Raw data files for BigAnt robot motion tracking data collected at the University of Michigan's Bio-Inspired Robotics and Dynamical Systems Lab 
(BIRDS-Lab) https://www.birds.eecs.umich.edu Principal Investigator: Shai Revzen

Collection of these data is the work of many people over a period of several years. 

Data file names follow a naming convention, e.g. 2019-07-11-T+75_f22_gL_e2
  Was a trial taken on July 11th, 2019, 
  with turning (T) rate +0.75, 
  at frequency (f) 0.22Hz, 
  on the Low friction ground (g) surface; 
  this was the 3rd experiment (e) with these parameters (e0 would have been the first).

All data files are .csv.gz files, with 9 header lines. 
All data in the files are integers, in units of either 1.0 mm or 0.5 mm (see metadata.py for scale)
Typical python code for reading the data is:
  from numpy import loadtxt
  d = loadtxt('2019-07-11-T+75_f22_gL_e2.csv.gz',skiprows=9,delimiter=',')
  xyz = d.reshape(d.shape[0],d.shape[1]//3,3)

The key technologies used to develop the robot were described in:

Fitzner, I.; Sun, Y.; Sachdeva, V. & Revzen, S. 
   Rapidly Prototyping Robots: Using Plates and Reinforced Flexures
   IEEE Robotics Automation Magazine, 2017, 24, 41-47 
   https://doi.org/10.1109/MRA.2016.2639058

The data in this dataset was used in the following publications:

Zhao, D. & Revzen, S.
   Multi-legged steering and slipping with low DoF hexapod robots <br>
   Bioinspiration & biomimetics, 2020, 15, 045001 
   https://doi.org/10.1088/1748-3190/ab84c0

Zhao, D.
   Ph.D. Thesis "Locomotion of low-DOF multi-legged robots" 
   University of Michigan 2021

and is currently being used in several additional manuscripts and pre-prints.

To Cite this Work:
BIRDS Lab, U. BigAnt v6 robot motion tracking data - RAW dataset [Data set], 
University of Michigan - Deep Blue Data. https://doi.org/10.7302/024q-kk06


Funding for the equipment was provided from:
   University of Michigan start-up funds for Revzen
   ARO W911NF-17-1-0243 "DRAKE: Dynamics, Robotics, And Kinematics Experiments"

Funding for researchers was provided from:
   ARO W911NF-14-1-0573 "Morphologically Modulated Dynamics"
   ARO MURI W911NF-17-1-0306 "From Data-Driven Operator Theoretic Schemes to Prediction, Inference, and Control of Systems"
   D. Dan and Betty Kahn Michigan-Israel Partnership for Research and Education Autonomous Systems Mega-Project
   NSF CMMI 1825918 "Geometrically-Optimal Gait Optimization"

With particular thanks to Devin Miller & Haotian Li for their hard work on robot data collection.