Getting Started

This page provides a guide on how to set up the MILUV devkit and dataset. The MILUV devkit is a Python package that provides tools to work with the MILUV dataset. Details on the dataset can be found here. The devkit provides tools to load data from the dataset, visualize data, and run experiments on the dataset. The devkit can be installed locally or can be run virtually using Docker, as outlined below.

Devkit installation

Local installation

To install the MILUV devkit, clone the repository by running

git clone https://github.com/decargroup/miluv.git

in the directory where you would like to store the repository. To intall the devkit locally, run

pip3 install .

in the root directory of the repository. This will install the devkit and its dependencies. For a list of all dependencies, refer to requirements.txt in the repository’s root directory.

Docker installation

To install the MILUV devkit using Docker, you must have Docker installed on your machine, which can be installed by following the instructions here.

Start by cloning the repository by running

git clone https://github.com/decargroup/miluv.git

in the directory where you would like to store the repository. To build the Docker image, run

docker build -t miluv .

in the root directory of the repository. This will create a Docker image called miluv that contains the devkit and its dependencies. This took 2 minutes on my machine and with my internet connection.

Dataset setup

The devkit is used alongside the MILUV dataset, and by default the devkit expects that the data for each experiment is available in /path/to/miluv/data/{exp_number}, where {exp_number} is the number of the experiment outlined here. If you wish to change the default data location, be sure to specify the data directory when creating an instance of the MILUV Dataloader, but it is recommended to keep the data in the default location. You do not have to download the entire dataset, but at least the experiments that you would like to work with.

Using the devkit

Local usage

After installing the devkit, you should be able to use the devkit by importing it in your Python scripts. For example, to use the DataLoader, you can add

from miluv.data import DataLoader

to the top of your script.

If you want to use the devkit as a ROS package, you will have to create a symlink to the devkit and the uwb_ros subdirectory in the src directory of your ROS workspace. To do this, run

ln -s /path/to/miluv /path/to/your/ros/workspace/src/miluv
ln -s /path/to/miluv/uwb_ros /path/to/your/ros/workspace/src/uwb_ros

and then build your ROS workspace as you normally would.

Docker usage

Alternatively, you can run the devkit using Docker, which sets up the environment for you. To run the Docker container, we provide a Docker compose file that will mount the necessary directories and run the container. To run the container, run

docker compose up

from the root directory of the repository, which will start the container. To open a shell inside the container, run in a separate terminal

docker exec -it miluv-miluv-1 bash

Troubleshooting

If you encounter any issues during installation or usage of the MILUV devkit, you can open an issue on the GitHub repository for further assistance.

You are now ready to start using the MILUV devkit! For examples on how to use the devkit, refer to the Examples.