Connecting biological design principles and optimal mechanics

Biological systems often express optimal mechanics because they have navigated through some complicated evolutionary fitness landscape. Recent studies have highlighted that the nonlinear design principles of biological actuators (skeletal muscle) exhibit certain mechanical performance advantages – for example, improved energy economy, improved stability, and reduced information entropy in the control effort. We hypothesize that the nonlinear mechanical design principles of biological systems manifest optimal mechanics. However, because of the inherent complexity of the neuroskeletomuscular system, the underlying physical mechanisms that provide these well documented mechanical advantages remains poorly understood. Taking a reductionist approach, we create a robo-physical model system of animal legged locomotion to connect the underlying mechanical design principles to the observed mechanical performance advantages. We construct a two degree-of-freedom robotic leg constrained to jump vertically in one dimension. By implementing feedback control, we actuate the hopper with nonlinear, bioinspired force-velocity characteristics found in the Hill model of muscle. Furthermore, using impedance control in the hopper's ankle to mimic the function of tendons in a biological system, we study how stiffness and damping on impact provide passive mechanical stability. By studying a robo-physical model system of animal legged locomotion, we take a reductionist approach to uncover how the underlying nonlinear physical mechanisms in biology provide mechanical performance advantages.