Yanran Wei
Papers
4
Total Citations
59
H-Index
4
About
Yanran Wei is a rising leader in the field of robotic manipulation and haptic sensing, with a research focus on contact force estimation, disturbance rejection, and environmental interaction for robot manipulators. Her work addresses a critical challenge in robotics: accurately estimating interaction forces when dynamic models are imperfect or incomplete. Wei’s most cited paper, “Contact Force Estimation of Robot Manipulators With Imperfect Dynamic Model: On Gaussian Process Adaptive Disturbance Kalman Filter” (2023, 45 citations), introduces a hybrid model that fuses nominal dynamics with residual learning, enabling robust force estimation under uncertainty. She further advances this line of inquiry with a composite disturbance filtering approach that simultaneously estimates interaction forces and explores environmental stiffness—a key capability for minimally invasive surgery. Her decoupling observer based on an enhanced Gaussian process model (2022) and her recent work on image-to-force estimation using structured light (2025) demonstrate a sustained commitment to bridging model-based and data-driven methods. With a growing citation impact and applications in surgical robotics, Wei is establishing herself as a key innovator in safe, sensor-free haptic feedback for next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
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