MEMS Setae for Bio-Inspired Wind and Lift Sensing

Sensing relative wind and inferring the aerodynamic state of primary lifting surfaces provides the feedback necessary for very fast reactions which adjust wing surface shape, incidence, and flapping parameters. In nature, this reaction can be hard-wired into the nervous system in which signals are routed directly to muscles to reduce delays. This approach yields aerodynamic force management unparalleled in current autonomous aerial systems. In this project, we are investigating biologically inspired distributed airflow sensing and the underlying processing required to extract robust information. The goal is to improve disturbance rejection capabilities and lift control, enabling operation in complex environments requiring high maneuverability and all-weather operability.