Instructions for how to download and install this software

There are two versions of the Developer platform: Cloud and Local.

Below are the instructions for each setup, along with how to get started with a license.

Licensing

To utilize the SWARM RDS Platform, you will need to purchase a license.

You can either contact one of the individuals listed below or go to our website to request a license.

Getting Started

SWARM RDS Consists of a client application that you can use to submit simulations to the SWARM RDS system. To go with this application, there is a Python-based repository that allows you a development workspace through which you can quickly build new algorithms, save different vehcile profiles and much more.

Requirements

The following list are the requirements you will need to have isntalled to be able to use the SWARM RDS Platform.

  1. Required A working version of Python version 3.8 or greater. Check Supported Software
  2. Required Git (If on Windows, installing Git will install the extension in Powershell - Install Git (Windows))
  3. (Optional) A good development environment. (We recommend Visual Studio Code)
  4. (Optional) If you are on Windows, we recommend installing Anaconda and linking that with Powershell.

Install the SWARM RDS Client Application

You can download our client application from the following link:

Download the SWARM RDS Python Repository

Using your development environment or the command line inside of Visual Studio Code, clone our client repository. 

    git clone https://github.com/CodexLabsLLC/SWARM-RDS-Client

Next, you will want to create a new virtual environment with your choice of environment manager, such as Anaconda or pyenv.

Install all dependencies with the following command: 

    python3 -m pip install -r requirements.txt


Scroll down to see additional instructions for the Cloud and Local editions of the SWARM RDS Platform.

Recommended Python Installation

Windows Users

Installing Python on Windows can be slightly complex. The recommended method is to install the Python application, along with Visual Studio Code. This will allow you to easily install the required packages and use Python through the terminal in VS Code.

The recommended method is to install Python via Micrsoft store or to download it Here.

Once you have installed Python, we recommend installing Anaconda to manage dependencies. You can download Anaconda Here.

Once you have installed Anaconda, you first need to create a new conda virtual environment in Powershell. To do this, run the following command: conda --create swarmrds. More commands are here: Conda Cheat Sheet. You can then activate this environment with the following command: conda activate swarmrds.

Once you have activated the environment, you will need to go to where you installed our python repository. In visual studio code, open our repository and then create a new terminal. Then, you can then install the required packages with the following command: conda install --yes --file requirements.txt.

Mac Users

The recommended method is to install Python via a tool like brew or to install the Developer Command Line tools. Please install the python packages using the above method.

Linux Users

The recommended method is to install Python apt with sudo apt-get install -y python3-dev python3-pip. Please install the python packages using the above method.

Local Edition Only (ie. you are not using the cloud!)

If you have a copy of our Docker Container

The Local edition of the SWARM Simulation Platform is still easy to get started and set up.

What you'll need:
  1. Install NVIDIA Docker on your host platform (we currently only support Linux) NVIDIA Docker
  2. The lastest NVIDIA Drivers for your specific GPU (>= Version 515)Download NVIDIA Drivers

Installing SWARM Core

Next, we will install the SWARM Container to the Docker host.

Using the link provided, download the tar file that contains the container. (Please not this container may be 10 - 15 GB, so please ensure you have space on your system!)

Next, we will load the container. In the same directory where you downloaded the tar file, run the following command: 

    docker load --input NAME_OF_TAR_FILE.tar.gz

This will take several minutes depending on the size of the container.

Once completed, you can then run the following command to view the name of the container.



(Optional) If you have a Proxy Network

If you are on a Proxy network, you will need to set the proxy settings for the container. To do this, run the following command: 

    docker run -it --rm --net=host -e HTTP_PROXY=http://<PROXY_IP>:<PROXY_PORT> -e HTTPS_PROXY=http://<PROXY_IP>:<PROXY_PORT> -e NO_PROXY=localhost,


Adding these environment variables will enable the container to access the internet through the proxy network. Please see the README in the Python Repository for more information.

That's it! You are ready to rock and build your awesome autonomous system! Visit the Getting Started guide or the API Documentation to get started!

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