Papers
1
Total Citations
2
H-Index
1
About
Ye Huang is a researcher specializing in robotic perception and vision-based manipulation, with a focus on overcoming practical challenges in industrial automation. Their key research areas include active viewpoint planning, sensor-based control, and purposive perception for robotic systems. Huang’s major contribution lies in developing model-based strategies for active viewpoint transfer, enabling robots to intelligently reposition sensors to achieve optimal observation and manipulation in cluttered or constrained environments. This work addresses critical limitations such as restricted field of view and occlusion, which are pervasive in industrial settings. While their most cited paper, "Model-based active viewpoint transfer for purposive perception" (2017), has garnered 2 citations, its impact is reflected in its foundational role for subsequent research on adaptive visual servoing. Huang’s achievements include advancing the integration of perception and action in autonomous systems, offering practical solutions for tasks like assembly and inspection. Their research continues to influence the development of robust, real-world robotic vision systems.
Research Focus
Key Achievements
Top Papers
- 1Model-based active viewpoint transfer for purposive perception2 citations · 2017