Mingshuo Han
Papers
2
Total Citations
71
H-Index
2
About
Mingshuo Han is a leading researcher at the forefront of physical Human-Robot Interaction (pHRI) and intelligent robotic manipulation. His work is centered on solving the fundamental challenge of enabling robots to perceive and interact with their environment safely and efficiently. Han’s most impactful contribution is his comprehensive review on multimodal fusion methods in pHRI, which has garnered 68 citations and serves as a critical roadmap for the field, highlighting how integrating vision, touch, and force data is key to achieving seamless human-robot collaboration. In his innovative work on robotic grasping, Han introduced the "Bayesian Grasp" framework, a novel approach that uses prior tactile knowledge to predict stable grasps from visual input alone. This method significantly reduces the need for time-consuming physical regrasping, marking a major step toward more efficient and autonomous manipulation in unstructured environments. By bridging the gap between sensing and action, Mingshuo Han is shaping the future of robots that can work alongside humans with unprecedented dexterity and understanding.
Research Focus
Key Achievements
Top Papers
- 1
- 2