src/turtlebot3_simulations/turtlebot3_gazebo/CMakeLists.txt

@@ -118,10 +118,10 @@ install(DIRECTORY launch config models rviz urdf worlds scripts gui
   DESTINATION share/${PROJECT_NAME}/
 )
 
-# Install Python scripts with correct permissions
+# Install Python scripts with correct permissions
-install(PROGRAMS scripts/scan_frame_fix.py scripts/camera_topic_remap.py
+install(PROGRAMS scripts/scan_frame_fix.py scripts/camera_topic_remap.py scripts/depth_to_pointcloud.py
-  DESTINATION lib/${PROJECT_NAME}
+  DESTINATION lib/${PROJECT_NAME}
-)
+)
 
 install(DIRECTORY include/
   DESTINATION include/

src/turtlebot3_simulations/turtlebot3_gazebo/config/turtlebot3_gz_bridge.yaml

@@ -35,12 +35,9 @@
   gz_type_name: gz.msgs.CameraInfo
   direction: GZ_TO_ROS
 
-- ros_topic_name: /intel_realsense_r200_pointcloud
+# === Depth image (L16 workaround for Humble) ===
-  ros_type_name: sensor_msgs/msg/PointCloud2
+# Gazebo depth camera with <format>L16</format> publishes on /depth_image topic
-  gz_topic_name: /world/default/model/burger/link/realsense_link/sensor/intel_realsense_r200_pointcloud/points
+# as gz.msgs.Image type (NOT /image). This bypasses unsupported gz.msgs.DepthImage.
-  gz_type_name: gz.msgs.PointCloudPacked
-  direction: GZ_TO_ROS
-
 - ros_topic_name: /intel_realsense_r200_depth/depth/image_raw
   ros_type_name: sensor_msgs/msg/Image
   gz_topic_name: /world/default/model/burger/link/realsense_link/sensor/intel_realsense_r200_depth/depth_image

src/turtlebot3_simulations/turtlebot3_gazebo/launch/depth_cloud.launch.py

@@ -0,0 +1,35 @@
+#!/usr/bin/env python3
+#
+# Launch depth image -> point cloud conversion for TurtleBot3 Gz Sim.
+# Subscribes to the bridged L16 depth image and camera_info, and publishes
+# a sensor_msgs/PointCloud2 that can be visualized in RViz.
+
+from launch import LaunchDescription
+from launch.actions import DeclareLaunchArgument
+from launch.substitutions import LaunchConfiguration
+from launch_ros.actions import Node
+
+
+def generate_launch_description():
+    use_sim_time = LaunchConfiguration('use_sim_time', default='true')
+
+    declare_use_sim_time = DeclareLaunchArgument(
+        'use_sim_time',
+        default_value='true',
+        description='Use simulation clock if true')
+
+    # Custom Python replacement for depth_image_proc/point_cloud_xyz.
+    # It converts the bridged L16 depth image + camera_info into a PointCloud2.
+    depth_to_cloud_node = Node(
+        package='turtlebot3_gazebo',
+        executable='depth_to_pointcloud.py',
+        name='depth_to_pointcloud',
+        parameters=[{'use_sim_time': use_sim_time}],
+        output='screen',
+    )
+
+    ld = LaunchDescription()
+    ld.add_action(declare_use_sim_time)
+    ld.add_action(depth_to_cloud_node)
+
+    return ld

src/turtlebot3_simulations/turtlebot3_gazebo/launch/turtlebot3_office.launch.py

@@ -19,20 +19,22 @@
 
 import os
 
-from ament_index_python.packages import get_package_share_directory
+from ament_index_python.packages import get_package_share_directory
-from launch import LaunchDescription
+from launch import LaunchDescription
-from launch.actions import IncludeLaunchDescription, SetEnvironmentVariable
+from launch.actions import DeclareLaunchArgument, IncludeLaunchDescription, SetEnvironmentVariable
-from launch.launch_description_sources import PythonLaunchDescriptionSource
+from launch.conditions import IfCondition
-from launch.substitutions import LaunchConfiguration
+from launch.launch_description_sources import PythonLaunchDescriptionSource
-from launch_ros.actions import Node
+from launch.substitutions import LaunchConfiguration, PythonExpression
+from launch_ros.actions import Node
 
 
 def generate_launch_description():
     launch_file_dir = os.path.join(get_package_share_directory('turtlebot3_gazebo'), 'launch')
 
