ROS2 Bootcamp

Four-session ROS2 bootcamp covering the full arc from mental model to autonomous robot behavior.

Sessions

#	Title	Core Skill
1	Mental Model + Survival Skills	Nodes, topics, CLI tools
2	Build Real ROS Nodes	Publisher, subscriber, colcon workspace
3	Simulation and Visualization	Gazebo, RViz2, sensor topics
4	Integration Project	Closed-loop system: sensor → decision → action

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Quick Start

All sessions run in the same Docker container. No ROS2 installation needed on the student machine — only Docker.

First time only — build the image (~10 min)

cd docker/
docker compose build

Start any session

bash docker/start.sh 1     # Session 1
bash docker/start.sh 2     # Session 2
bash docker/start.sh 3     # Session 3
bash docker/start.sh 4     # Session 4

Open a terminal in the running container

docker exec -it ros2_bootcamp bash

Open as many terminals as needed — each docker exec opens a new one.

Stop

bash docker/start.sh stop

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Repository Structure

ROS_bootcamp/
├── README.md
├── docker/                     ← Shared Docker setup (build once, use for all sessions)
│   ├── Dockerfile
│   ├── docker-compose.yml
│   ├── entrypoint.sh
│   ├── patch_worlds.py
│   └── start.sh
├── session_01/
│   ├── README.md               ← Session 1 outline
│   └── workspace/              ← Files available inside container at ~/workspace
│       ├── demo_publisher.py
│       ├── demo_subscriber.py
│       └── modify_me.py
├── session_02/
│   ├── README.md               ← Session 2 outline
│   └── workspace/
│       ├── fake_sensor.py
│       ├── processor.py
│       └── processor_todo.py
├── session_03/
│   ├── README.md               ← Session 3 outline
│   └── workspace/
│       ├── tb3_sim.launch.py
│       ├── scan_subscriber.py
│       ├── wall_follower_solution.py
│       ├── wall_follower_todo.py
│       └── ...
└── session_04/
    ├── README.md               ← Session 4 outline
    └── workspace/
        ├── obstacle_avoider_todo.py
        └── obstacle_avoider_solution.py

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Prerequisites

• Ubuntu (20.04 or 22.04)
• Docker + Docker Compose
• For sessions 3 and 4: a display (GUI required for Gazebo + RViz2)

Docker install

curl -fsSL https://get.docker.com | sh
sudo usermod -aG docker $USER
# Log out and back in
docker run hello-world   # verify

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Native ROS2 (Alternative)

If a student has ROS2 Humble installed natively:

# Install TB3 packages (needed for sessions 3 and 4)
sudo apt install ros-humble-turtlebot3 ros-humble-turtlebot3-simulations ros-humble-gazebo-ros-pkgs

# Set environment
export TURTLEBOT3_MODEL=waffle
export LIBGL_ALWAYS_SOFTWARE=1

# Run setup check (session 3 only)
bash session_03/workspace/setup_check.sh

Sessions 1 and 2 only need ROS2 Humble — no extra packages.