A Comprehensive and User-Friendly Guide to Docker and ROS 2: Stay Up-to-Date
Introduction:
Two years ago, I wrote a popular post titled “A Guide to Docker and ROS” which received a lot of attention due to the difficulty of the topic. Since then, I have gained more experience with Docker and collected new tips and tricks that I am excited to share in this updated post. While I agree with an article that argues against using ROS Docker, the truth is that Docker still serves as a helpful tool for creating reproducible ROS environments, especially for those who are new to ROS and face challenges with debugging and dependencies. If you are still interested in exploring Docker for ROS, I invite you to read on and discover how to revisit our Dockerfile with ROS 2.
Full Article: A Comprehensive and User-Friendly Guide to Docker and ROS 2: Stay Up-to-Date
Title: Docker and ROS 2: Building a Reproducible Environment
Introduction:
Two years ago, I wrote a comprehensive guide to Docker and ROS (Robot Operating System), which has garnered significant attention from readers seeking answers on this complex topic. Since then, I have gained more experience with Docker and ROS, and have gathered new insights that I will be sharing in this article. While there are several reasons why Docker and ROS may not be an ideal fit, it remains a valuable tool for creating reproducible ROS environments, especially for those who are new to ROS and struggle with debugging dependency and build errors. So, if you’re still interested in exploring the Docker adventure with ROS, read on.
Revisiting Our Dockerfile with ROS 2:
With ROS 1 reaching its final version and set to reach end of life in 2025, it is essential to upgrade our TurtleBot3 example repository to ROS 2. This upgrade primarily involves changes in client libraries, launch files, and DDS configuration. Additionally, the examples now incorporate the latest tools for behavior trees, including BehaviorTree.CPP 4/Groot 2 for C++ and py_trees/py_trees_ros_viewer for Python. For more details on behavior trees, refer to my previous post on Introduction to Behavior Trees.
Container Layout:
In terms of Docker, there aren’t many differences when switching from ROS 1 to ROS 2. The container layout remains largely the same. The Dockerfile for our TurtleBot3 example image now includes layers as follows:
– Base Layer: Inherits from the osrf/ros:humble-desktop ROS image and sets up the dependencies from the example repository.
– Overlay Layer: Copies the example source code, installs missing dependencies, and sets up an entrypoint script to be executed when launching the container.
Building the Docker Image:
To build the Docker image with a specific argument (e.g., using ROS 2 Rolling), you can use the following command:
docker build -f docker/Dockerfile –build-arg=”ROS_DISTRO=rolling” –target base -t turtlebot3_behavior:base
Switching to Cyclone DDS:
Personally, I have faced several issues with the default DDS vendor (FastDDS) in ROS 2 Humble and later versions. To overcome this, I prefer using Cyclone DDS and have included instructions to switch to this middleware in the Dockerfile.
Creating the Overlay Layer:
In the overlay layer, we copy the example source code, install missing dependencies, and set up the entrypoint script. The entrypoint is a Bash script that sources ROS 2 and any built workspaces, while setting up environment variables required to run the TurtleBot3 examples.
Introducing Docker Compose:
As the build and run commands for Docker images grow longer and complex, it is beneficial to utilize Docker Compose, a tool that simplifies managing Docker containers. With Docker Compose, you can define a YAML file that captures all the configuration needed for building images and running containers. It also allows you to orchestrate multiple services within the same image(s) and launch various programs simultaneously.
Docker Compose for Our Example:
In our TurtleBot3 example, we use a Docker Compose YAML file to specify the dependencies, image builds, and commands for running our examples. This YAML file includes services for the base image, overlay image, and specific demo worlds and behaviors using both Python and C++.
Setting up Developer Containers:
The current example provides a functional setup for running TurtleBot3 simulations with Docker and ROS 2. However, additional customization may be required depending on your specific needs. Developing a reproducible environment using Docker and ROS 2 lays the foundation for efficient robotics development.
Conclusion:
In conclusion, Docker continues to be a valuable tool for creating reproducible ROS environments, despite some challenges and limitations. By upgrading our TurtleBot3 example to ROS 2 and leveraging Docker Compose, developers can build and run containerized examples with ease. The combination of Docker and ROS 2 offers a powerful solution for developing and testing robotics applications in a consistent and scalable manner.
Summary: A Comprehensive and User-Friendly Guide to Docker and ROS 2: Stay Up-to-Date
Two years ago, the author wrote a guide on Docker and ROS, which has been frequently viewed due to its complexity. Now, the author has updated their learnings on Docker and ROS 2, as it is still difficult to ensure a reproducible ROS environment without Docker. The Dockerfile is explained, detailing the layers and dependencies. The use of Docker Compose is introduced to simplify the build and launch of the containerized examples. Additionally, the challenges of developing within the Docker environment are discussed.
Frequently Asked Questions:
1. Q: What is robotics?
A: Robotics is a field of technology that involves designing, constructing, programming, and operating robots. It combines aspects of engineering, electronics, computer science, and artificial intelligence to create machines that can perform a variety of tasks autonomously or with human guidance.
2. Q: What are the applications of robotics?
A: Robotics finds applications in various industries and sectors. Some common areas where robotics is utilized include manufacturing, healthcare, agriculture, space exploration, military, entertainment, and education. Robots can perform tasks such as assembly line operations, surgery, automated farming, space exploration missions, bomb disposal, entertainment performances, and teaching.
3. Q: How do robots work?
A: Robots work through a combination of sensors, actuators, and computer programming. Sensors provide data about the robot’s surroundings, allowing it to perceive and react to the environment. Actuators act upon this information, enabling the robot to move, manipulate objects, or perform specific tasks. The computer programming, often using artificial intelligence algorithms, controls the robot’s behavior and decision-making process.
4. Q: What are the benefits of using robots?
A: There are multiple benefits associated with the use of robots. These include increased efficiency, improved accuracy, enhanced productivity, reduction in human error, cost savings, and enhanced safety. Robots can work tirelessly, with consistent precision, and can often perform tasks that are too dangerous or tedious for humans. They also have the potential to free up human workers for more creative and complex jobs.
5. Q: What are the future prospects of robotics?
A: The future of robotics appears promising, with advancements in technology continuing to drive innovation. It is expected that robots will become more integrated into our daily lives, with increased use in personal assistance, transportation, space exploration, healthcare, and other areas. Additionally, as robotics intersects with other fields such as artificial intelligence and machine learning, robots are likely to become smarter, more autonomous, and better at adapting to dynamic environments. Robotics has the potential to revolutionize industries and contribute to human progress in various ways.
