LSD-SLAM: Large-Scale Direct Monocular SLAM

LSD-SLAM is a novel approach to real-time monocular SLAM. It is fully direct (i.e. does not use keypoints / features) and creates large-scale, semi-dense maps in real-time on a laptop. For more information see http://vision.in.tum.de/lsdslam where you can also find the corresponding publications and Youtube videos, as well as some example-input datasets, and the generated output as rosbag or .ply point cloud.

This fork contains a version that relieves the user of the horrors of a ROS dependency and uses the much nicer lightweight Pangolin framework instead.

Related Papers

• LSD-SLAM: Large-Scale Direct Monocular SLAM, J. Engel, T. Schöps, D. Cremers, ECCV '14

• Semi-Dense Visual Odometry for a Monocular Camera, J. Engel, J. Sturm, D. Cremers, ICCV '13

1. Quickstart / Minimal Setup

• Install boost glew glm libqglviewer suite-sparse eigen cmake opencv qt5 using 'brew'
• Follow the instructions to compile Pangolin and g2o
• Update build settings -> header search path & library search path
• Update build phases -> link binary with libraries
• Copy libg2o***.dylib & libpangolin.dylib to /usr/local/lib

There are still a bit problem with g2o optimization, but at least can run it on Xcode.

3. Running

Supports raw PNG images. For example, you can down any dataset from here in PNG format, and run like;

./LSD -c ~/Mono_Logs/LSD_machine/cameraCalibration.cfg -f ~/Mono_Logs/LSD_machine/images/

4. License

LSD-SLAM is licensed under the GNU General Public License Version 3 (GPLv3), see http://www.gnu.org/licenses/gpl.html.