Tzu-Yuan Lin
Papers
7
Total Citations
65
H-Index
5
About
Tzu-Yuan Lin is a robotics researcher specializing in state estimation, proprioceptive perception, and symmetry-aware control for mobile and legged robots. His work centers on developing robust, fully proprioceptive estimators that operate without reliance on external sensors like vision, making them resilient in perceptually degraded environments. Lin’s major contributions include the creation of slip-velocity-aware state estimators using invariant Kalman filtering and disturbance observers, which enable accurate robot localization even on slippery or uneven terrain. He has also pioneered learning-based contact estimators that leverage deep multi-modal proprioceptive data to replace physical contact sensors, enhancing legged robot autonomy. His research extends to tensegrity robots and non-inertial environments, addressing complex kinematic and dynamic challenges. With over 65 citations across his most-cited works, Lin’s impact is evident in advancing geometric and learning-based methods for robot perception and control. Notably, his 2023 paper on slip estimation has garnered 17 citations, reflecting its significance in the field. Lin’s work bridges theory and practice, offering elegant solutions grounded in symmetry and geometry for next-generation robotic systems.
Research Focus
Key Achievements
Top Papers
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- 7Legged Robot State Estimation within Non-inertial Environments3 citations · 2024