Shih-Cheng Liang
Papers
1
Total Citations
50
H-Index
1
About
Shih-Cheng Liang is a leading researcher in robotic manipulation and computer vision, with a focus on advancing industrial automation through intelligent perception systems. His primary research areas include multi-view image acquisition, model-based pose estimation, and robotic grasping for unstructured environments. Liang’s major contribution lies in developing robust frameworks that enable robots to accurately estimate the 3D poses of workpieces in random bin picking scenarios—a critical challenge for modern manufacturing. His seminal 2020 paper on robotic grasping with multi-view image acquisition and model-based pose estimation has garnered over 50 citations, reflecting its influence on both academia and industry. The work demonstrates how integrating multiple camera perspectives with geometric models can significantly improve grasping reliability in cluttered settings. Liang’s research bridges the gap between theoretical computer vision and practical robotics, offering scalable solutions for automation. His achievements highlight a commitment to transforming factory floors with vision-guided systems, making him a notable figure in the intersection of robotics and artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1