Papers
13
Total Citations
218
H-Index
8
About
Longhui Qin is a leading researcher at the intersection of soft robotics, tactile sensing, and computational mechanics, whose work bridges the gap between biological inspiration and engineered dexterity. His major contributions span three interconnected domains: the physics-based simulation of soft robotic systems, the design of bio-inspired tactile sensors, and the machine-learning-driven manipulation of deformable objects. Notably, his highly cited 2023 review on numerical approaches for soft robot dynamics (68 citations) has become a foundational resource for the field, systematically addressing the nonlinear modeling challenges that hinder real-world deployment. Qin’s innovative sensor designs—including micropyramidal capacitive pressure sensors and bioinspired tactile fingertips—have achieved remarkable surface roughness discrimination and force perception, with his 2017 work on enhanced tactile feature extraction (33 citations) setting a benchmark for texture recognition. His recent Sim2Real neural controllers (2023) demonstrate the first successful transfer of learned policies for deploying cables and rods from simulation to physical robots, a critical step toward autonomous manufacturing. With over 200 total citations and a 2025 breakthrough in contact-dominated pressure sensing, Qin continues to push the boundaries of how robots feel and interact with their environment.
Research Focus
Key Achievements
Top Papers
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- 5Surface Recognition With a Bioinspired Tactile Fingertip17 citations · 2023
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