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About

Renwei Liu is a researcher at the forefront of advanced manufacturing and control systems, with key contributions spanning additive manufacturing, industrial robotics, and networked control theory. Liu’s most impactful work centers on fused pellet modeling (FPM), a scalable additive manufacturing technique that uses granular materials instead of filaments, addressing critical challenges in large-scale part production such as long build times and deformation. Their 2016 paper on designing an FPM system with an industrial robot has garnered 53 citations, establishing a foundation for cost-effective, large-format 3D printing. In robotics, Liu has advanced hybrid manufacturing processes by developing trajectory accuracy evaluation maps based on joint angle error analysis and stiffness mapping methods, which are essential for maintaining precision under heavy external loads from deposition extruders or machining tools. Liu has also ventured into control theory, exploring asynchronous dissipative control for networked Markov jump systems with event-triggered schemes and packet dropouts, demonstrating versatility across disciplines. Notable achievements include pioneering robot ink deposition on curved surfaces using adaptive compensation algorithms, enabling precise additive manufacturing on complex geometries. With a research portfolio that bridges practical manufacturing challenges and theoretical control innovations, Liu’s work continues to influence both industrial automation and intelligent systems design.