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An installation of ROS2 Foxy in a container, with a full desktop environment, ready to deploy on balena devices.

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balena ROS2 Foxy Desktop container

Ben Notes

Currently set ssh to the lowest security. ssh to root without password ALternatively, we could use the ssh key to login as root instead. just add the key to the file id_ed25519.pub

balena deploy button

Special Note:

This GitHub repository is based on the foundational work of Keenan Johnson's repo, located here: https://github.com/keenanjohnson/balena-ros/. Be sure to give Keenan a Star and a Follow!

About

This repo installs ROS2 Foxy into a 64-bit Ubuntu Arm container, ready to be run on a Raspberry Pi 4 or an NVIDIA Jetson device running balenaOS (warning, the Nano is a bit under-powered, and frame rates when using a 4k monitor are quite slow). Other 64-bit Arm platforms might also work, but have not been tested. The Dockerfile adds the basic requirements, adds the ROS key and APT sources, then installs the ROS binaries. This repo sets up the ROS2 Foxy "Desktop" install, which is a fully featured installation including a desktop GUI, Rviz for robot visualization, and Gazebo for simulation. If you only need the minimal ROS installation, there is also a "Base" repo available here: https://github.com/balena-io-examples/balena-ros2-foxy-base, which makes for a slimmer container.

Usage

To get started, you can simply click the "Deploy with balena" button above, or use the traditional workflow and do a git clone of this repo, and then a balena push YourAppNameHere to deploy the container to your device. You can read about how to create a balena application, setup your device, and install the balena CLI here: https://www.balena.io/docs/learn/getting-started/raspberrypi4-64/python/

Once your device is provisioned and online, and the containers have been built and downloaded, you are ready. This repo will build a full desktop environment, so you'll want to attach a monitor, keyboard, and mouse to your device. Upon starting up, you will be brought directly to the desktop. We have included the TurtleBot3 sample application, so that you can get started and see how Rviz and Gazebo work. From the Start menu, open up a Terminal, and enter the following commands to launch TurtleBot (burger is the type of Turtlebot...there is also waffle and waffle_pi that you can try):

export TURTLEBOT3_MODEL=burger
ros2 launch turtlebot3_gazebo turtlebot3_house.launch.py

It will take a moment, but you will see Gazebo launch and a 3D-rendered house get built. A robot is created and placed on the ground out front, as well. To drive TurtleBot, you need to launch another Terminal, and enter the following commands:

export TURTLEBOT3_MODEL=burger
ros2 run turtlebot3_teleop teleop_keyboard

This will allow you to move the robot around, using the keyboard to move the robot as shown in the CLI: w,a,s,d,x for forward, left, stop, right, and back respectively.

SLAM

You can also have a look at TurtleBot's view of the world by launching Rviz. This is useful to get the simulated Lidar perspective, and begin to understand how a robot "sees" it's surroundings. Open yet another terminal, and enter the following:

export TURTLEBOT3_MODEL=burger
ros2 launch turtlebot3_cartographer cartographer.launch.py use_sim_time:=True

Switch back to your previous terminal tab, and again using the keyboard to move the bot, you can watch as TurtleBot begins to map it's surroundings.

Navigation

Finally, you can begin to experiment with Navigation and creating pre-determined movements, again in a simulated environment before deploying to your real-world autonomous devices. It's probably best to exit the SLAM simulation by navigating back to that terminal, and pressing Control-C on the keyboard to kill the process and close out that particular task. Then, you can enter the following to launch a Navigation simulation:

export TURTLEBOT3_MODEL=burger
ros2 launch turtlebot3_navigation2 navigation2.launch.py use_sim_time:=True

Conclusion

This repo is designed to get you up and running with ROS2 Foxy quickly, and help you to get ROS installed and functional. There is some demo functionality built-in as described, and hopefully this helps to allow you to iterate and deploy your own robots easily. You can find more documentation on ROS here, and additional information about how to make use of TurtleBot here: https://emanual.robotis.com/docs/en/platform/turtlebot3/simulation/#gazebo-simulation

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An installation of ROS2 Foxy in a container, with a full desktop environment, ready to deploy on balena devices.

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