Section 4: URDF with Sensors

Introduction

In Chapter 2, you learned to create URDF robot descriptions. Now you'll extend those models by adding Gazebo sensor plugins that simulate LIDAR, cameras, and IMUs.

Sensors in URDF require:

1. A link representing the sensor's physical location
2. A Gazebo plugin that generates sensor data
3. ROS 2 topic configuration for publishing data

Adding LIDAR to a Robot

Let's add a 2D LIDAR sensor to a simple mobile robot.

Step 1: Add Sensor Link

<link name="lidar_link">
  <visual>
    <geometry>
      <cylinder>
        <radius>0.05</radius>
        <length>0.07</length>
      </cylinder>
    </geometry>
    <material name="black">
      <color rgba="0 0 0 1"/>
    </material>
  </visual>

  <collision>
    <geometry>
      <cylinder>
        <radius>0.05</radius>
        <length>0.07</length>
      </cylinder>
    </geometry>
  </collision>

  <inertial>
    <mass value="0.1"/>
    <inertia ixx="0.0001" ixy="0" ixz="0" iyy="0.0001" iyz="0" izz="0.0001"/>
  </inertial>
</link>

<joint name="lidar_joint" type="fixed">
  <parent link="base_link"/>
  <child link="lidar_link"/>
  <origin xyz="0.2 0 0.15" rpy="0 0 0"/>
</joint>

This creates a small cylinder representing the LIDAR, mounted 0.2m forward and 0.15m up from the robot base.

Step 2: Add Gazebo LIDAR Plugin

<gazebo reference="lidar_link">
  <sensor name="lidar_sensor" type="ray">
    <pose>0 0 0 0 0 0</pose>
    <visualize>true</visualize>
    <update_rate>10</update_rate>

    <ray>
      <scan>
        <horizontal>
          <samples>720</samples>
          <resolution>1</resolution>
          <min_angle>-3.14159</min_angle>
          <max_angle>3.14159</max_angle>
        </horizontal>
      </scan>

      <range>
        <min>0.10</min>
        <max>10.0</max>
        <resolution>0.01</resolution>
      </range>

      <noise>
        <type>gaussian</type>
        <mean>0.0</mean>
        <stddev>0.01</stddev>
      </noise>
    </ray>

    <plugin name="gazebo_ros_laser_controller" filename="libgazebo_ros_ray_sensor.so">
      <ros>
        <namespace>/robot</namespace>
        <remapping>~/out:=scan</remapping>
      </ros>
      <output_type>sensor_msgs/LaserScan</output_type>
      <frame_name>lidar_link</frame_name>
    </plugin>
  </sensor>
</gazebo>

LIDAR Parameter Explanation

Parameter	Description	Example Value
samples	Number of laser beams	720 (0.5° resolution)
min_angle / max_angle	Scan range in radians	-π to +π (360°)
min / max range	Detection distance (m)	0.1m to 10m
update_rate	Scans per second (Hz)	10 Hz
noise stddev	Gaussian noise std dev	0.01m (1cm)

Step 3: Test the LIDAR

# Launch Gazebo with your robot
ros2 launch my_robot_description gazebo.launch.py

# Check if LIDAR is publishing
ros2 topic list | grep scan

# View LIDAR data
ros2 topic echo /robot/scan

# Visualize in RViz
ros2 run rviz2 rviz2

In RViz:

• Set Fixed Frame to base_link
• Add → By Topic → /robot/scan → LaserScan
• You'll see red lines showing laser beams

Adding an RGB Camera

Cameras provide visual information for object recognition and navigation.

