home / skills / a5c-ai / babysitter / gazebo-simulation
This skill helps you design and deploy Gazebo simulations by generating SDF worlds, configuring physics, sensors, and plugins for multi-robot scenarios.
npx playbooks add skill a5c-ai/babysitter --skill gazebo-simulationReview the files below or copy the command above to add this skill to your agents.
---
name: gazebo-simulation
description: Expert skill for Gazebo Classic and Ignition/Gazebo Sim world creation and plugin development. Create SDF worlds with terrain, lighting, physics configuration, sensor models, and custom plugins.
allowed-tools: Bash(*) Read Write Edit Glob Grep WebFetch
metadata:
author: babysitter-sdk
version: "1.0.0"
category: simulation
backlog-id: SK-002
---
# gazebo-simulation
You are **gazebo-simulation** - a specialized skill for Gazebo simulation environment creation, configuration, and plugin development.
## Overview
This skill enables AI-powered Gazebo simulation including:
- Creating SDF world files with terrain, lighting, and physics
- Configuring physics engine parameters (ODE, Bullet, DART)
- Implementing Gazebo plugins (model, world, sensor, visual)
- Generating sensor models (camera, LiDAR, IMU, GPS, depth)
- Setting up contact sensors and force-torque sensors
- Configuring dynamic actors and animated models
- Implementing custom physics materials and friction
- Creating procedural world generation
- Optimizing simulation performance (LOD, collision simplification)
- Setting up multi-robot simulation instances
## Prerequisites
- Gazebo Sim (Harmonic, Ionic) or Gazebo Classic (11)
- ROS2 with gazebo_ros_pkgs
- SDF specification knowledge
- C++ development tools for custom plugins
## Capabilities
### 1. World File Creation
Generate SDF world files:
```xml
<?xml version="1.0" ?>
<sdf version="1.8">
<world name="robot_world">
<!-- Physics Configuration -->
<physics name="default_physics" type="ode">
<max_step_size>0.001</max_step_size>
<real_time_factor>1.0</real_time_factor>
<real_time_update_rate>1000</real_time_update_rate>
<ode>
<solver>
<type>quick</type>
<iters>50</iters>
<sor>1.3</sor>
</solver>
<constraints>
<cfm>0.0</cfm>
<erp>0.2</erp>
<contact_max_correcting_vel>100.0</contact_max_correcting_vel>
<contact_surface_layer>0.001</contact_surface_layer>
</constraints>
</ode>
</physics>
<!-- Lighting -->
<light type="directional" name="sun">
<cast_shadows>true</cast_shadows>
<pose>0 0 10 0 0 0</pose>
<diffuse>0.8 0.8 0.8 1</diffuse>
<specular>0.2 0.2 0.2 1</specular>
<direction>-0.5 0.1 -0.9</direction>
</light>
<light type="point" name="point_light">
<pose>5 5 3 0 0 0</pose>
<diffuse>0.5 0.5 0.5 1</diffuse>
<specular>0.1 0.1 0.1 1</specular>
<attenuation>
<range>20</range>
<linear>0.05</linear>
<quadratic>0.001</quadratic>
</attenuation>
</light>
<!-- Ground Plane -->
<model name="ground_plane">
<static>true</static>
<link name="link">
<collision name="collision">
<geometry>
<plane>
<normal>0 0 1</normal>
<size>100 100</size>
</plane>
</geometry>
<surface>
<friction>
<ode>
<mu>100</mu>
<mu2>50</mu2>
</ode>
</friction>
</surface>
</collision>
<visual name="visual">
<geometry>
<plane>
<normal>0 0 1</normal>
<size>100 100</size>
</plane>
</geometry>
<material>
<ambient>0.8 0.8 0.8 1</ambient>
<diffuse>0.8 0.8 0.8 1</diffuse>
</material>
</visual>
</link>
</model>
<!-- Include Models -->
<include>
<uri>model://my_robot</uri>
<name>robot1</name>
<pose>0 0 0.1 0 0 0</pose>
</include>
<!-- Plugins -->
<plugin filename="gz-sim-physics-system" name="gz::sim::systems::Physics"/>
<plugin filename="gz-sim-user-commands-system" name="gz::sim::systems::UserCommands"/>
<plugin filename="gz-sim-scene-broadcaster-system" name="gz::sim::systems::SceneBroadcaster"/>
<plugin filename="gz-sim-sensors-system" name="gz::sim::systems::Sensors">
<render_engine>ogre2</render_engine>
</plugin>
</world>
</sdf>
```
### 2. Physics Engine Configuration
Configure different physics engines:
```xml
<!-- ODE (Default, fast) -->
<physics name="ode_physics" type="ode">
<max_step_size>0.001</max_step_size>
<real_time_factor>1.0</real_time_factor>
<ode>
<solver>
<type>quick</type>
<iters>50</iters>
</solver>
</ode>
</physics>
<!-- Bullet (Better for complex collisions) -->
<physics name="bullet_physics" type="bullet">
<max_step_size>0.001</max_step_size>
<real_time_factor>1.0</real_time_factor>
<bullet>
<solver>
<type>sequential_impulse</type>
<iters>50</iters>
<sor>1.3</sor>
</solver>
</bullet>
</physics>
<!-- DART (Best for robotics, articulated bodies) -->
<physics name="dart_physics" type="dart">
<max_step_size>0.001</max_step_size>
<real_time_factor>1.0</real_time_factor>
<dart>
<collision_detector>fcl</collision_detector>
<solver>
<solver_type>pgs</solver_type>
</solver>
</dart>
</physics>
```
### 3. Sensor Configuration
Add various sensors to robots:
```xml
<!-- Camera Sensor -->
<sensor name="camera" type="camera">
<always_on>true</always_on>
<update_rate>30</update_rate>
<camera>
<horizontal_fov>1.3962634</horizontal_fov>
<image>
<width>640</width>
<height>480</height>
<format>R8G8B8</format>
</image>
<clip>
<near>0.1</near>
<far>100</far>
</clip>
<noise>
<type>gaussian</type>
<mean>0</mean>
<stddev>0.007</stddev>
</noise>
</camera>
<plugin filename="gz-sim-camera-system" name="gz::sim::systems::Camera"/>
</sensor>
<!-- Depth Camera -->
<sensor name="depth_camera" type="depth_camera">
<always_on>true</always_on>
<update_rate>15</update_rate>
<camera>
<horizontal_fov>1.047</horizontal_fov>
<image>
<width>640</width>
<height>480</height>
<format>R_FLOAT32</format>
</image>
<clip>
<near>0.1</near>
<far>10</far>
</clip>
</camera>
<plugin filename="gz-sim-depth-camera-system" name="gz::sim::systems::DepthCamera"/>
</sensor>
<!-- LiDAR Sensor -->
<sensor name="lidar" type="gpu_lidar">
<always_on>true</always_on>
<update_rate>10</update_rate>
<lidar>
<scan>
<horizontal>
<samples>640</samples>
<resolution>1</resolution>
<min_angle>-3.14159</min_angle>
<max_angle>3.14159</max_angle>
</horizontal>
<vertical>
<samples>16</samples>
<resolution>1</resolution>
<min_angle>-0.26</min_angle>
<max_angle>0.26</max_angle>
</vertical>
</scan>
<range>
<min>0.3</min>
<max>100</max>
<resolution>0.01</resolution>
</range>
<noise>
<type>gaussian</type>
<mean>0</mean>
<stddev>0.01</stddev>
</noise>
</lidar>
<plugin filename="gz-sim-gpu-lidar-system" name="gz::sim::systems::GpuLidar"/>
</sensor>
<!-- IMU Sensor -->
<sensor name="imu" type="imu">
<always_on>true</always_on>
<update_rate>200</update_rate>
<imu>
<angular_velocity>
<x>
<noise type="gaussian">
<mean>0.0</mean>
<stddev>0.0002</stddev>
</noise>
</x>
<y>
<noise type="gaussian">
<mean>0.0</mean>
<stddev>0.0002</stddev>
</noise>
</y>
<z>
<noise type="gaussian">
<mean>0.0</mean>
<stddev>0.0002</stddev>
</noise>
</z>
</angular_velocity>
<linear_acceleration>
<x>
<noise type="gaussian">
<mean>0.0</mean>
<stddev>0.017</stddev>
</noise>
</x>
</linear_acceleration>
</imu>
<plugin filename="gz-sim-imu-system" name="gz::sim::systems::Imu"/>
</sensor>
<!-- GPS Sensor -->
<sensor name="gps" type="navsat">
<always_on>true</always_on>
<update_rate>5</update_rate>
<navsat>
<position_sensing>
<horizontal>
<noise type="gaussian">
<mean>0</mean>
<stddev>0.5</stddev>
</noise>
</horizontal>
<vertical>
<noise type="gaussian">
<mean>0</mean>
<stddev>1.0</stddev>
</noise>
</vertical>
</position_sensing>
</navsat>
<plugin filename="gz-sim-navsat-system" name="gz::sim::systems::NavSat"/>
</sensor>
```
### 4. ROS2-Gazebo Bridge
Configure ROS2 bridge for topics:
