Gazebo Lessons

Introduction to Gazebo & ROS Integration Learn what Gazebo simulates, how its physics and sensors work, how Gazebo Classic differs from the newer Gazebo line, and how ROS nodes communicate with the simulation through topics, services, and plugins. Th

// Gazebo and ROS integration mental model
// Gazebo world -> sensors -> plugins -> bridge -> ROS topics
#include <iostream>

int main() {
    std::cout << "/cmd_vel -> differential drive plugin" << std::endl;
    std::cout << "/scan -> lidar sensor stream" << std::endl;
    std::cout << "/joint_states -> simulated robot state" << std::endl;
    return 0;
}

Installing ROS + Gazebo Install ROS and Gazebo, verify the environment, and run a known world so the toolchain is proven before deeper robotics work begins. These lessons explain what Gazebo is, how it fits next. Gazebo is not only a 3D viewer. It is

# Install ROS 2 and Gazebo
sudo apt install ros-humble-desktop
sudo apt install ros-humble-ros-gz

# Verify with a sample world
gz sim shapes.sdf

URDF Basics (Robot Description) Describe a robot with links, joints, visuals, collisions, inertials, and sensors so Gazebo has a robot model worth simulating. These lessons explain what Gazebo is, how it fits next. Gazebo is not only a 3D viewer. It

<robot name="demo_bot">
  <link name="base_link">
    <visual><geometry><box size="0.4 0.3 0.2"/></geometry></visual>
    <collision><geometry><box size="0.4 0.3 0.2"/></geometry></collision>
    <inertial><mass value="4.0"/></inertial>
  </link>
  <joint name="laser_joint" type="fixed">
    <parent link="base_link"/>
    <child link="laser_link"/>
  </joint>
</robot>

SDF Basics (World & Model Description) Use SDF to describe worlds, simulation properties, and model-level details that go beyond a basic robot description. These lessons focus on the files and runtime steps that. URDF usually describes the robot, SDF

<sdf version="1.9">
  <world name="warehouse_world">
    <physics type="ode"/>
    <light name="sun" type="directional"/>
    <model name="ground_plane"/>
  </world>
</sdf>

Spawning Robots in Gazebo Load a robot description into a running simulation, spawn the entity cleanly, and connect it to controllers. These lessons focus on the files and runtime steps that. URDF usually describes the robot, SDF usually describes th

# Spawn a robot described by URDF
ros2 run gazebo_ros spawn_entity.py \
  -entity demo_bot \
  -topic /robot_description

# Or launch with controllers
ros2 launch demo_bot_bringup sim.launch.py

ROS-Gazebo Bridge Bridge the simulation transport layer to ROS topics and services so commands and sensors move across the boundary correctly. These lessons focus on the files and runtime steps that. URDF usually describes the robot, SDF usually desc

# Example bridge mappings
ros2 run ros_gz_bridge parameter_bridge \
  /cmd_vel@geometry_msgs/msg/Twist@gz.msgs.Twist \
  /scan@sensor_msgs/msg/LaserScan@gz.msgs.LaserScan \
  /joint_states@sensor_msgs/msg/JointState@gz.msgs.Model

Controlling Robots Publish commands, subscribe to state, and build safe control loops that behave predictably in simulation. These lessons show how commands, sensors, plugins, and controller loops. A useful simulation is more than visuals. It must pu

#include <chrono>
#include <iostream>

int main() {
    double cmdVel = 0.3;
    double maxVel = 0.5;
    bool emergencyStop = false;
    if (!emergencyStop && cmdVel <= maxVel) std::cout << "publish /cmd_vel" << std::endl;
    return 0;
}

Sensors & Plugins Attach realistic sensors and motion plugins so the robot can publish data and respond to actuators like a real platform. These lessons show how commands, sensors, plugins, and controller loops. A useful simulation is more than visua

<plugin name="diff_drive" filename="gz-sim-diff-drive-system">
  <left_joint>left_wheel_joint</left_joint>
  <right_joint>right_wheel_joint</right_joint>
  <topic>/cmd_vel</topic>
</plugin>

<sensor name="front_lidar" type="gpu_lidar"/>

Navigation & SLAM (Advanced) Connect Nav2-style navigation, mapping, localization, and planning workflows to Gazebo so autonomous motion can be tested before hardware. These lessons connect Gazebo to navigation workflows and then turn. The goal is no

# Launch simulated navigation
ros2 launch nav2_bringup navigation_launch.py use_sim_time:=true
ros2 launch slam_toolbox online_async_launch.py use_sim_time:=true

# Goal topics and maps can now be tested in Gazebo

Building Reusable Simulation Skills Turn the whole Gazebo workflow into reusable skills for spawning, bridging, sensors, and control so future robot projects start faster and with fewer mistakes. These lessons connect Gazebo to navigation workflows a

// Reusable Gazebo workflow checklist
#include <iostream>
#include <vector>

int main() {
    std::vector<const char*> skills = {"spawn robots", "bridge topics", "integrate sensors", "run safe control loops"};
    for (const auto* skill : skills) std::cout << skill << std::endl;
    return 0;
}