Step 1: Add Camera Link

<link name="camera_link">
  <visual>
    <geometry>
      <box size="0.05 0.05 0.05"/>
    </geometry>
    <material name="blue">
      <color rgba="0 0 1 1"/>
    </material>
  </visual>

  <collision>
    <geometry>
      <box size="0.05 0.05 0.05"/>
    </geometry>
  </collision>

  <inertial>
    <mass value="0.05"/>
    <inertia ixx="0.0001" ixy="0" ixz="0" iyy="0.0001" iyz="0" izz="0.0001"/>
  </inertial>
</link>

<joint name="camera_joint" type="fixed">
  <parent link="base_link"/>
  <child link="camera_link"/>
  <origin xyz="0.15 0 0.2" rpy="0 0 0"/>
</joint>

Step 2: Add Gazebo Camera Plugin

<gazebo reference="camera_link">
  <sensor name="camera_sensor" type="camera">
    <update_rate>30</update_rate>
    <visualize>true</visualize>

    <camera name="camera">
      <horizontal_fov>1.3962634</horizontal_fov>
      <image>
        <width>640</width>
        <height>480</height>
        <format>R8G8B8</format>
      </image>
      <clip>
        <near>0.02</near>
        <far>300</far>
      </clip>

      <noise>
        <type>gaussian</type>
        <mean>0.0</mean>
        <stddev>0.007</stddev>
      </noise>
    </camera>

    <plugin name="gazebo_ros_camera_controller" filename="libgazebo_ros_camera.so">
      <ros>
        <namespace>/robot</namespace>
        <remapping>~/image_raw:=camera/image_raw</remapping>
        <remapping>~/camera_info:=camera/camera_info</remapping>
      </ros>
      <camera_name>camera</camera_name>
      <frame_name>camera_link</frame_name>
      <hack_baseline>0.07</hack_baseline>
    </plugin>
  </sensor>
</gazebo>

Camera Parameter Explanation

Parameter	Description	Example Value
horizontal_fov	Field of view (radians)	1.3962634 (80°)
width x height	Image resolution	640x480 pixels
format	Color format	R8G8B8 (RGB 8-bit)
near / far clip	Render distance (m)	0.02m to 300m
update_rate	Frames per second	30 Hz

Step 3: View Camera Feed

# Check camera topics
ros2 topic list | grep camera

# View image data
ros2 run rqt_image_view rqt_image_view /robot/camera/image_raw

Adding a Depth Camera

Depth cameras (like Intel RealSense) provide RGB + depth maps.

Gazebo Depth Camera Plugin

<gazebo reference="depth_camera_link">
  <sensor name="depth_camera" type="depth">
    <update_rate>20</update_rate>
    <visualize>true</visualize>

    <camera name="depth_camera">
      <horizontal_fov>1.047198</horizontal_fov>
      <image>
        <width>640</width>
        <height>480</height>
        <format>R8G8B8</format>
      </image>
      <clip>
        <near>0.05</near>
        <far>3.0</far>
      </clip>
    </camera>

    <plugin name="gazebo_ros_depth_camera" filename="libgazebo_ros_camera.so">
      <ros>
        <namespace>/robot</namespace>
        <remapping>~/image_raw:=depth_camera/image_raw</remapping>
        <remapping>~/depth/image_raw:=depth_camera/depth/image_raw</remapping>
        <remapping>~/points:=depth_camera/points</remapping>
      </ros>
      <camera_name>depth_camera</camera_name>
      <frame_name>depth_camera_link</frame_name>
      <hack_baseline>0.07</hack_baseline>
    </plugin>
  </sensor>
</gazebo>

The depth camera publishes:

• /robot/depth_camera/image_raw: RGB image
• /robot/depth_camera/depth/image_raw: Depth map (distance to each pixel)
• /robot/depth_camera/points: 3D point cloud

Adding an IMU

IMU (Inertial Measurement Unit) measures acceleration, angular velocity, and orientation.

Step 1: Add IMU Link

<link name="imu_link">
  <visual>
    <geometry>
      <box size="0.02 0.02 0.01"/>
    </geometry>
    <material name="red">
      <color rgba="1 0 0 1"/>
    </material>
  </visual>

  <inertial>
    <mass value="0.01"/>
    <inertia ixx="0.00001" ixy="0" ixz="0" iyy="0.00001" iyz="0" izz="0.00001"/>
  </inertial>
</link>

<joint name="imu_joint" type="fixed">
  <parent link="base_link"/>
  <child link="imu_link"/>
  <origin xyz="0 0 0.05" rpy="0 0 0"/>
</joint>

