Graph-based path planning for continuous fiber 3D printing with loop-dependent offset for topologically optimized structures

Continuous fiber reinforced composite (CFRC) 3D printing combines the advantages of additive manufacturing and advanced composite materials, enabling the fabrication of lightweight structures with complex geometries and improved mechanical performance. However, converting topology optimization results into manufacturable continuous fiber toolpaths remains challenging, because discontinuous paths, void formation, abrupt turns, and fiber misalignment can substantially reduce structural performance. To address these issues, this study develops a graph-based continuous fiber path planning framework that links topology optimization results with manufacturable toolpath generation. The optimized topology is first converted into a skeleton-based graph, and locally continuous fiber paths are then constructed for the decomposed Eulerian or semi-Eulerian subgraphs. Based on the decomposition of the generated path set, a loop-dependent adaptive offset strategy is further introduced to redistribute fiber material among different load paths while maintaining nearly constant material consumption. The proposed framework generates curvature-controlled manufacturable fiber trajectories and enables performance-oriented material distribution. Under nearly identical material consumption, the proposed method improves structural stiffness and peak load by 8.73% and 14.88%, respectively, while producing manufacturable continuous-fiber trajectories with improved path continuity.