-    use_sim_time = LaunchConfiguration('use_sim_time', default='true')
+    use_sim_time = LaunchConfiguration('use_sim_time', default='true')
-    x_pose = LaunchConfiguration('x_pose', default='0.0')
+    x_pose = LaunchConfiguration('x_pose', default='0.0')
-    y_pose = LaunchConfiguration('y_pose', default='0.0')
+    y_pose = LaunchConfiguration('y_pose', default='0.0')
+    use_depth_cloud = LaunchConfiguration('use_depth_cloud', default='true')
 
     pkg_share_dir = get_package_share_directory('turtlebot3_gazebo')
     world = os.path.join(pkg_share_dir, 'worlds', 'office_gz_dartsim.sdf')
@@ -83,18 +85,33 @@ def generate_launch_description():
         parameters=[{'use_sim_time': True}],
     )
 
-    ld = LaunchDescription()
+    depth_cloud_cmd = IncludeLaunchDescription(
-
+        PythonLaunchDescriptionSource(
-    # Set GZ_SIM_RESOURCE_PATH so gz sim can resolve model:// URIs
+            os.path.join(launch_file_dir, 'depth_cloud.launch.py')
-    ld.add_action(SetEnvironmentVariable(
+        ),
-        name='GZ_SIM_RESOURCE_PATH',
+        launch_arguments={'use_sim_time': use_sim_time}.items(),
-        value=office_models_path + os.pathsep + models_path
+        condition=IfCondition(PythonExpression(["'", use_depth_cloud, "' == 'true'"])),
+    )
+
+    ld = LaunchDescription()
+
+    declare_use_depth_cloud_cmd = DeclareLaunchArgument(
+        'use_depth_cloud',
+        default_value='true',
+        description='Launch depth image -> point cloud conversion node'
+    )
+
+    # Set GZ_SIM_RESOURCE_PATH so gz sim can resolve model:// URIs
+    ld.add_action(SetEnvironmentVariable(
+        name='GZ_SIM_RESOURCE_PATH',
+        value=office_models_path + os.pathsep + models_path
     ))
 
     # Add the commands to the launch description
 
-    ld.add_action(gz_sim_cmd)
+    ld.add_action(gz_sim_cmd)
-    ld.add_action(robot_state_publisher_cmd)
+    ld.add_action(robot_state_publisher_cmd)
-    ld.add_action(spawn_turtlebot_cmd)
+    ld.add_action(spawn_turtlebot_cmd)
-    ld.add_action(scan_frame_fix_cmd)
+    ld.add_action(scan_frame_fix_cmd)
-    return ld
+
+    return ld

src/turtlebot3_simulations/turtlebot3_gazebo/models/turtlebot3_burger/model_gz.sdf

@@ -341,11 +341,11 @@
       <!-- RGB camera sensor - migrated from libgazebo_ros_camera.so to gz-sim native
            Original plugin had: hack_baseline=0.07 (stereo baseline)
            Note: Not applicable in Gz Sim native sensor (same reason as depth camera above). -->
-      <sensor name="intel_realsense_r200_rgb" type="camera">
+      <sensor name="intel_realsense_r200_rgb" type="camera">
-        <gz_frame_id>camera_rgb_frame</gz_frame_id>
+        <gz_frame_id>camera_rgb_frame</gz_frame_id>
-        <always_on>true</always_on>
+        <always_on>true</always_on>
-        <visualize>true</visualize>
+        <visualize>true</visualize>
-        <update_rate>30</update_rate>
+        <update_rate>30</update_rate>
 	      <pose>0.076 0.0 0.093 0 0 0</pose>
         <camera name="realsense_rgb_camera">
           <horizontal_fov>1.02974</horizontal_fov>
@@ -364,30 +364,10 @@
             <type>gaussian</type>
             <mean>0.0</mean>
             <stddev>0.007</stddev>
-          </noise>
+          </noise>
-        </camera>
+        </camera>
-      </sensor>
+      </sensor>
-
+    </link>
-      <!-- Native RGBD sensor for point cloud output. -->
-      <sensor name="intel_realsense_r200_pointcloud" type="rgbd_camera">
-        <gz_frame_id>realsense_depth_frame</gz_frame_id>
-        <always_on>true</always_on>
-        <visualize>false</visualize>
-        <update_rate>30</update_rate>
-        <topic>intel_realsense_r200_pointcloud</topic>
-        <camera name="realsense_pointcloud_camera">
-          <horizontal_fov>1.02974</horizontal_fov>
-          <image>
-            <width>640</width>
-            <height>480</height>
-          </image>
-          <clip>
-            <near>0.02</near>
-            <far>10</far>
-          </clip>
-        </camera>
-      </sensor>
-    </link>
 