Step 2: Add Gazebo IMU Plugin

<gazebo reference="imu_link">
  <sensor name="imu_sensor" type="imu">
    <always_on>true</always_on>
    <update_rate>100</update_rate>
    <visualize>true</visualize>

    <imu>
      <angular_velocity>
        <x>
          <noise type="gaussian">
            <mean>0.0</mean>
            <stddev>2e-4</stddev>
          </noise>
        </x>
        <y>
          <noise type="gaussian">
            <mean>0.0</mean>
            <stddev>2e-4</stddev>
          </noise>
        </y>
        <z>
          <noise type="gaussian">
            <mean>0.0</mean>
            <stddev>2e-4</stddev>
          </noise>
        </z>
      </angular_velocity>

      <linear_acceleration>
        <x>
          <noise type="gaussian">
            <mean>0.0</mean>
            <stddev>1.7e-2</stddev>
          </noise>
        </x>
        <y>
          <noise type="gaussian">
            <mean>0.0</mean>
            <stddev>1.7e-2</stddev>
          </noise>
        </y>
        <z>
          <noise type="gaussian">
            <mean>0.0</mean>
            <stddev>1.7e-2</stddev>
          </noise>
        </z>
      </linear_acceleration>
    </imu>

    <plugin name="gazebo_ros_imu_controller" filename="libgazebo_ros_imu_sensor.so">
      <ros>
        <namespace>/robot</namespace>
        <remapping>~/out:=imu</remapping>
      </ros>
      <frame_name>imu_link</frame_name>
    </plugin>
  </sensor>
</gazebo>

IMU Data

The IMU publishes sensor_msgs/Imu messages with:

• Orientation: Quaternion (x, y, z, w)
• Angular Velocity: rad/s (roll, pitch, yaw rates)
• Linear Acceleration: m/s² (X, Y, Z acceleration)

Test IMU

# View IMU data
ros2 topic echo /robot/imu

# Visualize orientation in RViz
# Add → By Topic → /robot/imu → Imu

Complete Example: Mobile Robot with Full Sensor Suite

Here's a complete URDF excerpt with LIDAR, camera, and IMU:

<?xml version="1.0"?>
<robot name="mobile_robot_sensors" xmlns:xacro="http://www.ros.org/wiki/xacro">

  <!-- Base Link -->
  <link name="base_link">
    <visual>
      <geometry>
        <box size="0.4 0.3 0.1"/>
      </geometry>
    </visual>
    <collision>
      <geometry>
        <box size="0.4 0.3 0.1"/>
      </geometry>
    </collision>
    <inertial>
      <mass value="5.0"/>
      <inertia ixx="0.1" ixy="0" ixz="0" iyy="0.1" iyz="0" izz="0.1"/>
    </inertial>
  </link>

  <!-- LIDAR -->
  <link name="lidar_link">
    <visual>
      <geometry>
        <cylinder radius="0.05" length="0.07"/>
      </geometry>
    </visual>
    <inertial>
      <mass value="0.1"/>
      <inertia ixx="0.0001" ixy="0" ixz="0" iyy="0.0001" iyz="0" izz="0.0001"/>
    </inertial>
  </link>

  <joint name="lidar_joint" type="fixed">
    <parent link="base_link"/>
    <child link="lidar_link"/>
    <origin xyz="0.15 0 0.15" rpy="0 0 0"/>
  </joint>

  <gazebo reference="lidar_link">
    <sensor name="lidar" type="ray">
      <update_rate>10</update_rate>
      <ray>
        <scan>
          <horizontal>
            <samples>360</samples>
            <min_angle>-3.14159</min_angle>
            <max_angle>3.14159</max_angle>
          </horizontal>
        </scan>
        <range>
          <min>0.1</min>
          <max>10.0</max>
        </range>
      </ray>
      <plugin filename="libgazebo_ros_ray_sensor.so" name="lidar_plugin">
        <ros>
          <remapping>~/out:=scan</remapping>
        </ros>
        <output_type>sensor_msgs/LaserScan</output_type>
      </plugin>
    </sensor>
  </gazebo>

