Xiwen Dengxiong
Papers
1
Total Citations
6
H-Index
1
About
Xiwen Dengxiong is a robotics researcher whose work centers on advancing robot manipulation through self-supervised learning and intuitive human-robot interaction. His key contributions lie in developing methods that reduce the need for costly, labor-intensive supervision in robotic grasping. In his most-cited paper, "Self-supervised 6-DoF Robot Grasping by Demonstration via Augmented Reality Teleoperation System" (2024, 6 citations), he tackles a critical bottleneck in robotics: enabling robots to learn precise, six-degree-of-freedom grasp poses without strong external labels. By combining augmented reality teleoperation with self-supervised learning, his framework allows robots to acquire dexterous grasping skills from human demonstrations in restricted or complex environments, making the process more practical and scalable. This work exemplifies his broader focus on bridging the gap between human intuition and autonomous robot learning. Though early in his career, Dengxiong’s research has already drawn attention for its potential to democratize robot training, offering a path toward more adaptable and cost-effective robotic systems in manufacturing, logistics, and assistive technologies.
Research Focus
Key Achievements
Top Papers
- 1