Accessing ARI sensors#

In this tutorials we’ll learn how to access to the different sensors in ARI.

Accessing the cameras#

Most of the sensor readings of ARI can be visualized in rviz. Though you can also use image_view or rqt_gui. Let’s have a look at both procedures.

  1. rviz visualization

In order to start the rviz GUI with a predefined configuration you need the ari_bringup package, which is accessible from the PAL docker image (see Developing with docker and ROS).

To install ari_bringup, execute

1apt install pal-gallium-ari-bringup-dev

Then start rviz:

1export ROS_MASTER_URI=http://ari-0c:11311
2rosrun rviz rviz -d `rospack find ari_bringup\`/config/ari.rviz

The image below shows how the torso front and back cameras are visualized in rviz.

  1. image_view visualization

Run image_view tool to visualize the desired camera as follows:

1export ROS_MASTER_URI=http://ari-0c:11311
2rosrun image_view image_view image:=/torso_back_camera/fisheye2/image_raw _image_transport:=compressed

When visualizing images from an external computer through WiFi, it is recommended to use the compressed topic to reduce bandwidth and latency.

  1. rqt_gui visualisation

You can also use rqt_gui, a tool that allows incorporate multiple plugins and thus, have a better understanding of the system. One such example is rqt_human_radar (see ros4hri_tools), a plugin for rqt_gui, where additional visualization tools for ROS4HRI can be combined.

To use rqt_gui, follow the next steps:

  1. Run rqt_gui:

    1export ROS_MASTER_URI=http://ari-0c:11311
    2rosrun rqt_gui rqt_gui
  2. In the top menu, select: Plugins ‣ Visualization ‣ Image View

  3. Select the topic of the camera you want to visualize. In the image below we are visualizing the /torso_back_camera/fisheye1/image_raw/*.


Accessing the microphones#

Please refer to ARI microphone array and audio recording to learn how to access the audio data.