One of the most robust examples of self-assembly in living organisms is the formation of collagen architectures. Collagen type I molecules are a crucial component of the extracellular-matrix where they self-assemble into fibrils of well defined striped patterns. This striped fibrilar pattern is preserved across the animal kingdom and is important for the determination of cell phenotype, cell adhesion, and tissue regulation and signalling. The understanding of the physical processes that determine such a robust morphology of self-assembled collagen fibrils is currently almost completely missing. Here we develop a minimal coarse-grained computational model to identify the physical principles of the assembly of collagen-mimetic molecules. We find that screened electrostatic interactions can drive the formation of collagen-like filaments of well-defined striped morphologies. The fibril pattern is determined solely by the distribution of charges on the molecule and is robust to the changes in protein concentration, monomer rigidity, and environmental conditions. We show that the fibril pattern cannot be easily predicted from the interactions between two monomers, but is an emergent result of multi-body interactions. Our results can help address collagen remodelling in diseases and ageing, and guide the design of collagen scaffolds for biotechnological applications. Statement of Significance Collagen type I protein is the most abundant protein in mammals. It is a crucial component of the extracellular-matrix where it robustly self-assembles into fibrils of specific striped architectures that are crucial for the correct collagen function. The molecular features that determine such robust fibril architectures are currently not well understood. Here we develop a minimal coarse-grained model to connect the design of collagen-like molecules to the architecture of the resulting self-assembled fibrils. We find that the pattern of charged residues on the surface of molecules can drive the formation of collagen-like fibrils and fully control their architectures. Our findings can help understand changes in collagen architectures observed in diseases and guide the design of synthetic collagen scaffolds.