Papers
1
Total Citations
5
H-Index
1
About
Na Wei is an emerging researcher in the field of robotics and human-robot interaction, with a particular focus on dexterous manipulation and skill transfer. Her work centers on bridging the gap between human motor capabilities and robotic systems, developing innovative methods that allow robots to learn complex grasping behaviors directly from human demonstration. Her most notable contribution, "Learn to Grasp Objects with Dexterous Robot Manipulator from Human Demonstration" (2022), introduces a framework leveraging Dynamic Motion Primitives (DMPs) to model and replicate 3D trajectories from human-guided demonstrations, enabling intuitive programming of robotic manipulators without requiring deep technical expertise from users. This approach represents a significant step forward in making dexterous robotic manipulation more accessible and adaptable across real-world applications. With early citation traction in a highly competitive field, Wei's research is gaining recognition within the robotics community. Her work holds particular promise for applications in assistive robotics, industrial automation, and teleoperation, where seamless human-to-robot skill transfer is critical. As her research portfolio continues to grow, Na Wei is establishing herself as a promising voice in intelligent robotic systems and learning-from-demonstration methodologies.
Research Focus
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Top Papers
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