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Routine Operations

This document describes routine operations that may be performed during the operation of the Galbot robot to ensure all functions work properly.

Map Engine - Mapping & Localization

The map engine is the core foundation of the navigation function. It is not an optional add-on, but a mandatory prerequisite for navigation. Before using the navigation function, you must complete mapping and ensure localization is running properly. Failure to complete mapping and localization correctly will result in the navigation function not working.

Mapping Process

Mapping is a prerequisite for navigation. You must complete the construction of an environment map before using the navigation function.

1. Prerequisites Check (Required)

Check whether the LiDAR service is running

Mapping requires the LiDAR service to be running. Enter the following command on the HPU terminal to check the LiDAR process:

top

If the LiDAR has been automatically started, you can see a process named service_livox_capture in the process list, as shown below:

LiDAR Service

If the LiDAR is not running, use the following command to start it (do not start it repeatedly):

/data/galbot/bin/service_livox_capture

Ensure the map path has write permissions

The default map path is stored in the /var/maps/ directory. If the path does not exist or does not have write permissions, create the path and grant write permissions:

sudo mkdir -p /var/maps/
sudo chmod 777 -R /var/maps/

2. Start Mapping (Required)

Start the mapping program

  1. Press the robot's emergency stop button and push the robot to the mapping start point (mapping can begin from any location)
  2. Execute the following command to start mapping:
/data/galbot/bin/mapping_server

During normal mapping, the following information will be displayed: - Keyframe count (keyframe num) - Pose delay (time delay) - Current robot pose (x y z qx qy qz qw)

The keyframe count increases as the robot moves and remains unchanged when the robot is stationary, as shown below:

Mapping Process

  1. Push the robot around the environment once to build a complete map. Avoid excessive acceleration and angular velocity while pushing (approximately walking speed is sufficient)

3. Save the Map (Required)

Save the constructed map

Simply stopping the mapping program will not automatically save the map. If you need to save the map, please perform the save operation before closing the mapping program.

Run the map saving tool:

/data/galbot/bin/engine_tools

After launching the tool, enter 1 and press Enter to select the save map function. The default save path is /var/maps/room1102, as shown below:

Save Map

4. Edit Map (Optional)

This step is used to optimize map quality, improving navigation accuracy and safety.

Impact if skipped

  • Removing map noise: Airborne noise points in the map may cause the navigation system to misidentify obstacles, affecting path planning accuracy
  • Drawing geofences: Without geofence restrictions, the robot may enter unexpected or dangerous areas
4.1 Remove Map Noise (Optional)

You need to check for noise points within the robot's operating area (from ground level up to 2.5 meters in height). Ground points do not affect navigation; the main focus is on checking and removing airborne floating noise points.

Preparation: Download CloudCompare software

Download link: https://www.cloudcompare.org/release/index.html

As shown below:

Download Software

Steps:

  1. Open CloudCompare and drag the point cloud map global_cloud.pcd into the workspace

pcd

  1. Follow the numbered green arrows in the image below:
  2. Step 1: Check the file
  3. Step 2: Select the front view
  4. Step 3: Select the crop tool (scissors icon)
  5. Step 4: Box-select the target area (between floor and ceiling in the robot's operating area)
  6. Step 5: Keep the points inside the selection
  7. Step 6: Confirm the operation (checkmark icon)

The point cloud is now split into two parts: global_cloud.segmented inside the selection and global_cloud.remaining outside:

opensource

  1. Continue with the following steps:
  2. Step 7: Uncheck global_cloud.remaining
  3. Step 8: Check global_cloud.segmented
  4. Step 9: Select the top view
  5. Step 10: Select the crop tool (scissors icon)
  6. Step 11: Box-select the robot's operating area (do not select real obstacles such as stacks or tables)
  7. Step 12: Click the icon outside the box
  8. Step 13: Confirm the operation

opensource2

  1. Delete noise and merge:
  2. Select global_cloud.segmented.remaining (noise portion), right-click and delete
  3. Hold Ctrl and multi-select global_cloud.remaining and global_cloud.segmented.remaining

opensource3

  1. Save the cleaned map:
  2. Select Edit → Merge to merge the two point clouds
  3. Select File → Save to save the point cloud
  4. Name it global_cloud_cleand
  5. Move the cleaned map global_cloud_cleand.pcd to the map folder /var/maps/room1102/

opensource4

4.2 Edit OSM File (Optional)

Draw geofences to restrict the robot's operating range, preventing it from entering dangerous or unintended areas.