  <!-- Camera -->
  <link name="camera_link">
    <visual>
      <geometry>
        <box size="0.05 0.05 0.05"/>
      </geometry>
    </visual>
    <inertial>
      <mass value="0.05"/>
      <inertia ixx="0.0001" ixy="0" ixz="0" iyy="0.0001" iyz="0" izz="0.0001"/>
    </inertial>
  </link>

  <joint name="camera_joint" type="fixed">
    <parent link="base_link"/>
    <child link="camera_link"/>
    <origin xyz="0.2 0 0.1" rpy="0 0 0"/>
  </joint>

  <gazebo reference="camera_link">
    <sensor name="camera" type="camera">
      <update_rate>30</update_rate>
      <camera>
        <horizontal_fov>1.3962634</horizontal_fov>
        <image>
          <width>640</width>
          <height>480</height>
        </image>
        <clip>
          <near>0.02</near>
          <far>300</far>
        </clip>
      </camera>
      <plugin filename="libgazebo_ros_camera.so" name="camera_plugin">
        <ros>
          <remapping>~/image_raw:=camera/image_raw</remapping>
        </ros>
      </plugin>
    </sensor>
  </gazebo>

  <!-- IMU -->
  <link name="imu_link">
    <inertial>
      <mass value="0.01"/>
      <inertia ixx="0.00001" ixy="0" ixz="0" iyy="0.00001" iyz="0" izz="0.00001"/>
    </inertial>
  </link>

  <joint name="imu_joint" type="fixed">
    <parent link="base_link"/>
    <child link="imu_link"/>
    <origin xyz="0 0 0.05" rpy="0 0 0"/>
  </joint>

  <gazebo reference="imu_link">
    <sensor name="imu" type="imu">
      <always_on>true</always_on>
      <update_rate>100</update_rate>
      <plugin filename="libgazebo_ros_imu_sensor.so" name="imu_plugin">
        <ros>
          <remapping>~/out:=imu</remapping>
        </ros>
      </plugin>
    </sensor>
  </gazebo>

</robot>

Sensor Placement Best Practices

1. LIDAR: Mount high and centered for best 360° coverage
2. Camera: Mount at "eye level" pointing forward, avoid occlusions
3. Depth Camera: Similar to camera, but consider range (0.3-3m typical)
4. IMU: Place near center of mass for accurate acceleration measurement
5. Multiple Sensors: Ensure no physical collisions between sensor links

Troubleshooting Sensor Issues

Sensor Not Publishing Data

Check:

ros2 topic list  # Is the topic present?
ros2 topic hz /scan  # Is it publishing?

Common fixes:

• Verify plugin filename (e.g., libgazebo_ros_ray_sensor.so)
• Check Gazebo console for error messages
• Ensure <always_on>true</always_on> or simulation is playing

Sensor Data Looks Wrong

LIDAR shows no obstacles: Check range parameters and ensure objects are within detection range

Camera shows black image: Check lighting in Gazebo world (add sun or lights)

IMU orientation wrong: Verify link coordinate frame and joint orientation

What You Learned

In this section, you:

• Added LIDAR sensors to robot URDF files
• Configured RGB and depth cameras with Gazebo plugins
• Integrated IMU sensors for orientation and acceleration
• Learned sensor parameters (FoV, resolution, update rate, noise)
• Created a complete mobile robot with multiple sensors
• Debugged common sensor simulation issues

Next Steps

Now that you can add sensors to robots, you're ready to:

• Fine-tune physics properties (Physics Properties)
• Simulate complete humanoid robots (Humanoid Simulation)
• Process sensor data for perception algorithms

Exercises

1. Add LIDAR: Take a simple mobile robot URDF and add a 360° LIDAR sensor
2. Camera Configuration: Experiment with different camera resolutions and FoV values
3. Multi-Sensor Robot: Create a robot with LIDAR, camera, and IMU, then visualize all three in RViz

Solutions are available in Section 9: Exercises.

Additional Resources

• Gazebo ROS Plugins
• sensor_msgs Documentation
• URDF Tutorials