MCPTAM is a set of ROS nodes for running Real-time 3D Visual Simultaneous Localization and Mapping (SLAM) using Multi-Camera Clusters. It includes tools for calibrating both the intrinsic and extrinsic parameters of the individual cameras within the rigid camera rig.
License: GNU General Public License v3.0
CMake 2.22%C++ 96.82%C 0.96%Python 0.01%
mcptam's Introduction
*************************************************************************
*
*
* Copyright 2014 Adam Harmat (McGill University)
* [[email protected]]
* Michael Tribou (University of Waterloo)
* [[email protected]]
*
* Multi-Camera Parallel Tracking and Mapping (MCPTAM) is free software:
* you can redistribute it and/or modify it under the terms of the GNU
* General Public License as published by the Free Software Foundation,
* either version 3 of the License, or (at your option) any later
* version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*
* MCPTAM is based on the Parallel Tracking and Mapping (PTAM) software.
* Copyright 2008 Isis Innovation Limited
*
*
*************************************************************************
MCPTAM is a set of ROS nodes for running Real-time 3D Visual Simultaneous Localization and Mapping (SLAM) using Multi-Camera Clusters. It includes tools for calibrating both the intrinsic and extrinsic parameters of the individual cameras within the rigid camera rig.
Visit the MCPTAM website (https://github.com/aharmat/mcptam).
For more information, refer to the MCPTAM Wiki (https://github.com/aharmat/mcptam/wiki).
A Getting-Started Guide is available on the Wiki, or a snapshot can be found in the file Getting-Started.pdf.
If you use this software, please cite the following papers:
A. Harmat, M. Trentini and I. Sharf "Multi-Camera Tracking and Mapping for Unmanned Aerial Vehicles in Unstructured Environments" in Journal of Intelligent and Robotic Systems, vol. 78, no. 2, pp. 291-317, May 2015 (http://link.springer.com/article/10.1007%2Fs10846-014-0085-y)
A. Harmat, I. Sharf and M. Trentini "Parallel Tracking and Mapping with Multiple Cameras on an Unmanned Aerial Vehicle" in Intelligent Robotics and Applications Lecture Notes in Computer Science, vol. 7506, pp. 421-432, 2012 (http://link.springer.com/chapter/10.1007%2F978-3-642-33509-9_42)