DOI: 10.5061/dryad.15dv41ntr
title: The aerodynamic force platform as an ergometer

description: 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.
description: This dataset consists of the following collected data:
 High speed camera data collected to calibrate 5 high
 speed cameras and 5 high speed projectors High speed
 camera data (5 cameras + 5 projectors projecting structured-light
 patterns) collected of a single dove flight as described in the
 manuscript Aerodynamic force platform data collected
 for the same single dove flight This
 dataset consists of the following processing steps: 
 The calibration data has been processed to calibrate all 5 high
 speed cameras and projectors using the steps described in this
 paper: Deetjen ME, Lentink D. Automated calibration of
 multi-camera-projector structured light systems for volumetric high-speed
 3D surface reconstructions. Opt Express.
 2018;26(25):33278–304.  The bird has been modeled
 using structured-light processing steps described in this paper: Deetjen
 ME, Biewener AA, Lentink D. High-speed surface reconstruction of a flying
 bird using structured light. J Exp Biol [Internet]. 2017 Jun
 1;220(11):1956–61. Available from:
 http://jeb.biologists.org/lookup/doi/10.1242/jeb.149708.
 The rest of the processing steps to compute aerodynamic power
 are described in the current publication.
description: The main folders are labeled with numbers 0-9 and should all be
 placed in a single folder. Folder 1 is contained in "1 Experimental
 Flights.zip", folder 9 is contained in "9 FinalModel.zip",
 and the other folders are contained in
 "IntermediateProcessingSteps.zip". Instructions for running and
 understanding this code/data: <br>
 <strong>0 MATLAB Base Folder</strong> 
 This should be set as your MATLAB startup folder
 (https://www.mathworks.com/help/matlab/matlab_env/matlab-startup-folder.html) <strong>1 Experimental Flights</strong> This is where all of the collected data is located To save space, only calibrations 1 & 2 (2018_12_11_calib1 & 2018_12_11_calib2) is present, but we combined the first 10 calibrations to give the best result. The results can be seen in the folder: 5 Calibration The flight of interest is in the folder "Dove_OP/2018_12_11_OP_F03". This folder contains recordings from all 5 high speed cameras and the Aerodynamic Force Platform (AFP) data <strong>2 </strong> There was originally a folder here, but the content was not relevant to this manuscript, so to save space, this folder was removed. <strong>3 Other data</strong> This folder contains the dot patterns used for calibration and the hash patterns used for 3D reconstruction <strong>5 Calibration</strong> 1DotPatterns: This folder contains all the dot patterns used for calibration 2Intermediate: This folder contains all the intermediate saved data used for calibration - files here are created as the calibration runs 3Results: This folder contains the results of the calibrations. The calibration file we use for this flight is 2018_12_11_calibAll_1-10/Final_Calib.mat MainCalibCode: All of the main calibration code is located in this folder MultiCalib Run BatchRun.m to run one of the two calibrations (2018_12_11_calib1 & 2018_12_11_calib2) we have provided Run BatchRunCombo.m to combine data from multiple calibrations together into an improved calibration. To save space, this code is set up to run calibrations 1 & 2, but in our test, we combined calibrations 1-10. <strong>6 SLS Reconstruction</strong> 2Intermediate: All of the results of Hash_v2 are stored here Hash_v2: Run RunDoveSetupHash.m to compute the automated 3D reconstruction of the dove. Hash_v2/Kinematics: Run the KinClick.m function to manually click kinematics points and update the Kinematics.mat file in 2Intermediate. Afterwards, run the Kin2Dprocess.m file to interpolate and smooth the kinematic points. Hash_v2/SurfFit: Run the WingClick.m function to manually click the region of the left wing so as to isolate it and update the WingClickReg.mat file in 2Intermediate. Run the SurfModel.m script to fit the wing, body, and tail surfaces to the bird and store the result in the 2Intermediate folder. <strong>7 AccuracyXYZ</strong> 1 SphereDrop: Run SphereDir.m to find the direction of gravity 2 RodDir: Run RodDir.m to get the forward direction relative to the AFP 4 PerchPos: Run PerchPos.m to get the positions of the perches XYZ_KeyVars: Here are stored all of the key variables to transfer between reference frames as determined by the sphere drop, rod direction, and perch position. <strong>8 AFP</strong> Run Aero.m to read in the AFP data and create a simple plot <strong>9 FinalModel</strong> Run Model_AeroPower.m to compute all of the necessary parameters to plot the figures in the manuscript and store the data in the folder named Data. Run Model_Figs.m to plot all the figures in the manuscript.