SD Docker for Development

Table of Contents

1. Overview
2. Requirements
   1. Check Nvidia Drivers
   2. Install Docker Engine
   3. Install NVIDIA Container Toolkit
   4. Download Nvidia Isaac ROS Image
3. Usage
   1. Setup Workspace
   2. Build Image
   3. Run Container
   4. Toggle Container
4. References

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Overview

This repository provides the tools and scripts necessary to create Docker Containers for the development of the Bot-Q TMS platform. It streamlines the setup of the development environment using NVIDIA Isaac ROS.

Requirements

You need a Linux environment with an NVIDIA GPU.

Component	Requirement
OS	Ubuntu >= 22.04 LTS
GPU	NVIDIA GPU with valid drivers
Software	Docker Engine, NVIDIA Container Toolkit

Check Nvidia Drivers

First, ensure that Nvidia drivers are installed and recognized by your machine.

nvidia-smi

You should see output similar to the following:

+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.133.07             Driver Version: 570.133.07     CUDA Version: 12.8     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 4080 ...    Off |   00000000:01:00.0  On |                  N/A |
+-----------------------------------------+------------------------+----------------------+

If the command is not found or no GPU is detected, please refer to this guide to install the drivers (GUI method recommended).

Install Docker Engine

Install Docker Engine on Ubuntu using the official repository.

1. Set up Docker's apt repository:

   # Add Docker's official GPG key:
   sudo apt-get update
   sudo apt-get install ca-certificates curl
   sudo install -m 0755 -d /etc/apt/keyrings
   sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc
   sudo chmod a+r /etc/apt/keyrings/docker.asc
   
   # Add the repository to Apt sources:
   echo \
     "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \
     $(. /etc/os-release && echo "${UBUNTU_CODENAME:-$VERSION_CODENAME}") stable" | \
     sudo tee /etc/apt/sources.list.d/docker.list > /dev/null
   sudo apt-get update

2. Install the Docker packages:

   sudo apt-get install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin

3. Configure Docker to run without root privileges:

   sudo groupadd docker
   sudo usermod -aG docker $USER

4. Apply changes: Reboot or logout/login to activate the group changes.

   reboot

Install NVIDIA Container Toolkit

This toolkit allows the Docker container to utilize the host's GPU.

1. Configure the production repository:

   curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg \
     && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
       sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
       sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
   
   sudo apt-get update

2. Install the toolkit:

   export NVIDIA_CONTAINER_TOOLKIT_VERSION=1.17.8-1
   sudo apt-get install -y \
       nvidia-container-toolkit=${NVIDIA_CONTAINER_TOOLKIT_VERSION} \
       nvidia-container-toolkit-base=${NVIDIA_CONTAINER_TOOLKIT_VERSION} \
       libnvidia-container-tools=${NVIDIA_CONTAINER_TOOLKIT_VERSION} \
       libnvidia-container1=${NVIDIA_CONTAINER_TOOLKIT_VERSION}

3. Apply changes:

   reboot

Download Nvidia Isaac ROS image

Download the base image required for development.

docker pull nvcr.io/nvidia/isaac/ros:x86_64-ros2_humble_23aced29fb80f407b727eec37775e30e

Note

This image is approximately 20GB. Ensure you have sufficient disk space and a stable internet connection (wired recommended).

Usage

Setup Workspace

Clone this repository and set up your workspace directory.

git clone https://github.com/sd-robotics/sd-docker

Copy the configuration to a new directory for your specific container instance.

cp -r sd-docker/ ~/docker_workspaces/
mv ~/docker_workspaces/ ~/{your_new_container_name}/

Warning

Container names must be unique. Please ensure specific folder names are used for different environments.

Build Image

Before building, configure the architecture settings.

Note

Edit the env.sh file inside the docker folder. Set the ARCHITECTURE variable to match your hardware:

ARCHITECTURE=jetson   # Use 'amd64' for PC, 'jetson' for Nvidia Jetson

Navigate to the directory and build the Docker image.

cd ~/{your_new_container_name}/docker
bash build.sh

Run Container

Once the build is complete, launch the container.

bash run.sh

Tip

A shared folder is created at ~/colcon_ws/src/ inside the container, mapping to your local machine for easy data exchange.

Toggle Container

Commands to manage the container lifecycle.

Start an existing container:

docker start {your_new_container_name}

Enter the container terminal:

docker exec -it {your_new_container_name} /bin/bash

Stop the container:

docker stop {your_new_container_name}

References

• Docker Engine Installation: Official Documentation
• Isaac ROS Base Image: NVIDIA NGC Catalog