Modular representation and control of floppy networks

Geometric graph models of systems as diverse proteins, DNA assemblies, architected materials and robot swarms are useful abstract representations these objects that also unify ways to study their properties control them in space time. While much work has been done the context characterizing behaviour networks close critical points associated with bond rigidity percolation, isostaticity, etc., less is known about floppy, underconstrained far more common nature technology. Here, we combine geometric algebraic sparsity provide a framework for identifying zero energy floppy modes via representation illuminates underlying hierarchy modularity network thence its nestedness locality. Our allows us demonstrate range applications this approach include robotic reaching tasks motion primitives, predicting linear nonlinear response elastic based solely on infinitesimal sparsity, which test using physical experiments. thus likely be use broadly dissecting geometrical optimize function performance.