Guoxian Song

University of Science and Technology of China

Papers

Total Citations

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About

Guoxian Song is a pioneering researcher in robotic additive manufacturing, with a focus on advancing 3D printing beyond conventional layer-by-layer methods. His key research areas include spatial thermoplastic extrusion, robotic fabrication of frame structures, and novel strategies for 3D spatial printing. Song’s most influential work, "FrameFab" (2016), with 84 citations, introduced a groundbreaking approach to fabricating frame shapes—structures composed of interconnected struts—using robotic extrusion. This work addressed the growing interest in creating lightweight, geometrically complex frames for applications in art, sculpture, architecture, and geometric modeling, demonstrating how robots can directly build and join struts in free space. In his subsequent paper, "Highly Informed Robotic 3D Printed Polygon Mesh" (2016), Song further advanced this paradigm by proposing a strategy to print polygon meshes without relying on traditional layered deposition, enabling more efficient and structurally sound spatial printing. His contributions have significantly impacted the field of digital fabrication, offering new possibilities for creating custom, material-efficient structures. Song’s research continues to inspire innovations in robotic construction and additive manufacturing, making him a notable figure in the evolution of 3D printing technology.