The metapackage includes 3 nodes named dotnect_dgram_socket, kinect_tracking and sensor_processor. The first listens on a multicast socket and pushes the data depending on the sensor to a ROS-topic. The second one subscribes to an Image topic of type sensor_msgs::Image and tracks via Minimum Entry Search the closest point inside the depth matrix. The points coordinates including a Rviz marker are then published. The sensor_processor averages the output of the previous topics and pushs them to topic for Rviz again or parses with a user specific template to a text file.
Furthermore the node rviz markers and coordinate transforms are output to see where the tracked point goes.
Clone the package into your workspace directory catkin_ws/src . If the workspace is non existent, follow this link.
You can use any depth camera with this package as long as it provides an Image topic of type sensor_msgs::Image.
Launch it via roslaunch dotnect_launch dotnect.launch
Change the calibration data according to your calibration results, merge them into the yaml-file with your custom name depth<serial number>. Place it in the directory /home//.ros/camera_info. The parameters dont differ too much, so they could be reused for other Kinectv1.
Workspace is developed with * kinetic (1.12.2) * (earlier versions not tested)
The code style is consistent with the ROS style guide. With clang-format:
find . -name '*.h' -or -name '*.hpp' -or -name '*.cpp' | xargs clang-format -i -style=file $1
The scripts are a convenience thing to pull driver and ros-package for the kinectv1 and get you started right away. Run them inside their install folder via sudo ./3party.sh and sudo ./2party.sh. (Make sure to have the box ticked off for executing file as program)
For the kinectv2 (One) use this driver and that ros-package.
After implementing the IK-solver for a generalized URDF-model, all main controls will be brought into RViz with a major GUI to ease steering. Adjusting the parameters real-time results in new opportunities to optimize parameters and test algorithms.
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