Description

  • Drawing geofences: Set virtual boundaries on the map to prohibit the robot from crossing fences into specific areas (such as stairs, dangerous areas, non-work areas, etc.)
  • Impact if skipped: The robot can freely move to any position on the map, potentially entering dangerous or unintended work areas, posing safety risks

After mapping is complete (assuming the map is saved at /var/maps/room1102/), use the engine_tools tool to convert the point cloud map to an OSM file:

  1. Run engine_tools, enter 3 to select the point cloud to OSM file conversion function
  2. Press Enter to use the default map. In this example, the map is stored at /var/maps/room1102/, so enter the full path /var/maps/room1102/global_cloud.pcd and press Enter to convert:

osm1

  1. The converted file is highlighted in green below. Open the OSM file with JOSM, as shown below:

osm2

Install JOSM (if not installed):

sudo apt install josm

After installation, enter josm in the terminal to open the software.

Steps to draw geofences:

  1. Click File in the top-left corner, choose Open, and locate /var/maps/room1102/map_topo.osm
  2. Select the tool indicated by white arrow 1, then left-click to draw the shape (thin red line), as shown by white arrow 2
  3. After drawing is complete (closed shapes finish automatically; otherwise press Esc), click the icon above white arrow 1 and select the line you just drew. The selected line turns red. Hold Ctrl to select multiple lines. Then click white arrow 3:

osm3

  1. In the pop-up, choose the Fence tab, set the type to barbed_wire as indicated by white arrow 4, click Apply Preset, then right-click white arrow 5 and choose Save:

osm4

5. Map Update (Optional)

When the environment changes (e.g., new furniture added, obstacles moved, etc.), you can optimize the map using the map update function.

Impact if skipped

If the environment changes and the map is not updated, the robot will continue to navigate using the old map, which may lead to: - Decreased localization accuracy - Inaccurate path planning - The robot may misidentify obstacle positions

To save computing resources, the map update feature is disabled by default. You can manually enable the update switch and save the updated map:

Step 1: When localization is stable (current score > 0.9), enable the map update switch

vim /data/galbot/config/mes/manager.config

Change manager_update_map=0 to manager_update_map=1

Step 2: Restart localization in place. Once the score returns to normal (current score > 0.9), run engine_tools and choose Start Map Update

Step 3: Push the robot around the environment for one full loop, then run engine_tools and choose Stop Map Update

Step 4: The updated map will not overwrite the current localization map (/var/maps/cur). It will be saved to /var/maps/update_map

Step 5: After finishing the map update, change manager_update_map=1 back to 0, then replace the map if needed

Important Notes

  1. Both parameter changes and map replacement require restarting the localization service to take effect
  2. This example uses engine_tools. If you don't have engine_tools, use /data/galbot/bin/test_start_update_map and /data/galbot/bin/test_stop_update_map instead

Localization Process

Localization is a prerequisite for navigation. Before starting navigation, you must ensure the localization service is running properly and the localization status is good.

1. Prepare the Map (Required)

The localization program requires the LiDAR to be running (it does not depend on the mapping program, so you can close the mapping program after it finishes).

Localization uses the map path /var/maps/cur. Rename the target map to cur (for example, rename the newly created map room1102 to cur), as shown below:

cur

2. Start Localization (Required)

Start the localization service:

/data/galbot/bin/localization_server

3. Check Localization Status (Required)

Check localization status:

tail -f /userdata/log/localization_server/localization_server.INFO

state

If the score is below 0.75 or no score/pose is published, push the robot to the mapping start pose and send an initial pose once (use engine_tools, enter 2, and press Enter), as shown below:

state2

4. Verify Localization Ready (Required)

Before starting navigation, please confirm the following checklist items:

  • LiDAR service is running
  • Localization service has been started
  • Localization score is greater than 0.75
  • Current pose is being published normally

Ready to Go

After completing all the required steps above, you can start using the robot navigation function. For details, please refer to Tutorials - Example 3. Robot Navigation.