Small deviations in kinematics and body form dictate muscle performances in the finely tuned avian downstroke.

Avian takeoff requires peak pectoralis muscle power to generate sufficient aerodynamic force during the downstroke. Subsequently, the much smaller supracoracoideus recovers the wing during the upstroke. How the pectoralis work loop is tuned to power flight is unclear. We integrate wingbeat-resolved muscle, kinematic, and aerodynamic recordings in vivo with a new mathematical model to disentangle how the pectoralis muscle overcomes wing inertia and generates aerodynamic force during takeoff in doves. Doves reduce the angle of attack of their wing mid-downstroke to efficiently generate aerodynamic force, resulting in an aerodynamic power dip, that allows transferring excess pectoralis power into tensioning the supracoracoideus tendon to assist the upstroke-improving the pectoralis work loop efficiency simultaneously. Integrating extant bird data, our model shows how the pectoralis of birds with faster wingtip speed need to generate proportionally more power. Finally, birds with disproportionally larger wing inertia need to activate the pectoralis earlier to tune their downstroke.

The aerodynamic force platform as an ergometer.

Animal flight requires aerodynamic power, which is challenging to determine accurately in vivo Existing methods rely on approximate calculations based on wake flow field measurements, inverse dynamics approaches, or invasive muscle physiological recordings. In contrast, the external mechanical work required for terrestrial locomotion can be determined more directly by using a force platform as an ergometer. Based on an extension of the recent invention of the aerodynamic force platform, we now present a more direct method to determine the in vivo aerodynamic power by taking the dot product of the aerodynamic force vector on the wing with the representative wing velocity vector based on kinematics and morphology. We demonstrate this new method by studying a slowly flying dove, but it can be applied more generally across flying and swimming animals as well as animals that locomote over water surfaces. Finally, our mathematical framework also works for power analyses based on flow field measurements.

Automated calibration of multi-camera-projector structured light systems for volumetric high-speed 3D surface reconstructions.

It is challenging to calibrate multiple camera-projector pairs for multi-view 3D surface reconstruction based on structured light. Here, we present a new automated calibration method for high-speed multi-camera-projector systems. The method uses printed and projected dot patterns on a planar calibration target, which is moved by hand in the calibration volume. Calibration is enabled by automated image processing and bundle-adjusted parameter optimization. We determined the performance of our method by 3D reconstructing a sphere. The accuracy is -0.03 ± 0.09 % as a percentage of the diameter of the calibration volume. Applications include quality control, autonomous systems, engineering measurements, and motion capture, such as the preliminary 3D reconstruction of a bird in flight we present here.

High-speed surface reconstruction of a flying bird using structured light.

Birds fly effectively and maneuver nimbly by dynamically changing the shape of their wings during each wingbeat. These shape changes have yet to be quantified automatically at high temporal and spatial resolution. Therefore, we developed a custom 3D surface reconstruction method, which uses a high-speed camera to identify spatially encoded binary striped patterns that are projected on a flying bird. This non-invasive structured-light method allows automated 3D reconstruction of each stand-alone frame and can be extended to multiple views. We demonstrate this new technique by automatically reconstructing the dorsal surface of a parrotlet wing at 3200 frames s-1 during flapping flight. From this shape we analyze key parameters such as wing twist and angle of attack distribution. While our binary 'single-shot' algorithm is demonstrated by quantifying dynamic shape changes of a flying bird, it is generally applicable to moving animals, plants and deforming objects.