Juncheng Lin
Papers
3
Total Citations
38
H-Index
3
About
Juncheng Lin is an emerging researcher specializing in safety-critical control for robotic systems, with a particular focus on addressing the fundamental challenges posed by uncertain dynamic models and incomplete state measurements in real-world robotics applications. His work sits at the intersection of control theory and robotics, leveraging advanced mathematical frameworks to ensure robots operate safely under practical constraints. Lin's most significant contributions center on the development and application of Control Barrier Functions (CBFs) and High-Order Control Barrier Functions (HOCBFs) for robotic manipulators. His double-level safety-critical control framework addresses the pervasive problem of model uncertainty in real robots, while his integration of Extended State Observers (ESOs) with safety-critical control elegantly tackles the compounded challenges of unmeasured joint velocities and input delays — conditions frequently encountered in deployed robotic systems. His work on UR-type manipulators further demonstrates the practical applicability of his methods to commercially relevant platforms. Accumulating approximately 38 citations across three papers published between 2023 and 2024, Lin has rapidly established a notable presence in the robotics control community. His research provides students and engineers with actionable, theoretically grounded tools for designing robotic systems that remain safe and reliable even when operating under real-world imperfections and constraints.
Research Focus
Key Achievements
Top Papers
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