## repository: https://github.com/ccny-ros-pkg/ccny_rgbd_tools.git
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== Details ==

<<Youtube(YE9eKgek5pI)>>

== ROS API ==

{{attachment:rgbd_system.png}}

The package provides the following ROS nodes/nodelets:

 * [[ccny_rgbd/rgbd_image_proc | rgbd_image_proc]]: processes raw OpenNI camera data by performing image rescaling, rectification, registration, and depth unwarping. Also see [[ccny_openni_launch]] 
 * [[ccny_rgbd/feature_viewer | feature_viewer]]: auxliary node which lets users test out different feature detectors, and visualize feature locations and covariances in [[rviz]]
 * [[ccny_rgbd/visual_odometry | visual_odometry ]]: visual odometry based on sparse 3D features.
 * [[ccny_rgbd/keyframe_mapper | keyframe_mapper ]]: a map server which stores RGBD keyframes, performs (offline) graph-based SLAM, and handles map generation and disk output.

== Quick usage ==

First, launch the device and image processing via [[ccny_openni_launch]]. 

{{{
roslaunch ccny_openni_launch openni.launch publish_cloud:=true
}}}

Next, launch [[https://github.com/ccny-ros-pkg/ccny_rgbd_tools/blob/master/ccny_rgbd/launch/visual_odometry.launch | visual_odometry.launch]] for visual odometry, or
[[https://github.com/ccny-ros-pkg/ccny_rgbd_tools/blob/master/ccny_rgbd/launch/vo+mapping.launch | vo+mapping.launch]] for visual odometry and mapping interfaces.

{{{
roslaunch ccny_rgbd vo+mapping.launch
}}}

Launch [[rviz]], and load the [[https://github.com/ccny-ros-pkg/ccny_rgbd_tools/blob/master/ccny_rgbd/launch/vo+mapping.vcg | vo+mapping.vcg]] configuration file.

If you are using the mapping interface, you can call the following services to perform graph-based SLAM (offline):

{{{
rosservice call /generate_graph 
rosservice call /solve_graph
}}}

You can publish the resulting keyframe to rviz:

{{{
rosservice call /publish_keyframes  ".*"
}}}

Or save the entire map as a pcd:

{{{
rosservice call /save_pcd_map /home/your_user_name/my_map.pcd
}}}

For more options, consult the individual app pages.

== References ==

Ivan Dryanovski, Roberto G. Valenti, Jizhong Xiao. ''Fast Visual Odometry and Mapping from RGB-D Data''. 2013 International Conference on Robotics and Automation (ICRA2013).

== Bug Reports & Feature Requests ==

We appreciate the time and effort spent submitting bug reports and feature requests.

Please submit your tickets through [[https://github.com/ccny-ros-pkg/ccny_rgbd_tools/issues/|github]] (requires github account) or by emailing the maintainers.