World canvas server

A component of the world canvas framework, a ROS stack for storing and accessing semantic information about the world, with an initial emphasis on needs and use cases for mobile robots.

World canvas server is a storage manager for semantic maps. Initial version replicates map_store behavior for semantic maps.

Give it a fast try

Installing

Use world_canvas.rosinstall to create a world_canvas workspace. Don't forget to install dependencies:

rosdep install --from-paths -i src

Running

First of all, launch the annotations server (the Python version)

roslaunch world_canvas_server py_annotations_server.launch --screen

Then you need to populate the database with some annotations (we still don't have an editor :( Use the save_xxxx.py scripts and the test/annotations/xxx_list.yaml data files from world_canvas_server package, e.g.

> rosrun world_canvas_server save_markers.py _world_id:='70a98ad3-78be-45eb-85f7-d2f14e81d95a' _filename:=`rospack find world_canvas_server`/test/annotations/ar_list.yaml
> rosrun world_canvas_server save_walls.py _world_id:='70a98ad3-78be-45eb-85f7-d2f14e81d95a' _filename:=`rospack find world_canvas_server`/test/annotations/wall_list.yaml

These scripts will request the server to save in database both the annotations and the associated data the YAML files contain.

And now you are ready to look for annotations. Until we have an operating client library, use the get_any.py script from world_canvas_server package, e.g.

> rosrun world_canvas_server get_any.py  _world_id:='70a98ad3-78be-45eb-85f7-d2f14e81d95a' _ids:=[] _types:=['ar_track_alvar/AlvarMarker'] _keywords:=[] _relationships=[] _topic_type:=ar_track_alvar/AlvarMarker _topic_name:=ar_markers _pub_as_list:=False
> rosrun world_canvas_server get_any.py  _world_id:='70a98ad3-78be-45eb-85f7-d2f14e81d95a' _ids:=[] _types:=['yocs_msgs/Wall'] _keywords:=[] _relationships=[] _topic_type:=yocs_msgs/WallList _topic_name:=wall_pose_list _pub_as_list:=True

The first 5 parameters provide search criteria:

world_id Retrieved annotations associated to this world. Mandatory
ids Retrieved annotation uuid is within this list
types Retrieved annotation type is within this list
keywords Retrieved annotation has AT LEAST one of these keywords
relationships Still not implemented on server, so just ignored

And the other 3 define how the server must publish the retrieved annotations

topic_name Where server must publish annotations data
topic_type The message type to publish annotations data. Mandatory if pub_as_list is true; ignored otherwise
pub_as_list If true, annotations will be packed in a list before publishing, so topic_type must be an array of the requested annotations

The get_any script calls 3 services in the annotations server:

get annotations to retrieve the annotations that satisfy the filter criteria
get annotations data to retrieve the data of those annotations
pub annotations data to make the server publish such data

You can verify that all went right by echoing topics

topic_name Published by the server with the loaded annotations data
topic_name + '_client' Published by the get_Any script with the retrieved annotations data

Or in RViz showing topic

topic_name + '_markers' Published by the get_Any script with visualization markers

Import/export database

The save_xxxx.py scripts are a temporal workaround to play with world canvas. The canonical ways to populate the database are a graphic tool still do be implemented and a import from YAML file service. To try the later method, and the reverse operation of exporting to file, you can run the import.py/export.py scripts:

rosrun world_canvas_server import.py _filename:=<world canvas workspace>/src/world_canvas/world_canvas_server/test/annotations/full_db.yaml
rosrun world_canvas_server export.py _filename:=<world canvas workspace>/src/world_canvas/world_canvas_server/test/annotations/export_db.yaml

Real scenario testing

Now we can show a more practical use: Turtlebot simulated on Stage using virtual sensor and getting the 2D map from WC server. You must first update your workspace using the modified rosinstall file. It adds the experimental branch of the turtlebot_simulator repo. Then, populate the WC database, and ready to go!

roslaunch world_canvas_server py_annotations_server.launch --screen
roslaunch turtlebot_stage populate_world.launch --screen
roslaunch turtlebot_stage world_canvas_demo.launch --screen

stonier/world_canvas

World canvas server

Give it a fast try