HanBo Zhang
Papers
1
Total Citations
3
H-Index
1
About
HanBo Zhang is a researcher whose work sits at the intersection of computer vision and robotic manipulation, with a particular focus on enabling robots to operate intelligently in cluttered, real-world environments. His key research areas include visual reasoning for robotic grasping, multi-object scene understanding, and the integration of perception with physical action. Zhang’s most notable contribution is his framework for robotic grasping in multi-object stacking scenes, which uses a two-stage visual reasoning approach—perception followed by execution—to allow a robot to identify and grasp a target object even when it is partially obscured or surrounded by others. This work, published in 2018, has garnered 3 citations and represents an early step toward more adaptive and context-aware robotic systems. By moving beyond simple single-object grasping, Zhang addresses a critical challenge in automation and logistics. His research is particularly valuable for students and engineers interested in bridging the gap between high-level visual understanding and low-level robotic control, demonstrating how reasoning about spatial relationships can directly inform physical interaction with the world.
Research Focus
Key Achievements
Top Papers
- 1