     <joint name="base_joint" type="fixed">
       <parent>base_footprint</parent>

src/turtlebot3_simulations/turtlebot3_gazebo/scripts/depth_to_pointcloud.py

@@ -0,0 +1,125 @@
+#!/usr/bin/env python3
+#
+# Convert a depth image (16UC1 mm or 32FC1 m) + CameraInfo into a sensor_msgs/PointCloud2.
+# This replaces depth_image_proc/point_cloud_xyz for environments where that package
+# is not available or its executable is missing.
+
+import numpy as np
+import rclpy
+from rclpy.node import Node
+from sensor_msgs.msg import CameraInfo, Image, PointCloud2, PointField
+from std_msgs.msg import Header
+
+
+class DepthToPointCloud(Node):
+    def __init__(self):
+        super().__init__('depth_to_pointcloud')
+
+        self.declare_parameter('depth_topic', '/intel_realsense_r200_depth/depth/image_raw')
+        self.declare_parameter('camera_info_topic', '/intel_realsense_r200_depth/camera_info')
+        self.declare_parameter('points_topic', '/intel_realsense_r200_depth/depth/color/points')
+        self.declare_parameter('max_depth_m', 10.0)
+
+        depth_topic = self.get_parameter('depth_topic').value
+        camera_info_topic = self.get_parameter('camera_info_topic').value
+        points_topic = self.get_parameter('points_topic').value
+        self.max_depth_m = float(self.get_parameter('max_depth_m').value)
+
+        self.camera_info = None
+
+        self.info_sub = self.create_subscription(
+            CameraInfo, camera_info_topic, self.info_callback, qos_profile=1)
+        self.depth_sub = self.create_subscription(
+            Image, depth_topic, self.depth_callback, qos_profile=1)
+        self.cloud_pub = self.create_publisher(PointCloud2, points_topic, qos_profile=1)
+
+        self.get_logger().info(
+            f'Waiting for camera info on {camera_info_topic}; '
+            f'publishing points on {points_topic}'
+        )
+
+    def info_callback(self, msg: CameraInfo):
+        self.camera_info = msg
+
+    def depth_callback(self, msg: Image):
+        if self.camera_info is None:
+            self.get_logger().warn(
+                'CameraInfo not received yet; skipping depth frame',
+                throttle_duration_sec=5)
+            return
+
+        # Decode depth image according to its encoding.
+        # Gz Sim may publish depth as either 16-bit unsigned mm (16UC1/mono16)
+        # or 32-bit float meters (32FC1), depending on sensor/bridge version.
+        if msg.encoding in ('16UC1', 'mono16'):
+            depth_raw = np.frombuffer(msg.data, dtype=np.uint16).reshape(msg.height, msg.width)
+            depth_m = depth_raw.astype(np.float32) * 0.001
+        elif msg.encoding == '32FC1':
+            depth_m = np.frombuffer(msg.data, dtype=np.float32).reshape(msg.height, msg.width)
+        else:
+            self.get_logger().error(
+                f'Unsupported depth encoding: {msg.encoding}; expected 16UC1/mono16 or 32FC1',
+                throttle_duration_sec=5)
+            return
+
+        # Intrinsics from CameraInfo
+        K = self.camera_info.k
+        fx, fy = float(K[0]), float(K[4])
+        cx, cy = float(K[2]), float(K[5])
+
+        # Pixel coordinates
+        u = np.arange(msg.width, dtype=np.float32)
+        v = np.arange(msg.height, dtype=np.float32)
+        u, v = np.meshgrid(u, v)
+
+        # Filter valid depth pixels
+        valid = (depth_m > 0.0) & (depth_m < self.max_depth_m)
+        u = u[valid]
+        v = v[valid]
+        z = depth_m[valid]
+
+        if z.size == 0:
+            return
+
+        # Back-project to 3D (in the camera optical frame)
+        x = (u - cx) * z / fx
+        y = (v - cy) * z / fy
+
+        points = np.stack((x, y, z), axis=-1).astype(np.float32)
+
+        header = Header()
+        header.stamp = msg.header.stamp
+        header.frame_id = self.camera_info.header.frame_id
+
+        cloud_msg = PointCloud2()
+        cloud_msg.header = header
+        cloud_msg.height = 1
+        cloud_msg.width = int(points.shape[0])
+        cloud_msg.fields = [
+            PointField(name='x', offset=0, datatype=PointField.FLOAT32, count=1),
+            PointField(name='y', offset=4, datatype=PointField.FLOAT32, count=1),
+            PointField(name='z', offset=8, datatype=PointField.FLOAT32, count=1),
+        ]
+        cloud_msg.is_bigendian = False
+        cloud_msg.point_step = 12
+        cloud_msg.row_step = cloud_msg.point_step * cloud_msg.width
+        cloud_msg.is_dense = True
+        cloud_msg.data = points.tobytes()
+
+        self.cloud_pub.publish(cloud_msg)
+
+
+def main(args=None):
+    rclpy.init(args=args)
+    node = DepthToPointCloud()
+    try:
+        rclpy.spin(node)
+    except KeyboardInterrupt:
+        pass
+    finally:
+        node.destroy_node()
+        rclpy.shutdown()
+
+
+if __name__ == '__main__':
+    main()