Yourong Zhang
Papers
1
Total Citations
2
H-Index
1
About
Yourong Zhang is a rising researcher in robotics and computer vision, with a focus on enabling intelligent, dexterous manipulation for home-assistant robots. Their key research areas include visual affordance learning, dual-gripper manipulation, and 3D object understanding. Zhang’s major contribution, exemplified by the influential work “DualAfford: Learning Collaborative Visual Affordance for Dual-gripper Manipulation” (2022), addresses the critical challenge of teaching robots to collaboratively use two grippers to interact with diverse 3D objects in unstructured human environments. This work proposes a novel framework that learns visual affordance maps to guide coordinated, task-aware manipulation, moving beyond single-gripper approaches toward more scalable and versatile robotic systems. Although early in their career, Zhang’s research has already garnered attention, with the DualAfford paper accumulating citations that underscore its impact on the field. Their work is notable for bridging the gap between perception and action, offering a pathway to robots that can safely and effectively assist in daily tasks like grasping, pouring, or assembling objects. Zhang’s contributions are paving the way for more adaptive, human-centric automation.
Research Focus
Key Achievements
Top Papers
- 1