Lingyun Zeng
Papers
5
Total Citations
28
H-Index
4
About
Lingyun Zeng is a robotics researcher whose work focuses on the modeling, control, and design of continuum robots for surgical and industrial applications. His research spans kinetostatic modeling, state estimation, and haptic feedback systems, with a particular emphasis on enabling precise manipulation in confined and unstructured environments. Zeng’s most cited work introduces a model-based estimation method for gravity-loaded shape and scene depth in slim continuum robots using monocular visual feedback (10 citations), addressing a fundamental challenge in soft robotic control. He further advanced the field with the kinetostatic modeling of the continuum Delta robot, CurviPicker, designed for pick-and-place tasks (7 citations). A notable methodological contribution is his application of the Koopman operator-based extended Kalman filter for wrench estimation in Cosserat rods (5 citations), offering a data-driven approach to force sensing. Zeng also contributed to surgical robotics through the design of ParaMaster, a haptic device for teleoperation (4 citations), and a sliding-pin needle driver for continuum surgical robots (2 citations). His work bridges theoretical modeling with practical robotic systems, demonstrating impact in both industrial automation and minimally invasive surgery.
Research Focus
Key Achievements
Top Papers
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- 5Design of a Sliding-Pin Needle Driver for a Continuum Surgical Robot2 citations · 2018