Reduction and Identification for Hybrid Dynamical Models of Terrestrial Locomotion

The study of terrestrial locomotion has compelling applications ranging from design of legged robots to development of novel prosthetic devices. From a first-principles perspective, the dynamics of legged locomotion seem overwhelmingly complex as nonlinear rigid body dynamics couple to a granular substrate through viscoelastic limbs. However, a surfeit of empirical data demonstrates that animals use a small fraction of their available degrees-of-freedom during locomotion on regular terrain, suggesting that a reduced–order model can accurately describe the dynamical variation observed during steady–state locomotion. Exploiting this emergent phenomena has the potential to dramatically simplify design and control of micro–scale legged robots. We propose a paradigm for studying dynamic terrestrial locomotion using empirically–validated reduced–order models.