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Using PCL and Laser as obstacle_layer (RTABmap obstacles_detection)

asked 2019-07-09 06:45:00 -0500

EdwardNur gravatar image

How can I use both Laser and PCL from obstacles_detection node to view the obstacles in the local costmap?

If i put the local_costmap like this:

 plugins:
   - {name: obstacle_layer, type: "costmap_2d::ObstacleLayer"}


  observation_sources: point_cloud_sensor

  # assuming receiving a cloud from rtabmap_ros/obstacles_detection node
  point_cloud_sensor: {
    sensor_frame: base_footprint,
    data_type: PointCloud2,
    topic: /planner_cloud,
    expected_update_rate: 0.5,
    marking: true,
    clearing: true,
    min_obstacle_height: -99999.0,
    max_obstacle_height: 99999.0}

I get the laser obstacles but not get the PCL obstacles. If I remove that plugin, I do not get the laser obstacles but get the PCL obstacles.

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answered 2019-07-09 09:18:12 -0500

matlabbe gravatar image

For the main question, yes you can feed both sensors to update the local costmap. See https://github.com/introlab/rtabmap_r... for such example:

global_frame: odom
robot_base_frame: base_footprint
update_frequency: 2.0
publish_frequency: 2.0
rolling_window: true
width: 4.0
height: 4.0
resolution: 0.025
origin_x: -2.0
origin_y: -2.0

plugins:
  - {name: obstacle_layer,      type: "costmap_2d::ObstacleLayer"}
  - {name: inflation_layer,  type: "costmap_2d::InflationLayer"}

obstacle_layer:
  obstacle_range: 2.5
  raytrace_range: 3.0
  max_obstacle_height: 0.4
  track_unknown_space: true

  observation_sources: laser_scan_sensor point_cloud_sensorA point_cloud_sensorB

  laser_scan_sensor: {
    data_type: LaserScan, 
    topic: /base_scan, 
    expected_update_rate: 0.2, 
    marking: true, 
    clearing: true
  }

  point_cloud_sensorA: {
    sensor_frame: base_footprint,
    data_type: PointCloud2, 
    topic: /obstacles_cloud, 
    expected_update_rate: 0.5, 
    marking: true, 
    clearing: true,
    min_obstacle_height: 0.04
  }

  point_cloud_sensorB: {
    sensor_frame: base_footprint,
    data_type: PointCloud2,
    topic: /ground_cloud,
    expected_update_rate: 0.5,
    marking: false,
    clearing: true,
    min_obstacle_height: -1.0 # make usre the ground is not filtered
  }

The ground and obstacle coulds are generated like in this file:

  <group ns="camera">
    <!-- camera_nodelet_manager started by openni or freenect -->
    <node pkg="nodelet" type="nodelet" name="data_throttle" args="load rtabmap_ros/data_throttle camera_nodelet_manager">
      <param name="rate" type="double" value="5"/>
      <param name="decimation" type="int" value="2"/>

      <remap from="rgb/image_in"       to="rgb/image_rect_color"/>
      <remap from="depth/image_in"     to="depth_registered/image_raw"/>
      <remap from="rgb/camera_info_in" to="rgb/camera_info"/>

      <remap from="rgb/image_out"       to="data_resized_image"/>
      <remap from="depth/image_out"     to="data_resized_image_depth"/>
      <remap from="rgb/camera_info_out" to="data_resized_camera_info"/>
    </node>

    <!-- for the planner -->
    <node pkg="nodelet" type="nodelet" name="points_xyz_planner" args="load rtabmap_ros/point_cloud_xyz camera_nodelet_manager">
      <remap from="depth/image"            to="data_resized_image_depth"/>
      <remap from="depth/camera_info"      to="data_resized_camera_info"/>
      <remap from="cloud"                  to="cloudXYZ" />
      <param name="decimation" type="int" value="1"/>                     <!-- already decimated above -->
      <param name="max_depth"  type="double" value="3.0"/>
      <param name="voxel_size" type="double" value="0.02"/>
    </node>

    <node pkg="nodelet" type="nodelet" name="obstacles_detection" args="load rtabmap_ros/obstacles_detection camera_nodelet_manager">
      <remap from="cloud" to="cloudXYZ"/>
      <remap from="obstacles" to="/obstacles_cloud"/>
      <remap from="ground"    to="/ground_cloud"/>

      <param name="frame_id"             type="string" value="base_footprint"/>     
      <param name="map_frame_id"         type="string" value="map"/>
      <param name="wait_for_transform"   type="bool" value="true"/>
      <param name="min_cluster_size"     type="int" value="20"/>
      <param name="max_obstacles_height" type="double" value="0.4"/>
    </node>  
  </group>

cheers,
Mathieu

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Asked: 2019-07-09 06:45:00 -0500

Seen: 16 times

Last updated: Jul 09