Xiaoke Yang
Papers
1
Total Citations
6
H-Index
1
About
Xiaoke Yang is a researcher whose work has centered on robotics and computer vision, with a particular focus on autonomous navigation and sensor-based control. Their most notable contribution, "Robotic Vehicle Navigation Based on Image Processing Using Kinect" (2016), explored the use of Microsoft Kinect’s depth-sensing technology to enable real-time obstacle detection and path planning for robotic vehicles. By leveraging depth maps to interpret environmental range data, Yang proposed a practical approach to improving robotic autonomy in dynamic settings. Although the paper has since been retracted, it has accumulated 6 citations, reflecting initial interest in the integration of consumer-grade sensors for navigation tasks. Yang’s research highlights the challenges and potential of low-cost vision systems in robotics, contributing to broader discussions on accessible automation. This work underscores a commitment to advancing intelligent vehicle control through image processing, offering insights for students and researchers exploring sensor fusion and real-time navigation in constrained environments.
Research Focus
Key Achievements
Top Papers
- 1