If you’ve just opened the door to ROS2 (Robot Operating System 2), chances are the learning curve already feels overwhelming. Between C++, ament build tools, Linux commands, and a brand-new communication architecture, it can feel like you’re expected to know everything at once.
The truth is, you don’t need to jump into every tutorial you find. What you need is a structured roadmap—a way to build each skill step by step so you’re not left guessing whether your error comes from ROS2 itself or your own code.
Here’s how to start ROS2 the right way.
Step 1: Get Comfortable with C++
ROS2 is written in C++. If you don’t understand the language, debugging ROS2 nodes will feel like solving a puzzle in the dark. Start small:
Write single-file programs like hello.cpp and compile with g++.
Progress to multi-file projects (main.cpp, MotorController.cpp, MotorController.hpp).
Learn how modular code compiles together—this mirrors how ROS2 packages are structured.
By doing this outside ROS2, you remove complexity and build confidence with the basics.
Step 2: Learn CMake Before Ament
ROS2 packages rely on ament_cmake, but the foundation is still CMake. Build small projects using CMakeLists.txt, then move on to libraries and unit tests. Example:
add_library(motor_driver MotorDriver.cpp)
add_executable(robot_node main.cpp)
target_link_libraries(robot_node motor_driver)
This practice sets you up to understand how real ROS2 packages are built.
Step 3: Master the Command Line
You’ll spend most of your ROS2 time in a terminal. Commands like cd, source, mkdir, and export are essential when creating workspaces, launching nodes, and managing environments. If you’re not fluent here, even simple ROS2 tasks will be frustrating.
Step 4: First ROS2 Steps — Topics, Nodes, and Messages
Once you’re ready, begin with the core of ROS2: nodes publishing and subscribing to topics.
Write a talker node that publishes strings to /chatter.
Write a listener node that subscribes to /chatter.
Use ros2 topic echo /chatter and rqt_graph to see communication in action.
This simple exercise unlocks the messaging system that powers every robot.
Step 5: Use Simulation Before Real Hardware
Before connecting motors and sensors, use a simulated robot. The TurtleBot3 Gazebo world is perfect for beginners. You can practice publishing velocity commands, viewing lidar scans, and testing navigation stacks without risking your hardware.
ros2 launch turtlebot3_gazebo turtlebot3_world.launch.py
ros2 topic pub /cmd_vel geometry_msgs/Twist "{linear: {x: 0.1}, angular: {z: 0.1}}"
Simulation builds intuition while protecting your time (and your robot).
Step 6: Bring Your Own C++ Code into ROS2
Finally, integrate your C++ libraries into ROS2 packages. Suppose you wrote a SensorFusion class earlier—wrap it inside a ROS2 node, link it with ament_cmake, and test it against simulated sensor data. This approach keeps your core logic independent of ROS2 while making it usable inside a robotics system.
A Clearer Path to ROS2
Instead of jumping randomly between tutorials, this roadmap ensures you learn the right skill at the right time:
C++ basics → understand logic
CMake → build modular projects
CLI skills → navigate ROS2 environments
ROS2 core → topics, nodes, messages
Simulation → test safely before hardware
Integration → combine your libraries with ROS2
By separating software engineering fundamentals from ROS2 specifics, you’ll always know where to look when something breaks.
Final Thoughts
ROS2 doesn’t have to feel like a wall of errors. With a step-by-step approach—first mastering C++, then CMake, then ROS2—you’ll move from confusion to confidence.
At Robotisim, we’ve built this same roadmap into our Mobile Robotics Engineering course. It’s the difference between “copy-paste until it works” and truly learning how robotics software is built.
Start small. Build strong fundamentals. Then let ROS2 bring your robots to life.
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