderly care and rehabilitation. Long’s focus on real-time, low-cost tracking systems positions them as an emerging voice in assistive robotics, with potential to impact both academic research and real-world medical service deployments.
Research Focus
Key Achievements
Top Papers
- 1