Wenzhuo Chen

PLA Army Service Academy, North China Institute of Science and Technology

Papers

Total Citations

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About

Wenzhuo Chen is a leading researcher in robotic painting and manufacturing automation, with a particular focus on paint thickness simulation and trajectory planning for industrial robots. His work addresses critical challenges in achieving uniform coating on complex surfaces, combining computational modeling with practical robotic system design. Chen’s most cited paper, “Paint thickness simulation for painting robot trajectory planning: a review” (2017, 52 citations), provides a comprehensive comparison of explicit function-based and CFD-based methods, establishing a foundational reference for the field. He further advanced this area with “Paint thickness simulation for robotic painting of curved surfaces based on Euler–Euler approach” (2019, 27 citations), introducing a sophisticated multiphase flow model to improve accuracy on non-planar geometries. Chen also demonstrated engineering innovation in “Design of redundant robot painting system for long non-regular duct” (2016, 17 citations), where he developed a specialized autonomous system for navigating and painting confined, irregular spaces. His early work on speech recognition robots (2012) shows his broader interest in human-machine interaction. With over 100 total citations, Chen’s research has direct implications for automotive, aerospace, and industrial coating applications, making his contributions valuable for both researchers and practitioners seeking to optimize robotic painting processes.