Chunpeng Yao

Papers

Total Citations

H-Index

About

Chunpeng Yao’s research lies at the intersection of computer vision, robotics, and intelligent game systems. His most cited work, “Visual Image Processing of Humanoid Go Game Robot Based on OPENCV” (2020, 9 citations), tackles a core challenge in humanoid robotics: extracting and interpreting complex visual information from physical game boards. Yao proposed a Python-based chessboard recognition method that uses projection transformation for image correction and binarization for enhancement, enabling a humanoid robot to accurately perceive and interact with a Go board. This contribution is significant because it bridges the gap between abstract AI game algorithms and real-world robotic manipulation, making autonomous gameplay more feasible. Beyond this flagship paper, Yao’s broader research explores how visual processing can be optimized for humanoid platforms, emphasizing practical, low-cost solutions. His work has been cited by researchers developing similar robotic systems for board games and other structured environments, highlighting its impact on applied computer vision. Yao’s achievements demonstrate a commitment to making intelligent robots more perceptive and autonomous, offering valuable insights for students and engineers interested in robotics, image processing, and human-machine interaction.