Papers
10
Total Citations
363
H-Index
8
About
Yingtian Xu is a leading researcher at the intersection of soft robotics, tactile sensing, and intelligent perception, with a focus on bridging the gap between artificial and human-like sensory capabilities. Their work centers on developing advanced soft sensors and actuators, particularly through vat photopolymerization 3D printing, enabling the fabrication of flexible, stretchable devices for wearable electronics and soft robotics. Xu’s major contributions include pioneering wide-range-tunable ionic hydrogel strain sensors, which achieve exceptional gauge factor control through a road-narrow-inspired strain concentration design (54 citations), and creating biomimetic mechanoreceptors for self-adaptive perception of object deformability (18 citations). Their impact is evident in highly cited reviews on perceptive intelligence for soft robotics (73 citations) and machine learning for tactile perception (64 citations), which have shaped the field’s direction. Notably, Xu has developed innovative applications such as flexible multimodal sole sensors for legged robots to sense complex ground information, hierarchically porous piezoresistive sensors for climbing robots, and augmented pointing gesture estimation for human-robot interaction. Their recent work on robot embodied dynamic tactile perception of liquid in containers (2024) further demonstrates their commitment to advancing closed-loop control and autonomous interaction. With over 360 total citations across their top papers, Xu’s research is driving the next generation of intelligent, perceptive soft systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Recent Advances in Perceptive Intelligence for Soft Robotics73 citations · 2023
- 3
- 4
- 5
- 6
- 7
- 8
- 9Augmented Pointing Gesture Estimation for Human-Robot Interaction6 citations · 2022
- 10Robot Embodied Dynamic Tactile Perception of Liquid in Containers4 citations · 2024