DVO 在indigo下运行 ubuntu14.04
The build has been tested on Linux Mint Rosa 17.3 (Ubuntu Trusty 14.04) + ROS Indigo. It also worked on Ubuntu Xenial 16.04 + ROS Kinetic. The following steps assume ROS Indigo.
Install ROS Indigo
sudo sh -c ‘echo “deb http://packages.ros.org/ros/ubuntu trusty main” > /etc/apt/sources.list.d/ros-latest.list’
sudo apt-key adv –keyserver hkp://ha.pool.sks-keyservers.net –recv-key 0xB01FA116
sudo apt-get update
sudo apt-get install ros-indigo-desktop-full
sudo rosdep init
rosdep update
echo “source /opt/ros/indigo/setup.bash” >> ~/.bashrc
source ~/.bashrc
sudo apt-get install python-rosinstall
Checkout DVO SLAM
The DVO SLAM code is clone from jade-devel branch from DVO SLAM repository. This version uses catkin to build the code, which makes things much easier.
The Catkin workspace is organized as follows:
dvo_slam (Catkin workspace root)
src
dvo_core
CMakeLists.txt
src
dvo_benchmark
CMakeLists.txt
src
README.md
where dvo_slam is the root of the Catkin workspace and has 4 packages: dvo_core, dvo_ros, dvo_slam, and dvo_benchmark.
Dependencies
sophus
git clone https://github.com/strasdat/Sophus.git
cd Sophus
git checkout b474f05
mkdir build
cd build
cmake ..
make
sudo make install
Note: As of Dec 2016, the master branch of Sophus seems no longer compatible for building DVO SLAM. Here we use an older version of Sophus, commit b474f05, to build.
CSparse
sudo apt-get install libsuitesparse-dev
g2o
It is necessary to build g2o after installing suitesparse to let g2o detect suitesparse. Recent g2o starts using C++11, which causes trouble when DVO links to the default PCL provided by Ubuntu. This PCL build does not have C++11 support.
It is best to use an old version of g2o instead, which does not require C++11, so we don’t need to rebuild PCL with C++11. The suitable g2o version is commit 67d5fa7. (To speed up the g2o compilation, you can skip building g2o apps and examples, which are not necessary in our case.)
git clone https://github.com/RainerKuemmerle/g2o.git
cd g2o
git checkout 67d5fa7
mkdir build
cd build
cmake .. -DBUILD_SHARED_LIBS:BOOL=OFF -DBUILD_LGPL_SHARED_LIBS:BOOL=OFF -DG2O_BUILD_APPS:BOOL=OFF -DG2O_BUILD_EXAMPLES:BOOL=OFF
make
sudo make install
If your system has Eigen >= 3.3, don’t use it with g2o. The old version of g2o is only compatible to Eigen 3.2.8. Download Eigen 3.2.8, put it into the EXTERNAL folder in g2o, and use this CMake command instead:
cmake .. -DBUILD_SHARED_LIBS:BOOL=OFF -DBUILD_LGPL_SHARED_LIBS:BOOL=OFF -DG2O_BUILD_APPS:BOOL=OFF -DG2O_BUILD_EXAMPLES:BOOL=OFF -DG2O_EIGEN3_INCLUDE=/home/sutd/Workspace/g2o/EXTERNAL/eigen3.2.8/
This will force g2o to use our Eigen library instead of the system Eigen.
We have to build g2o into static libraries and build DVO SLAM also as static libraries to avoid some weird undefined reference to g2o::csparse_extension. It could be possible to build as shared libraries (by default) but somehow it does not work on my machine.
Building DVO SLAM
Go back to Catkin workspace’s root folder and execute
catkin_make -DCMAKE_BUILD_TYPE=Release
to build all packages. You can also build each package separately by
catkin_make –pkg dvo_core -DCMAKE_BUILD_TYPE=Release
catkin_make –pkg dvo_ros -DCMAKE_BUILD_TYPE=Release
catkin_make –pkg dvo_slam -DCMAKE_BUILD_TYPE=Release
catkin make –pkg dvo_benchmark -DCMAKE_BUILD_TYPE=Release
How to run
source devel/setup.sh
This will make ROS able to find our newly built packages.
Now we can navigate to example folder and execute
roslaunch launch/benchmark.launch dataset:=
You can check the output trajectory in example/output/trajectory.txt.
Dataset follows structures in RGBD SLAM by TUM. The only difference is the depth scale is reset 1000 (in benchmark_slam.cpp) instead of 5000. I found this to be more convenient as images from Kinect or Asus Xtion all follows this convention.
The focal length is hard coded in benchmark_slam.cpp. Change it to your focal length.
Rviz
After DVO SLAM is running, you can launch rviz to observe some results.
In global options in the left panel, set target frame is “world”. Then click Add button, switch to By Topic tab, and choose PointCloud2. You can also add Interactive Markers.
If you see nothing in rviz but DVO is running, it could be because the project is built in Debug mode, which is slow. Make sure -DCMAKE_BUILD_TYPE=Release is used with catkin_make