```xml
<!-- In world file -->
<plugin filename="gz-sim-ros-gz-bridge" name="ros_gz_bridge::RosGzBridge">
<ros>
<namespace>/robot</namespace>
</ros>
<!-- Camera -->
<bridge topic="/camera/image_raw" ros_topic="/robot/camera/image_raw" type="sensor_msgs/msg/Image" direction="GZ_TO_ROS"/>
<bridge topic="/camera/camera_info" ros_topic="/robot/camera/camera_info" type="sensor_msgs/msg/CameraInfo" direction="GZ_TO_ROS"/>
<!-- LiDAR -->
<bridge topic="/lidar/points" ros_topic="/robot/scan" type="sensor_msgs/msg/PointCloud2" direction="GZ_TO_ROS"/>
<!-- IMU -->
<bridge topic="/imu" ros_topic="/robot/imu" type="sensor_msgs/msg/Imu" direction="GZ_TO_ROS"/>
<!-- Velocity Commands -->
<bridge topic="/cmd_vel" ros_topic="/robot/cmd_vel" type="geometry_msgs/msg/Twist" direction="ROS_TO_GZ"/>
<!-- Odometry -->
<bridge topic="/odom" ros_topic="/robot/odom" type="nav_msgs/msg/Odometry" direction="GZ_TO_ROS"/>
<!-- Joint States -->
<bridge topic="/joint_states" ros_topic="/robot/joint_states" type="sensor_msgs/msg/JointState" direction="GZ_TO_ROS"/>
<!-- TF -->
<bridge topic="/tf" ros_topic="/tf" type="tf2_msgs/msg/TFMessage" direction="GZ_TO_ROS"/>
</plugin>
```
### 5. Terrain and Environment
Create terrain and environment models:
```xml
<!-- Heightmap Terrain -->
<model name="terrain">
<static>true</static>
<link name="link">
<collision name="collision">
<geometry>
<heightmap>
<uri>file://terrain/heightmap.png</uri>
<size>100 100 10</size>
<pos>0 0 0</pos>
</heightmap>
</geometry>
</collision>
<visual name="visual">
<geometry>
<heightmap>
<uri>file://terrain/heightmap.png</uri>
<size>100 100 10</size>
<pos>0 0 0</pos>
<texture>
<diffuse>file://terrain/grass.png</diffuse>
<normal>file://terrain/grass_normal.png</normal>
<size>10</size>
</texture>
</heightmap>
</geometry>
</visual>
</link>
</model>
<!-- Obstacles -->
<model name="obstacle_box">
<static>true</static>
<pose>5 3 0.5 0 0 0</pose>
<link name="link">
<collision name="collision">
<geometry>
<box>
<size>1 1 1</size>
</box>
</geometry>
</collision>
<visual name="visual">
<geometry>
<box>
<size>1 1 1</size>
</box>
</geometry>
<material>
<ambient>0.5 0.5 0.5 1</ambient>
</material>
</visual>
</link>
</model>
```
### 6. Custom Plugin Development
Create custom Gazebo plugins:
```cpp
// WorldPlugin example
#include <gz/sim/System.hh>
#include <gz/plugin/Register.hh>
namespace my_plugins {
class MyWorldPlugin : public gz::sim::System,
public gz::sim::ISystemConfigure,
public gz::sim::ISystemPreUpdate
{
public:
void Configure(const gz::sim::Entity &_entity,
const std::shared_ptr<const sdf::Element> &_sdf,
gz::sim::EntityComponentManager &_ecm,
gz::sim::EventManager &_eventMgr) override
{
// Configuration on load
gzmsg << "MyWorldPlugin configured" << std::endl;
}
void PreUpdate(const gz::sim::UpdateInfo &_info,
gz::sim::EntityComponentManager &_ecm) override
{
// Called before each simulation step
if (_info.paused)
return;
// Custom logic here
}
};
}
GZ_ADD_PLUGIN(my_plugins::MyWorldPlugin,
gz::sim::System,
my_plugins::MyWorldPlugin::ISystemConfigure,
my_plugins::MyWorldPlugin::ISystemPreUpdate)
```
### 7. Launch File Integration
Launch Gazebo with ROS2:
```python
from launch import LaunchDescription
from launch.actions import IncludeLaunchDescription, DeclareLaunchArgument
from launch.launch_description_sources import PythonLaunchDescriptionSource
from launch.substitutions import LaunchConfiguration, PathJoinSubstitution
from launch_ros.actions import Node
from launch_ros.substitutions import FindPackageShare
def generate_launch_description():
pkg_share = FindPackageShare('my_robot_gazebo')
# World file
world_file = PathJoinSubstitution([pkg_share, 'worlds', 'robot_world.sdf'])
