**NOTE: Site under construction**

====== Required Software ======
  * rviz
  * knowrob
  * knowrob_addons
  * openni2
  * Xsens MVN studio

====== Required Hardware ======
  * Xsens laptop
  * Xsens suite
  * kinect

====== Preparation ======
  * **recharge** batteries and replacement batteries
  * make sure to set up streaming for only one client

====== Running the software ======
  * Start RVIZ

	$ rosrun rviz rviz

  * For Calibration, define TF between `map` and `mocap`

	$ rosrun comp_mocap tf_dynamic_transform.py

  * Receive mocap data on port 9763
  * Modify the IP in the script to reflect the IP of your computer

	$ rosrun comp_mocap xsens_tf_broadcaster.py

  * Publish marker messages for human skelleton with TF root set to `mocap`

	$ rosrun comp_mocap mocap_marker.py --skeleton xsens --root-frame mocap

  * Start Xsens MVN studio on the Xsens laptop
  - Make sure to attach the USB stick with the license
  - Go to Options/Preferences/Network streamer
  - Add your computers IP to the destination addresses

  * Setup a kinect for capturing RGB images
  - Attach kinect to tripod and to your computer via USB
  - Start Publishing

	$ roslaunch openni2_launch openni2.launch

  * Calibrate kinect camera
  -  Go to camera/driver
  - Check depth_registration if you need depth info

	$ rosrun rqt_reconfigure rqt_reconfigure

  * Spawn semantic map in rviz via knowrob
  - Start knowrob_vis

	$ roslaunch knowrob_vis knowrob_vis.launch

  - in firefox, go to http://127.0.0.1:1111/ and spawn the map

	$ owl_parse('package://iai_semantic_maps/owl/room.owl').

	$ register_ros_package(knowrob_objects).

	$ owl_individual_of(A, knowrob:'SemanticEnvironmentMap'), !, add_object_with_children(A).

  - Leave the knowrob server

====== Dressing the suite ======
TODO

====== Calibration ======
TODO

====== Recording ======


rosbag record --duration=3 --output-name=$1 /camera/rgb/camera_info /camera/rgb/image_raw /camera/depth/camera_info /camera/depth/image /camera/depth_registered/image_raw /tf