Yihan Meng
Papers
1
Total Citations
7
H-Index
1
About
Yihan Meng is a rising researcher at the intersection of soft robotics, biomimetics, and deep learning, with a focus on advancing the sensing and control capabilities of bio-inspired robotic systems. Their most cited work introduces a novel deep learning-based method for 3D pose reconstruction of an underwater soft robotic hand, addressing a critical bottleneck in the field: the difficulty of accurately sensing and reconstructing the complex, continuous deformations of soft structures during grasping tasks. By combining computer vision techniques with biomimetic evaluation, Meng’s approach enables precise motion analysis without relying on traditional, often restrictive, embedded sensors. This contribution is particularly significant for the design and fabrication of next-generation soft grippers intended for delicate underwater manipulation. With 7 citations on this foundational paper, Meng’s research is gaining traction among engineers and roboticists working on autonomous underwater vehicles and soft haptic interfaces. Their work exemplifies a growing trend toward integrating data-driven methods with soft material systems, promising more adaptive and resilient robotic hands for real-world aquatic environments.
Research Focus
Key Achievements
Top Papers
- 1