# Gazebo launch
gazebo = IncludeLaunchDescription(
PythonLaunchDescriptionSource([
FindPackageShare('ros_gz_sim'), '/launch/gz_sim.launch.py'
]),
launch_arguments={
'gz_args': ['-r ', world_file],
'on_exit_shutdown': 'true'
}.items()
)
# Spawn robot
spawn_robot = Node(
package='ros_gz_sim',
executable='create',
arguments=[
'-name', 'my_robot',
'-topic', '/robot_description',
'-x', '0', '-y', '0', '-z', '0.1'
],
output='screen'
)
# ROS-GZ Bridge
bridge = Node(
package='ros_gz_bridge',
executable='parameter_bridge',
arguments=[
'/cmd_vel@geometry_msgs/msg/[email protected]',
'/odom@nav_msgs/msg/[email protected]',
'/scan@sensor_msgs/msg/[email protected]'
],
output='screen'
)
return LaunchDescription([
gazebo,
spawn_robot,
bridge
])
```
## MCP Server Integration
This skill can leverage the following MCP servers for enhanced capabilities:
| Server | Description | Installation |
|--------|-------------|--------------|
| Gazebo MCP Server | ROS2 MCP for Gazebo | [lobehub.com](https://lobehub.com/mcp/yourusername-gazebo-mcp) |
| ros-mcp-server | ROS/ROS2 bridge | [GitHub](https://github.com/robotmcp/ros-mcp-server) |
## Best Practices
1. **Use appropriate physics** - Choose physics engine based on requirements
2. **Sensor noise** - Add realistic noise models to sensors
3. **Collision simplification** - Use simplified collision geometry
4. **Real-time factor** - Adjust for simulation vs real-time requirements
5. **Resource management** - Disable unused sensors to improve performance
6. **Modular worlds** - Use includes for reusable world components
## Process Integration
This skill integrates with the following processes:
- `gazebo-simulation-setup.js` - Primary simulation setup
- `digital-twin-development.js` - Digital twin creation
- `synthetic-data-pipeline.js` - Training data generation
- `simulation-performance-optimization.js` - Performance tuning
- `hil-testing.js` - Hardware-in-the-loop testing
## Output Format
When executing operations, provide structured output:
```json
{
"operation": "create-world",
"worldName": "robot_world",
"status": "success",
"configuration": {
"physicsEngine": "ode",
"realTimeFactor": 1.0,
"sensors": ["camera", "lidar", "imu"]
},
"artifacts": [
"worlds/robot_world.sdf",
"launch/simulation.launch.py"
],
"launchCommand": "ros2 launch my_robot_gazebo simulation.launch.py"
}
```
## Constraints
- Verify Gazebo version compatibility (Classic vs Sim)
- Check SDF version for feature availability
- Test sensor update rates for performance impact
- Validate physics parameters for stability
- Ensure ROS-GZ bridge topic compatibility
This skill provides expert assistance for creating Gazebo Classic and Ignition/Gazebo Sim worlds, configuring physics, and developing custom plugins. It focuses on producing SDF world files, realistic sensor models, terrain and lighting setups, ROS2 bridges, and performant multi-robot simulations. The guidance covers both world-level configuration and plugin code examples to speed development and debugging.
The skill generates SDF snippets and complete world files with physics, lighting, terrain, and included models. It produces sensor configurations (camera, LiDAR, IMU, GPS, depth), ROS2-Gazebo bridge mappings, and example C++ systems/plugins following Gazebo Sim APIs. It also suggests physics engine choices, tuning parameters, and launch file integration for ROS2-based workflows.
Which physics engine should I pick for legged robots?
Use DART for articulated bodies and robots with complex joint dynamics; tune PGS or solver iterations for stability.
How do I reduce simulation CPU load with many sensors?
Lower sensor update rates, reduce image resolution/points, simplify collision meshes, and use GPU-accelerated sensors where available.