Qing Gui Wu
Papers
1
Total Citations
2
H-Index
1
About
Qing Gui Wu is a robotics researcher specializing in autonomous navigation and computer vision for mobile robots. Their work focuses on enabling robots to operate effectively in unknown environments, particularly addressing the challenge of obstacle avoidance using monocular vision systems. Wu's most cited paper, "Autonomous Obstacle Avoidance Scheme Using Monocular Vision Applied to Mobile Robots" (2021), proposes an enhanced strategy that combines Canny edge detection with Otsu's thresholding to extract barrier features and identify critical pixels for navigation. This approach allows mobile robots to navigate around static or slow-moving obstacles without relying on expensive depth sensors. While their citation count remains modest at 2, the work represents a practical contribution to low-cost, vision-based robotic navigation. Wu's research sits at the intersection of computer vision and robotics, offering accessible solutions for autonomous systems in unstructured environments—a growing area of interest for students and researchers working on affordable mobile robot platforms.
Research Focus
Key Achievements
Top Papers
- 1