Add directory structure

index.md

@@ -1,7 +1,4 @@
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-# Feel free to add content and custom Front Matter to this file.
-# To modify the layout, see https://jekyllrb.com/docs/themes/#overriding-theme-defaults
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 title: Home
 nav_order: 1
 usemathjax: true
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 # MILUV Dataset
 
-Introducing MILUV, the first multi-robot dataset with ultra-wideband (UWB) measurements. This dataset features
+Introducing MILUV, the first multi-robot dataset with ultra-wideband (UWB) measurements and vision data. This dataset features
 * Pose data
   * On-board inertial measurement unit (IMU) data
   * Camera IMU data from Intel RealSense d435i
@@ -38,3 +35,26 @@ MILUV is accompanied by a Python devkit to facilitate the development of applica
 * Examples of alternative uses for the dataset
   * Line-of-sight/non line-of-sight classification from CIR data
   * AprilTag detection from camera measurements
+
+The repository is available [here](https://github.com/decargroup/miluv), and the directory structure of the repository is as follows:
+```
+miluv
+├── config
+│   ├── apriltags    (AprilTag positions)
+│   ├── height       (Height bias)
+│   ├── imu          (Camera IMU and PX4 IMU calibration files from the allan_variance_ros package)
+│   ├── realsense    (Camera calibration files from Kalibr)
+│   ├── setup        (The files provided by Vicon mocap system for apriltags and UWB anchors)
+│   ├── uwb          (Anchor and tag position files and UWB calibration results)
+│   ├── vins         (VINS-Fusion configuration files)
+├── data             (this is where the dataset should be downloaded)
+├── examples         (Example scripts on how to use the devkit)
+├── launch           (ROS launch files)
+├── miluv            (The devkit with the data loading and utility scripts)
+├── paper            (Scripts used to produce the results in the paper)
+├── preprocess       (Scripts used to preprocess the raw data into the dataset format)
+├── tests            (Unit tests)
+├── uwb_ros          (ROS package with msg files for UWB data)
+```
+
+To get started with the MILUV dataset, follow the instructions in the [Getting Started](https://decargroup.github.io/miluv/docs/gettingstarted.html) page.