GridMap Mapping with LidarSLAM and EasyNav

This HowTo explains how to build a multi-layer GridMap from a LidarSLAM point cloud and save it to disk (YAML + one PGM per layer) so it can be loaded later by the Gridmap Maps Manager and the planner.

Setup

Before starting, ensure that:

1. You have completed the installation described in Build & Install.

2. You have a working workspace containing the following repositories:

   • EasyNavigation

   • easynav_plugins

   • easynav_gridmap_stack (for GridMap representation and planner)

   • easynav_lidarslam_ros2 (for SLAM)

   • easynav_playground_summit (for the Summit simulation world)

Warning

The easynav_gridmap_stack [repository](https://github.com/EasyNavigation/easynav_gridmap_stack.git) is not included in the default EasyNav build or in easynav_plugins. You must clone it manually into your workspace as shown above before building. It provides the GridMap representation, its Maps Manager, and the corresponding planner.

3. All packages build successfully and are sourced:

   cd ~/ros/ros2/easynav_ws
   colcon build --symlink-install
   source install/setup.bash
   

4. RViz2 is installed for visualization.

5. Simulation nodes use use_sim_time: true.

—

Overview

The workflow consists of:

1. Launching the Summit playground simulation.

2. Running LidarSLAM to build a 3D point cloud of the environment.

3. Converting the resulting map point cloud into a GridMap using the GridMap Builder.

4. Feeding the built GridMap to the Gridmap Maps Manager.

5. Saving the map to disk for later use.

—

1. Start the Simulator

Start the Summit world simulation in Gazebo with RViz configured automatically.

ros2 launch easynav_playground_summit playground_summit.launch.py

Keep the RViz window open to visualize topics such as the LIDAR scan and the map.

—

2. Launch LidarSLAM

Start the LidarSLAM pipeline (scan matcher + graph-based SLAM). If your package provides a consolidated launch file, you can start it directly:

ros2 launch lidarslam lidarslam.launch.py

You can close any extra RViz instance this launch may open; we will use the one started in step (1).

As the robot moves, LidarSLAM will publish a map point cloud:

• Topic: /map

• Type: sensor_msgs/msg/PointCloud2

• Frame: map

In RViz, add a PointCloud2 display for /map and increase the point size to improve visibility.

—

3. Build the Map with Teleoperation

Drive the robot around the environment to accumulate the map:

ros2 run teleop_twist_keyboard teleop_twist_keyboard

Continue until the environment is sufficiently covered.

—

4. Run the GridMap Builder (PointCloud → GridMap)

The GridMap Builder converts the accumulated /map point cloud into a multi-layer GridMap. The example parameters file listens to /map and downsamples the cloud before rasterization.

Run the builder:

ros2 run easynav_gridmap_maps_manager gridmap_maps_builder_main \
  --ros-args --params-file ~/ros/ros2/easynav_ws/src/easynav_outdoor_testcase/robots_params/maps_builder.params.yaml

Example configuration:

pointcloud_maps_builder_node:
  ros__parameters:
    use_sim_time: true
    sensors: [map]
    downsample_resolution: 0.1
    perception_default_frame: map
    map:
      topic: map
      type: sensor_msgs/msg/PointCloud2
      group: points

The builder publishes the resulting GridMap on:

• Topic: /maps_builder_gridmap/gridmap

• Type: grid_map_msgs/msg/GridMap

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5. Run the Gridmap Maps Manager

The Gridmap Maps Manager can ingest the GridMap published by the builder via a remap of its incoming_map input.

Option A (recommended): start the full EasyNav system with a minimal parameter file where all plugins are dummy except the Gridmap Maps Manager:

ros2 run easynav_system system_main \
  --ros-args --params-file ~/ros/ros2/easynav_ws/src/easynav_playground_summit/config/summit_building_params.yaml \
  -r /maps_manager_node/gridmap/incoming_map:=/maps_builder_gridmap/gridmap

Option B (standalone): if available, run a dedicated manager executable with the same remap. If your workspace does not include a standalone binary, use Option A.

Example parameter file (summit_building_params.yaml):

controller_node:
  ros__parameters:
    use_sim_time: true
    controller_types: [dummy]
    dummy:
      plugin: easynav_controller/DummyController

localizer_node:
  ros__parameters:
    use_sim_time: true
    localizer_types: [dummy]
    dummy:
      plugin: easynav_localizer/DummyLocalizer

maps_manager_node:
  ros__parameters:
    use_sim_time: true
    map_types: [gridmap]
    gridmap:
      freq: 10.0
      plugin: easynav_gridmap_maps_manager/GridmapMapsManager

planner_node:
  ros__parameters:
    use_sim_time: true
    planner_types: [dummy]
    dummy:
      plugin: easynav_planner/DummyPlanner

sensors_node:
  ros__parameters:
    use_sim_time: true
    forget_time: 0.5
    sensors: [laser1]
    perception_default_frame: odom
    laser1:
      topic: /scan_raw
      type: sensor_msgs/msg/LaserScan
      group: points

system_node:
  ros__parameters:
    use_sim_time: true
    position_tolerance: 0.1
    angle_tolerance: 0.05

This setup runs a lightweight EasyNav system in which the Gridmap Maps Manager receives the GridMap from the builder.

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6. Save the GridMap to Disk

Once the GridMap has been received, you can save it to disk by calling the Maps Manager service. This will create a .yaml file and one `.pgm` per layer (for example, _elevation.pgm, _traversability.pgm).

ros2 service call /maps_manager_node/gridmap/savemap std_srvs/srv/Trigger

You can later reload this map in the Gridmap Maps Manager by setting the same package and map_path_file parameters in your configuration.

Note

GridMap supports multi-layer data structures (elevation, traversability, etc.) and is ideal for 3D or semi-structured terrain. You can visualize individual layers in RViz using the GridMap plugin or by converting to an image topic.