ccny_rgbd_tools
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README.md

CCNY RGB-D tools

Ivan Dryanovski
ivan.dryanovski@gmail.com

Copyright (C) 2013, City University of New York
CCNY Robotics Lab
http://robotics.ccny.cuny.edu/

Overview

The stack contains ROS applications for visual odometry and mapping using RGB-D cameras. The applications are built on top of the rgbdtools library.

This code is at an experimental stage, and licensed under the GPLv3 license.

Installing

From source

Create a directory where you want the package downloaded (ex. ~/ros), and make sure it's added to your$ROS_PACKAGE_PATH.

If you don't have git installed, do so:

sudo apt-get install git-core

Download the stack from our repository:

git clone https://github.com/ccny-ros-pkg/ccny_rgbd_tools.git

Install any dependencies using rosdep.

rosdep install ccny_rgbd_tools

Alternatively, you can manually install the dependencies by

sudo apt-get install libsuitesparse-dev

Compile the stack:

rosmake ccny_rgbd_tools

If you get an error compiling ccny_g2o, it might be because of an incompatible g2o installation. Try removing libg2o:

sudo apt-get remove ros-fuerte-libg2o
sudo apt-get remove ros-groovy-libg2o

Quick usage

Connect your RGB-D camera and launch the Openni device. The openni_launch file will start the driver and the processing nodelets.

roslaunch ccny_openni_launch openni.launch 

For faster performace, consider using dynamic reconfigure to change the sampling rate of the rgbd_image_proc nodelet. For example, setting it to to 0.5 will downsample the images by a factor of 2.

Next, launch the visual odometry:

roslaunch ccny_rgbd vo+mapping.launch

Finally, launch rviz.

rosrun rviz rviz

For convenience, you can load the ccny_rgbd/launch/rviz.cfg file.

References

If you use this system in your reasearch, please cite the following paper:

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

More info

Documentation:

Videos: