These datasets were generated for calibrating robot-camera systems. In an extension, we also considered the problem of calibrating robots with more than one camera. These datasets are provided as a companion to the paper "Solving the Robot-World Hand-Eye(s) Calibration Problem with Iterative Methods" by Amy Tabb and Khalil M. Ahmad Yousef. Included are eight datasets in zipped files, numbered DS1.zip, DS2.zip, etc. Explanations of the format of the datasets is provided in the README resource in the file "README_input_format.txt". Generally, each zipped folder consists of images and a text file of robot positions when those images were acquired. Open source code can be found at: https://github.com/amy-tabb/RWHEC-Tabb-AhmadYousef We also include the results of using our code on one of the datasets so that you can be sure that the code worked correctly. This folder is named DS1_write.zip and can be found in the resource titled "Output from running methods on Dataset 1". Problems/Comments/Bugs should be addressed to amy.tabb@ars.usda.gov

The data herein contains all data collected and used for the Performance Characterization Testing and Model Calibration of a Vertical Axis Hydrokinetic Turbine. The data includes performance data and durability data for the Hydrokinetic Turbine. The device performance data contains shaft RPM, turbine RPM, power output, flow velocity, pressure, and pressure drop across the turbine. The mechanical durability data includes stress and strain at varied depths and velocities. There is also an FEA analysis included. This TEAMER project was awarded to Emrgy, Inc.in collaboration with Alden Research Laboratory LLC.

A set of PYTHON programs to implement image processing of ground and aerial images by offering via graphical user interface (GUI) 1) plot-level metrics extraction through a series of algorithms for image conversion, band math, radiometric/geometric calibrations, segmentation, masking, adaptive region of interest (ROI), gridding, heatmap, and batch process, 2) GIS interface for GeoTIFF pixels to Lat/Lon, UTM conversion, read/write shapefile, Lat/Lon to ROI, grid to polygon, and 3) utility GUI functions for zooming, panning, rotation, images to video, file I/O, and histogram.

GUI-based software coded in PYTHON to automate image stitching and alignment processes from a set of tile images for the high throughput image analytics by implementing a series of algorithms: 1) deskewing the image acquired in an oblique view angle, 2) row alignment of the geometrically drifted image due to acquisition errors by detecting the crop row using Hough Transformation, and 3) options for omnidirectional overlap trimming and resizing.