scitos_3d_mapping

Tools for building 3D maps and using these maps for navigation and visualization.

Start the system

Start all the nodes in this repository using:

roslaunch semantic_map_launcher semantic_map.launch

Data acquisition

To collect sweeps, use the action server from: cloud_merge do_sweep.py

To start the action server manually (already launched with roslaunch semantic_map_launcher semantic_map.launch):

rosrun cloud_merge do_sweep.py

Use:

rosrun actionlib axclient.py /do_sweep

This action server takes as input a string, with the following values defined: "complete", "medium", "short", "shortest". Internally the action server from scitos_ptu called ptu_action_server_metric_map.py is used, so make sure that is running.

The behavior is the following:

• If sweep type is complete, the sweep is started with parameters -160 20 160 -30 30 30 -> 51 positions
• If sweep type is medium, the sweep is started with parameters -160 20 160 -30 30 -30 -> 17 positions
• If sweep type is short, the sweep is started with parameters -160 40 160 -30 30 -30 -> 9 positions
• If sweep type is shortest, the sweep is started with parameters -160 60 140 -30 30 -30 -> 6 positions (there might be blank areas with this sweep type, depending on the environment).

Calibrate sweep poses

Once a number of sweeps of type "complete" have been collected, you can run the calibration routine which will compute the registration transformations for the 51 poses. Afterwards, you can execute sweeps of any type (from the types defined above) and the correct transformations will be loaded so that the sweeps are registered.

To start the action server manually (already launched with roslaunch semantic_map_launcher semantic_map.launch):

rosrun calibrate_sweeps calibrate_sweep_as

Use:

rosrun actionlib axclient.py /calibrate_sweeps

(Here you have to specify the minimum and maximum number of sweeps to use for the optimization. To get good registration results you should have collected > 5 sweeps. Note that only sweeps of type "complete" are used here, all others are ignored).

Once the calibration has been executed, the parameters are saved in ~/.ros/semanticMap/ from where they are loaded whenever needed. All sweeps recorded up to this point are automatically corrected using the registered sweeps.

Meta-Rooms

The Meta-Rooms are created by the semantic_map semantic_map_node. To start, run:

roslaunch semantic_map semantic_map.launch

For more information check out the semantic_map package.

The dynamic clusters are published on the /local_metric_map/dynamic_clusters topic and the Meta-Rooms are published on the /local_metric_map/metaroom topic.

Reinitialize the Meta-Rooms

After the calibration you can re-initialize the metarooms (in general a good idea, as the registration between the sweeps should be better now that the poses have been calibrated).

rosservice call /local_metric_map/ClearMetaroomService "waypoint_id: - 'WayPointXYZ' initialize: true"

Set the argument initialize to true and provide all the waypoints for which you want to re-initialize the metarooms in the waypoint_id list.

Access invidual dynamic clusters

The package object_manager allows access to individual dynamic clusters, via a number of services. To start use:

rosrun object_manager object_manager_node

For more information check out the object_manager package.

semantic_map_publisher

The package semantic_map_publisher provides a number of services for accessing previously collected data which is stored on the disk. To start use:

rosrun semantic_map_publisher semantic_map_publisher

For more information check out the semantic_map_publisher package.

Accessing saved data

The package metaroom_xml_parser provides a number of utilities for reading previously saved sweep data. These include utilities for accessing:

• merged point clouds
• individual point clouds
• dynamic clusters
• labelled data
• sweep xml files.

Check out the metaroom_xml_parser package for more information.