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The package provides the following ROS nodes/nodelets:

Quick usage

First, launch the device and image processing via ccny_openni_launch.

roslaunch ccny_openni_launch openni.launch publish_cloud:=true

Next, launch visual_odometry.launch for visual odometry, or vo+mapping.launch for visual odometry and mapping interfaces.

roslaunch ccny_rgbd vo+mapping.launch

Launch rviz, and load the 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.


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 github (requires github account) or by emailing the maintainers.

2024-07-13 13:14