Sungho Shin
Papers
2
Total Citations
7
H-Index
2
About
Sungho Shin is a researcher whose work spans the intersection of robotics engineering and intelligent systems, with contributions to both mechanical design methodologies and computer vision applications in robotics. In the domain of modular robotics, Shin developed analytical frameworks for designing modular robot interfaces, presenting simplified formulations that relate critical design parameters — including contact stiffness, geometric dimensions, and dimensional tolerances — to the positional and orientational accuracy of connected interfaces. This practical approach aids engineers during the initial phases of modular system design. More recently, Shin has turned attention to advancing robotic task planning through machine learning, contributing a novel object detection pipeline for interpreting 2D assembly instruction images. By combining context-aware data augmentation with Cascade Mask R-CNN, this work enables robots to extract key visual and textual components from instructional diagrams, pushing forward the frontier of autonomous assembly understanding. While still building a citation footprint — with his most recognized works accumulating citations in the range of three to four — Shin's research reflects a thoughtful progression from foundational mechanical analysis toward cutting-edge AI-driven robotics, making his profile of growing interest to researchers in intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2