Papers
23
Total Citations
291
H-Index
11
About
Pengwen Xiong is a leading researcher in robotics and haptic perception, whose work bridges the gap between machine sensing and human-like interaction. His core research areas include haptic actuation, cross-modal material perception, and robotic grasping, with a focus on enabling robots to understand and manipulate objects as adeptly as humans. Xiong’s major contributions include developing a multidirectional spherical MR actuator for haptic applications (36 citations), which enhances force output and stability in compact designs, and pioneering a deeply supervised subspace learning method for cross-modal material perception (35 citations), allowing robots to identify known and unknown objects via noncontact sensors. His work on human-exploratory-procedure-based hybrid measurement fusion (24 citations) and adaptive multikernel dictionary learning for multifinger grasping (22 citations) has advanced tactile exploration and object recognition. Notably, Xiong has also contributed to rehabilitation robotics, with a hierarchical safety supervisory control strategy (17 citations) ensuring patient safety during robot-assisted therapy. With over 230 total citations, his research is widely recognized for its practical impact on service robots, prosthetics, and teleoperation systems, making him a key figure in the evolution of intelligent robotic perception and control.
Research Focus
Key Achievements
Top Papers
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- 7Robotic Object Perception Based on Multispectral Few-Shot Coupled Learning19 citations · 2023
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