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toaster_visualizer
To start the toaster_visualizer ros node, run the following command on terminal -
> rosrun toaster_visualizerTo visualize you need to launch rviz as well:
> rosrun rviz rvizTo understand the situation and visualize the internal processes, a visualization module is rendering the names and 3d models at the position of the entities and the areas with their names. This visualization simplifies the debugging process and allows a faster setup of the framework parameters. This module is designed to create a simple 3d representation of toaster's physical elements in RVIZ.
To use rviz with TOASTER, follow the configuration instructions at https://github.com/Greg8978/toaster/blob/master/toaster_visualizer/doc/toaster_visualizer_doc.pdf. The figure below, explains the implementation of this module.

It uses the position of the entities published by the data gathering component and the areas published by the area manager component Toaster_visualizer use informations taken form toaster_msgs published on specifics ros topics to create markerArray. toaster_msgs concerned: AreaList, ObjectList, HumanList topics concerned: /area_manager/areaList, /pdg/objList, /pdg/humanList
It publishes markerArray on topics like /toaster_visualizer/marker_area, marker_human, marker_robot, marker_motion and marker_objects viewable with RVIZ as shown in images below.
To add a marker, you need to add the mesh of your object / agent in the corresponding repository. You will also need to add the name corresponding to this element in the xml file:
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environment mesh: toaster_visualizer/mesh/toaster_environment
xml file: toaster_visualizer/src/list_object.xml
The name of the object for the environment should be "env". -
human mesh: toaster_visualizer/mesh/toaster_humans
xml file: toaster_visualizer/src/list_human.xml -
robot mesh: toaster_visualizer/mesh/toaster_robots
xml file: toaster_visualizer/src/list_robot.xml -
object mesh: toaster_visualizer/mesh/toaster_objects
xml file: toaster_visualizer/src/list_obj.xml
The human and robots available are presented in the picture below

In a future work, we would like to improve this visualization by adding the rendering of other facts, such as the one generated by the agent monitoring component about the attention.

