Yun Yun Song
Papers
1
Total Citations
2
H-Index
1
About
Yun Yun Song is a robotics researcher specializing in autonomous navigation and computer vision for mobile systems. Her primary research focuses on developing intelligent obstacle avoidance strategies that enable robots to operate safely in unknown environments. In her most cited work, "Autonomous Obstacle Avoidance Scheme Using Monocular Vision Applied to Mobile Robots" (2021), Song introduced an enhanced approach that combines Canny edge detection with Otsu’s thresholding method to extract barrier features and identify critical pixels from monocular camera input. This contribution addresses a fundamental challenge in mobile robotics—navigating static or slow-moving obstacles without expensive sensor suites. While her citation count is currently modest, Song’s work represents a practical, cost-effective solution for real-world robotic applications, demonstrating her commitment to accessible and efficient autonomous systems. Her research holds promise for advancing mobile robot deployment in dynamic environments, from warehouse logistics to service robotics.
Research Focus
Key Achievements
Top Papers
- 1