Papers
4
Total Citations
12
H-Index
2
About
Guanran Pei is pioneering the intersection of soft robotics and embodied intelligence, with a focus on solving the fundamental challenges of sensing, control, and durability in compliant systems. Their most impactful work introduces a novel approach to pose reconstruction for soft continuum manipulators using IMU-based proprioception, achieving 6 citations for a 2024 paper that demonstrates closed-loop control of these highly deformable arms. Pei’s research addresses the core paradox of soft robotics: the very flexibility that makes these systems robust also makes them difficult to model and control. By developing a polynomial curvature model, they enable accurate shape estimation even under external forces, a critical step toward practical deployment. Beyond sensing, Pei tackles the often-overlooked issue of long-term reliability, identifying durability challenges in architectured materials for large-scale soft robots. Their most recent work draws inspiration from plant gravitropism to create a decentralized controller for robust orientation control, mimicking nature’s distributed intelligence. With a rapidly growing citation record and a clear trajectory from fundamental sensing to system-level robustness, Pei is establishing themselves as a key voice in making soft robots not just capable, but reliable and enduring.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4