Papers
6
Total Citations
66
H-Index
5
About
Zefeng Xu is a pioneering researcher at the intersection of soft robotics, intelligent control, and functional materials. Their work addresses fundamental challenges in robotic manipulation and locomotion, particularly for soft and flexible systems. Xu’s major contributions include developing a nonlinear nonsingular fast terminal sliding mode controller enhanced by deep reinforcement learning (24 citations), which significantly reduces chattering and improves tracking accuracy in industrial robots. They have also advanced soft robotic control through hybrid modeling and reinforcement learning (17 citations), enabling precise manipulation of highly deformable arms. In materials science, Xu created strong, tough hydrogels synergizing fiber reinforcement with metal-ligand bonds (11 citations), demonstrating exceptional gauge factor for wearable strain sensors. Their bio-inspired designs include a manta ray-inspired soft robotic swimmer achieving high-speed, multi-modal swimming via bistable flapping wings (6 citations), and a soft gripper integrating mechanically-prestressed actuators for rapid, robust grasping (5 citations). Xu’s work bridges control theory, soft robotics, and smart materials, with cumulative citations exceeding 60, reflecting significant impact in advancing dexterous, adaptive robotic systems for real-world applications.
Research Focus
Key Achievements
Top Papers
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- 5A soft gripper integrated with mechanically-prestressed soft actuators5 citations · 2022
- 6Dynamics Analysis of a Novel 3-PSS Parallel Robot Based on Linear Motor3 citations · 2020