TurtleBot3 Behavior Demos

In this repository, we demonstrate autonomous behavior with a simulated ROBOTIS TurtleBot3 using Ubuntu 22.04 and ROS 2 Humble.

The autonomy in these examples are designed using behavior trees. For more information, refer to this blog post or the Behavior Trees in Robotics and AI textbook.

This also serves as an example for Docker workflows in ROS based projects. For more information, refer to this blog post.

If you want to use ROS 1, check out the old version of this example from the noetic branch of this repository.

By Sebastian Castro, 2021-2023

Setup

Docker Setup (Recommended)

First, install Docker and Docker Compose using the official install guide.

To run Docker containers with graphics and GPU support, you will also need the NVIDIA Container Toolkit.

To use GUI based tools (e.g., RViz, Gazebo) inside Docker, there is additional setup required. The simplest way is to run the command below each time you log into your machine, but there is a more detailed walkthrough of options in the ROS Wiki.

xhost + local:docker

First, clone this repository and go into the top-level folder:

git clone https://github.com/sea-bass/turtlebot3_behavior_demos.git
cd turtlebot3_behavior_demos

Build the Docker images. This will take a while and requires approximately 5 GB of disk space.

docker compose build

Local Setup

If you do not want to use Docker, you can directly clone this package to a Colcon workspace and build it provided you have the necessary dependencies. As long as you can run the examples in the TurtleBot3 manual, you should be in good shape.

First, make a Colcon workspace and clone this repo there:

mkdir -p turtlebot3_ws/src
cd turtlebot3_ws/src
git clone https://github.com/sea-bass/turtlebot3_behavior_demos.git

Clone the external dependencies:

sudo apt-get install python3-vcstool
vcs import < turtlebot3_behavior_demos/dependencies.repos

Set up any additional dependencies using rosdep:

sudo apt update && rosdep install -r --from-paths . --ignore-src --rosdistro $ROS_DISTRO -y

Then, build the workspace.

cd turtlebot3_ws
colcon build

Basic Usage

We use Docker Compose to automate building, as shown above, but also for various useful entry points into the Docker container once it has been built. All docker compose commands below should be run from your host machine, and not from inside the container.

To enter a Terminal in the overlay container, first start a container:

docker compose up overlay

Then, in a separate Terminal, you can access the running container:

docker exec -it turtlebot3_behavior_demos-overlay-1 bash

You can verify that display in Docker works by starting a basic Gazebo simulation included in the standard TurtleBot3 packages:

docker compose up sim

Behavior Trees Demo

In this example, the robot navigates around known locations with the goal of finding a block of a specified color (red, green, or blue). Object detection is done using simple thresholding in the HSV color space with calibrated values.

To start the demo world, run the following command:

docker compose up demo-world

Behavior Trees in Python

To start the Python based demo, which uses py_trees:

docker compose up demo-behavior-py

You can also change the following environment variables to set arguments for the launch files, or by modifying the defaults in the .env file:

TARGET_COLOR=green BT_TYPE=queue ENABLE_VISION=true docker compose up demo-behavior-py

Note that the behavior tree viewer (py_trees_ros_viewer) should automatically discover the ROS node containing the behavior tree and visualize it.

After starting the commands above (plus doing some waiting and window rearranging), you should see the following. The labeled images will appear once the robot reaches a target location.

Behavior Trees in C++

To start the C++ demo, which uses BehaviorTree.CPP:

docker compose up demo-behavior-cpp