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Software package and ROS wrappers of the Aruco Augmented Reality marker detector library

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aruco_ros

Software package and ROS wrappers of the Aruco Augmented Reality marker detector library.

Features

* High-framerate tracking of AR markers * Generate AR markers with given size and optimized for minimal perceptive ambiguity (when there are more markers to track) * Enhanced precision tracking by using boards of markers * ROS wrappers

Applications

  • Object pose estimation
  • Visual servoing: track object and hand at the same time

ROS API

Messages

  • aruco_ros/Marker.msg

     Header header
     uint32 id
     geometry_msgs/PoseWithCovariance pose
     float64 confidence
    
  • aruco_ros/MarkerArray.msg

     Header header
     aruco_ros/Marker[] markers
    

Test it with REEM

  • Open a REEM in simulation with a marker floating in front of the robot. This will start the stereo cameras of the robot too. Since this is only a vision test, there is nothing else in this world apart from the robot and a marker floating in front of it. An extra light source had to be added to compensate for the default darkness.

    roslaunch reem_gazebo reem_gazebo.launch world:=floating_marker
    
  • Launch the image_proc node to get undistorted images from the cameras of the robot.

    ROS_NAMESPACE=/stereo/right rosrun image_proc image_proc image_raw:=image
    
  • Start the single node which will start tracking the specified marker and will publish its pose in the camera frame

    roslaunch aruco_ros single.launch markerId:=26 markerSize:=0.08 eye:="right"
    

    the frame in which the pose is refered to can be chosen with the 'ref_frame' argument. The next example forces the marker pose to be published with respect to the robot base_link frame:

    roslaunch aruco_ros single.launch markerId:=26 markerSize:=0.08 eye:="right" ref_frame:=/base_link
    
  • Visualize the result

    rosrun image_view image_view image:=/aruco_single/result
    

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Software package and ROS wrappers of the Aruco Augmented Reality marker detector library

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  • C++ 94.6%
  • Python 3.1%
  • CMake 1.4%
  • C 0.9%