• rviz
• knowrob
• knowrob_addons
• openni2
• Xsens MVN studio

• Xsens laptop
• Xsens suite
• kinect

• recharge batteries and replacement batteries

1. Start RVIZ

$ rosrun rviz rviz

1. For Calibration, define TF between `map` and `mocap`

$ rosrun comp_mocap tf_dynamic_transform.py

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

$ rosrun comp_mocap xsens_tf_broadcaster.py

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

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

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

1. Setup a kinect for capturing RGB images
2. - Attach kinect to tripod and to your computer via USB
3. - Start Publishing

$ roslaunch openni2_launch openni2.launch

1. Calibrate kinect camera
2. - Go to camera/driver
3. – Check depth_registration if you need depth info

$ rosrun rqt_reconfigure rqt_reconfigure

1. Spawn semantic map in rviz via knowrob
2. - Start knowrob_vis

$ roslaunch knowrob_vis knowrob_vis.launch

1. - 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).

1. - Leave the knowrob server

TODO

TODO

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