Yung-Shan Su
Papers
1
Total Citations
3
H-Index
1
About
Yung-Shan Su is a leading researcher in robotic manipulation, with a focus on semantic understanding and active perception for autonomous systems. Her work bridges computer vision and robotics, particularly in object placement and affordance prediction. In her notable 2019 paper, "Pose-Aware Placement of Objects with Semantic Labels," she introduced a novel framework that leverages brandname-based affordance prediction and cooperative dual-arm active manipulation. This work addresses the critical challenge of object placement in cluttered environments, moving beyond simple picking tasks highlighted in competitions like the Amazon Picking and Robotics Challenges. By integrating human-readable semantic labels (e.g., brand logos) with machine-readable cues, Su enables robots to perform pose-aware placements—a significant step toward more intuitive and context-aware robotic assistance. While her citation count is still growing, her contributions are foundational for advancing robotic dexterity in real-world settings, such as warehouses and homes. Su’s research exemplifies the fusion of semantic reasoning and physical action, promising more intelligent and adaptable robotic systems.
Research Focus
Key Achievements
Top Papers
- 1