Bioinspired Embodied Control of Locomotion in Complex Environments

Robophysics is an indispensable approach to discovering general principles of robots operating in complex environments. Fortunately, physics principles governing non-equilibrium processes where motion emerges by internal actuation in synergy with robotic physical models meeting real world environments can generate quantifiable, testable hypotheses of complex biological systems not otherwise possible. In biology, robophysics has led to simple system-level models (templates) that collapse staggering complexity, while exploring how behavior emerges from more representative models (anchors). A next step is to examine the parallel and serial composition of templates and their dynamic reconfiguration. Robophysics provides the opportunity to determine how: biologically embodied mechanical computation works with neural computation; stability occurs in complex environments using soft-matter physics; performance of multiple tasks results without change in structure; multifunctional hierarchical and heterarchical control networks emerge; properties of fail-safe and fault tolerant performance evolve; and how learning can occur using a reduced set of control modules. In turn, robophysics approach to biological locomotion can inspire the design of novel robots and applied mathematics.