Yalun Wen
Papers
11
Total Citations
176
H-Index
7
About
Yalun Wen is a robotics researcher whose work centers on robot motion planning, trajectory optimization, and automated surface finishing systems. His most influential contribution, "Path-Constrained and Collision-Free Optimal Trajectory Planning for Robot Manipulators" (2022, 52 citations), addresses a fundamental challenge in industrial robotics by developing algorithms that navigate complex environments while satisfying kinematic and dynamic constraints. Complementing this, his research on uniform coverage tool path generation (31 citations) and 3D path following control frameworks (24 citations) has significantly advanced the automation of freeform surface finishing — a domain traditionally reliant on skilled human operators. His 2019 paper introducing a novel robotic surface finishing system (28 citations) demonstrated early practical realization of these concepts, offering consistent quality and improved worker safety by reducing hazardous particulate exposure. More recently, Wen has expanded into cybersecurity for manufacturing, developing IoT-based anomaly detection methods to identify malicious or defective robot motion in collaborative workplaces. Across his portfolio, Wen's research bridges rigorous geometric and control theory — including differential geometry and rotation minimizing frames — with real-world industrial applications, accumulating over 175 citations and establishing him as a notable voice in intelligent robotic manufacturing.
Research Focus
Key Achievements
Top Papers
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- 3A Novel Robotic System for Finishing of Freeform Surfaces28 citations · 2019
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- 7A 3D Path Following Control Scheme for Robot Manipulators8 citations · 2020
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- 9A Novel Path Following Scheme for Robot End-Effectors3 citations · 2020
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