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Vision algorithms (tracking, visual-servoing,…) for the Agimus project

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This ROS node will find the AprilTag 0 in the video stream and publish its pose in the TF tree

Dependencies:

  • ROS Kinetic
  • OpenCV3
  • Visp3 and visp_bridge (sudo apt-get install ros-kinetic-vision-visp)
  • libxml2

Installation: mkdir build && cd build && cmake .. && make install

Usage: rosrun agimus-vision tracker_box

There are some ros parameters used to configure the node:

  • /imageTopic: Topic where the camera publish the RGB image (default: /camera/rgb/image_rect_color).
  • /cameraInfoTopic: Topic where the camera publish the information about the camera settings (default: /camera/rgb/camera_info).
  • /positionNode: Name of the TF node corresponding to the box position (default: box).
  • /positionParentNode: Name of its parent node in the TF tree (default: rgbd_rbg_optical_frame).wn

Generate DAE from AprilTag png files

Moved to gerard bauzil package.

Debugging images on the robot

  • We emulate a virtual display on the robot. On the robot, run the command in a terminal and leave it open.
Xvfb :1 -screen 0 800x600x16
  • We start the tracker node within this display, by setting the environment variable DISPLAY to :1 for the tracker node executable.
export DISPLAY=:1
  • Once the node is launched, you can ask for the debug to be published. There are two parameters for this: ~debugDisplay and ~publishDebugDisplay. Something similar to rosparam set /vision/tracker/debugDisplay true followed by rosparam set /vision/tracker/publishDebugDisplay true should enable the publication.
rosparam set /vision/tracker/publishDebugDisplay true
rosparam set /vision/tracker/debugDisplay true
  • On another terminal, possibly on another computer, run:
rosrun image_view image_view image:=/vision/tracker/debug _image_transport:=compressed

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Vision algorithms (tracking, visual-servoing,…) for the Agimus project

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