Routine Operations

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

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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.

When localization and navigation services are enabled (the robot working mode may start navigation services by default), mapping must be completed first. A new robot must be mapped before first use; otherwise, localization cannot start correctly and the robot may enter abnormal mode.

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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_lidar_capture in the process list, as shown below:

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

/data/galbot/bin/service_lidar_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. If the localization service becomes abnormal later, send relocalization at the initial mapping point)
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:

3. 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:

After saving the map, the map directory must contain global_cloud_cleaned.pcd for subsequent localization.

• If point cloud post-processing has been completed, make sure the cleaned map file is named global_cloud_cleaned.pcd
• If map noise removal is not performed for now, run the following command in the map directory:

cp global_cloud.pcd global_cloud_cleaned.pcd

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)

This step is recommended (if navigation is required, this step must be performed). The map may usually contain some noise points, and removing them can improve the navigation success rate. In particular, rooms with mirrors, frosted glass, or similar materials are more likely to produce noise points in the point cloud map, so CloudCompare post-processing is recommended.

Preparation: Download CloudCompare software

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

As shown below:

If the official website version cannot open PCD files, use the following commands:

sudo apt update
sudo apt install -y flatpak gnome-software-plugin-flatpak
flatpak remote-add --if-not-exists flathub https://mirrors.ustc.edu.cn/flathub
flatpak install flathub org.cloudcompare.CloudCompare -y

flatpak run org.cloudcompare.CloudCompare

Steps:

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

2. Follow the numbered green arrows in the image below:
   • Step 1: Select the front view
   • Step 2: Select the point cloud
   • Step 3: Select the scissors icon
   • Step 4: Left-click to select points and right-click to finish selecting points. Select the robot operating space as shown by the green box
   • Step 5: Keep the points inside the selection
   • 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:

3. Continue with the following steps:
   • Step 7: Remove noise points. Noise points refer to points in the robot operating space that affect robot passage. Unselect xxx.remaining and keep xxx.segmented
   • Step 8: Select the top view
   • Step 9: Select the scissors icon
   • Step 10: Left-click to select points and right-click to finish. Select the noise points you want to remove
   • Step 11: Keep the points outside the selection
   • Step 12: Click the checkmark to complete the segmentation

4. Delete noise and merge:
   • Step 13: Select xxx.segmented.remaining, then right-click and choose Delete
   • Step 14: Select the point clouds indicated by arrows 14 and 15 (hold Ctrl to multi-select)
   • Step 16: Select Edit → Merge to merge the point clouds

5. Save the cleaned map:
   • Step 17: Select File → Save
   • Step 18: In the dialog, choose the format Point Cloud Library cloud
   • Step 19: Save the new PCD point cloud map as global_cloud_cleaned.pcd, and upload it to /var/maps/room1102/ on the robot

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:

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

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:

4. 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:

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

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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:

2. Start Localization

This step is the same as the LiDAR service. After the robot is powered on, the localization service normally starts automatically. Use top to check whether the process has started. If it has not started properly, manually 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

If the score is below 0.8 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:

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 0.8
• 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.