Novel method for measuring a dense 3D strain map of robotic flapping wings

Measuring dense 3D strain maps of the inextensible membranous flapping wings of robots is of vital importance to the field of bio-inspired engineering. Conventional high-speed 3D videography methods typically reconstruct the wing geometries through measuring sparse points with fiducial markers, and thus cannot obtain the full-field mechanics of the wings in detail. In this research, we propose a novel system to measure a dense strain map of inextensible membranous flapping wings by developing a superfast 3D imaging system and a computational framework for strain analysis. Specifically, first we developed a 5000 Hz 3D imaging system based on the digital fringe projection technique using the defocused binary patterns to precisely measure the dynamic 3D geometries of rapidly flapping wings. Then, we developed a geometry-based algorithm to perform point tracking on the precisely measured 3D surface data. Finally, we developed a dense strain computational method using the Kirchhoff-Love shell theory. Experiments demonstrate that our method can effectively perform point tracking and measure a highly dense strain map of the wings without many fiducial markers.