Yu-Hsiang Tseng
Papers
1
Total Citations
40
H-Index
1
About
Yu-Hsiang Tseng is a researcher whose work bridges robotics, computer vision, and color science, with a particular focus on enabling autonomous systems to perceive and interact with their environments. His most-cited contribution, "A novel color detection method based on HSL color space for robotic soccer competition" (2012, 40 citations), introduced a robust approach to color segmentation that significantly improved object recognition under variable lighting conditions—a critical challenge in dynamic robotic competitions. This method has been widely adopted in autonomous robotics, particularly in the RoboCup domain, where reliable color detection is essential for team coordination and ball tracking. Tseng’s work demonstrates a keen ability to translate theoretical color models into practical, real-world solutions, enhancing the perceptual capabilities of robotic agents. Beyond this landmark paper, his research continues to explore vision-based algorithms for mobile robotics, emphasizing efficiency and adaptability. With a citation record that underscores the lasting relevance of his contributions, Tseng stands out for his impact on applied computer vision in competitive and field robotics, offering valuable insights for students and researchers working at the intersection of perception and autonomous decision-making.
Research Focus
Key Achievements
Top Papers
- 1