SVO === Disclaimer ---------- SVO has been tested under ROS Groovy and Hydro and Ubuntu 12.04 and 13.04. This is research code, expect that it changes often and any fitness for a particular purpose is disclaimed. Installation Instructions ------------------------- #### OPTIONAL: g2o - General Graph Optimization Only required if you want to run bundle adjustment. It is not necessary for visual odometry. g2o requires the following system dependencies: `cmake, libeigen3-dev, libsuitesparse-dev, libqt4-dev, qt4-qmake, libqglviewer-qt4-dev`, install them with `apt-get` I suggest an out-of-source build of g2o: cd workspace git clone https://github.com/RainerKuemmerle/g2o.git cd g2o mkdir build cd build cmake .. make sudo make install If you don't want to make a system install, then you can replace the cmake command with `cmake .. -DCMAKE_INSTALL_PREFIX:PATH=$HOME/installdir` #### Sophus - Lie groups Sophus by Hauke Strasdat implements Lie groups that we need to describe rigid body transformations. cd workspace git clone https://github.com/strasdat/Sophus.git cd Sophus git checkout a621ff mkdir build cd build cmake .. make You don't need to install the library since `cmake ..` writes the package location to `~.cmake/packages/` where CMake can later find it. #### Fast Detector The Fast detector by Edward Rosten is used to detect corners. To simplify installation we provide a CMake package that contains the fast detector from the libCVD library (http://www.edwardrosten.com/cvd/). cd workspace git clone https://github.com/uzh-rpg/fast.git cd fast mkdir build cd build cmake .. make #### ViKit - Some useful tools that we need ViKit for instance contains camera models, some math and interpolation functions that SVO needs. ViKit is a catkin project, therefore, download it into your catkin workspace source folder. cd catkin_ws/src git clone https://github.com/uzh-rpg/rpg_vikit.git #### SVO Now we are ready to build SVO. Clone it into your catkin workspace cd catkin_ws/src git clone https://github.com/uzh-rpg/rpg_slam.git If you installed g2o then set `HAVE_G2O` in `svo/CMakeLists.txt` to TRUE. Then build catkin_make Run SVO on a Dataset ------------------------- Download this example dataset: [rpg.ifi.uzh.ch/datasets/airground_rig_s3_2013-03-18_21-38-48.bag](http://rpg.ifi.uzh.ch/datasets/airground_rig_s3_2013-03-18_21-38-48.bag) Open a new console and start SVO with the prepared launchfile: roslaunch svo_ros test_rig3.launch Open a new console and start RViz rosrun rviz rviz In RViz, load the configuration file (File > Open Config) which is stored in `svo_ros/rviz_config.rviz`. Now you are ready to start the rosbag. Open a new console and change to the directory where you have downloaded the example dataset. Then type: rosbag play airground_rig_s3_2013-03-18_21-38-48.bag Now you should see the video with tracked features (green) and in RViz how the camera moves. SVO GUI ------- Type `rosrun rqt_svo rqt_svo` to run the SVO widget that displays the number of tracked features, the frame rate and provides some interface buttons. Keyboard Shortcuts ------------------ Make sure to active the console window when pressing the keys. * `s` Start/Restart * `q` Quit * `r` Reset Parameter Settings ------------------ A description of all parameters which can be set via the launchfile is provided in `svo/include/config.h`. The default parameters can be viewed in `svo/src/config.cpp`. Moreover, some additional parameters (mainly rostopic names etc.) are read from the ros parameter server in `svo_ros/slam_node.cpp`. Generating Code Documentation ----------------------------- You can generate a Doxygen documentation as follows cd svo doxygen Doxyfile Contributing ------------ You are very welcome to contribute by opening a pull request via Github. I try to follow the ROS C++ style guide. Licence ------- The source code is released under GPLv3 licence. A professional edition license for closed-source projects is also available. Please contact `forster at ifi dot uzh dot ch` for further information.