Pengwen Sun
Papers
1
Total Citations
35
H-Index
1
About
Pengwen Sun is a leading researcher in intelligent robotic manipulation and digital twin technologies, with a focus on bridging simulation and real-world robotic systems. Their most influential work introduces a grasps-generation-and-selection convolutional neural network designed for the digital twin of intelligent robotic grasping—a breakthrough that enhances robots' ability to autonomously plan and execute precise grasps in dynamic environments. This paper, with 35 citations, has become a cornerstone for researchers developing more adaptive and reliable robotic systems. Sun’s contributions are particularly notable for integrating deep learning with digital twin frameworks, enabling real-time simulation-to-reality transfer that reduces the gap between virtual training and physical deployment. Their work directly impacts industries such as manufacturing, logistics, and service robotics, where efficient grasping is critical. By advancing how robots perceive and interact with objects, Pengwen Sun is shaping the future of autonomous manipulation, making their research essential reading for students and engineers exploring the intersection of AI, robotics, and digital twins.
Research Focus
Key Achievements
Top Papers
- 1