Foreword
Recently, I used orb_slam2 modified by Dr. Gao Xiang to generate a dense point cloud, and then used an octree to generate a two-dimensional raster map for navigation. However, the effect of the created map is not very good and the drift is too serious.
On the left is the image generated by cartographer, and on the right is the image generated by orb_slam2.
The effect is so poor. On the one hand, my point cloud processing is not good, because the generated point cloud is tilted in the octree, and the angle I manually adjusted may not be so accurate. On the other hand, the generated pcd itself is Drift, this is the pcd file that was run out
So I looked at some other algorithms and wanted to do some evaluation of these algorithms. I ran the same euroc data set MH01_easy.
Installation of three algorithms
Because the library used by orb_slam2 conflicts with orb_slam3, two computers are used, and vins_mono is installed on both computers. Orb_slam3 is installed on a newly installed system.
1.orb_slam2
Using the modified version of GitHub by Dr. Gao Xiang – gaoxiang12/ORBSLAM2_with_pointcloud_map
Because it is troublesome to install and compile, I will make up for it later when I have time.
2.vins_mono
2.1 Installing system packages
sudo apt install ros-melodic-cv-bridge ros-melodic-tf ros-melodic-message-filters ros-melodic-image-transport
2.2 Install ceres_solver
Install dependencies
sudo apt-get install cmake sudo apt-get install libgoogle-glog-dev libgflags-dev sudo apt-get install libatlas-base-dev sudo apt-get install libeigen3-dev sudo apt-get install libsuitesparse-dev
Download the ceres_solver source code (note version compatibility, choose version 1.14)
Refer to this article
Ubuntu18.04 installs Ceres1.14_ubuntu18 installs ceres-CSDN blog
Compile and install
mkdir build cd build cmake.. make make test sudo make install
If the compilation error is reported, it may be a problem with the cmake version. You can establish a higher version of cmake soft connection. Be sure not to use automove. See this article.
cmake upgrade and update (ubuntu18.04)-CSDN blog
2.3 Run
roslaunch vins_estimator euroc.launch roslaunch vins_estimator vins_rviz.launch rosbag play --pause MH_01_easy.bag
The data set can be downloaded from here
kmavvisualinertialdatasets – ASL Datasets
3.orb_slam3
1. Install libraries and dependencies
Pangolin,opencv,eigen3,boost
pangolin uses version 0.6 like orb_slam2, opencv and eigen3 can use their own ones.
boost
Boost Downloads Download boost_1_77_0.tar.gz version
tar -xvf boost_1_77_0.tar.gz cd ./boost_1_77_0 ./bootstrap.sh sudo ./b2 install
rosdep Because the official website update download can easily fail, here we use rosdepc of Yuxiang ros.
sudo pip install rosdepc //If pip cannot be found, try pip3 sudo pip3 install rosdepc //If it still doesn't work, execute the following first and then repeat the above. sudo apt-get install python3-pip sudo rosdepc init rosdepc update
Tried and tested before but I don’t know why the new system can’t connect to the website. Here is a one-click installation using Xiaoyu.
wget http://fishros.com/install -O fishros & amp; & amp; . fishros
2. Compile
code
git clone https://github.com/UZ-SLAMLab/ORB_SLAM3.git
compile
Compiling build.sh is relatively simple. First give permissions to build_sh.
sudo chmod + x build.sh
Our opencv version does not correspond to the c++ version. We need to change two places in Cmakelists.
1.find
find_package(OpenCV 4.4)
Change to
find_package(OpenCV 3 REQUIRED)
2.find
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c + + 11")
Change to
set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -std=c + + 14")
If an internal segmentation fault occurs during compilation, just modify make -j8 in build.sh and delete all -j8.
If the compilation fails, you need to delete the build and lib folders under ORB_SlAM3, as well as the build and lib folders in DBoW2 and g2o under Thirdparty, and the build folder under Sophus. If you don’t delete it, an error will be reported during the next compilation. If some of the above files are not available, it means that the last compilation has not reached that point.
A few more steps to compile build_ros.sh
First of all, the Cmakelists need to be modified as above, and there are some
include_directories(
${PROJECT_SOURCE_DIR}
${PROJECT_SOURCE_DIR}/../../../
${PROJECT_SOURCE_DIR}/../../../include
${PROJECT_SOURCE_DIR}/../../../include/CameraModels
${Pangolin_INCLUDE_DIRS}
#Add the following. I don’t know if the catkin line is needed or not, so just add it all to avoid recompiling (this line will be deleted after copying)
${EIGEN3_INCLUDE_DIR}
${catkin_INCLUDE_DIRS}
${PROJECT_SOURCE_DIR}/../../../Thirdparty/Sophus
)
There is no ROS folder in Examples in the new version of ORB_SLAM3. Just copy the one in Eamples_old and then add the package path to the bash file.
sudo gedit ~/.bashrc
export ROS_PACKAGE_PATH=${ROS_PACKAGE_PATH}:/home/cr/ORB_SLAM3/Examples/ROS
Copy the above code into it. Note that it must be placed at the end of the source path otherwise it will not be displayed later. Just put it at the end to be on the safe side. Next, check whether there is any in the output path
echo ${ROS_PACKAGE_PATH}
The code also needs to be modified
In ~/ORB_SLAM3/Examples/ROS/ORB_SLAM3/src/AR/ViewerAR.cc
Add header file #include <Eigen/Dense> #include <opencv2/core/eigen.hpp>
//vPoints.push_back(pMP->GetWorldPos()); Comment out the above and change it to the following cv::Mat WorldPos; cv::eigen2cv(pMP->GetWorldPos(), WorldPos); vPoints.push_back(WorldPos);
//cv::Mat Xw = pMP->GetWorldPos(); Comment out the above and change it to the following cv::Mat Xw; cv::eigen2cv(pMP->GetWorldPos(), Xw);
In ~/ORB_SLAM3/Examples/ROS/ORB_SLAM3/src/AR/ros_mono_ar.cc
Add header file #include <Eigen/Dense> #include <opencv2/core/eigen.hpp>
//cv::Mat Tcw = mpSLAM->TrackMonocular(cv_ptr->image,cv_ptr->header.stamp.toSec()); Comment out the above and change it to the following cv::Mat Tcw; Sophus::SE3f Tcw_SE3f = mpSLAM->TrackMonocular(cv_ptr->image,cv_ptr->header.stamp.toSec()); Eigen::Matrix4f Tcw_Matrix = Tcw_SE3f.matrix(); cv::eigen2cv(Tcw_Matrix, Tcw);
Finally, enter the following command to update the shared library and compile it. Remember to give permissions to build_ros first.
sudo ldconfig
3.3 Run
./Examples/Monocular/mono_euroc ./Vocabulary/ORBvoc.txt ./Examples/Monocular/EuRoC.yaml /home/************/MH_01_easy ./Examples/Monocular/EuRoC_TimeStamps/MH01 .txt
*****Change to your own path. Note that what is running here is not the bag, but the data set, because subsequent evaluation requires a file in the data set.
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
If it crashes halfway through the run or just at the beginning and reports an error that the core has been dumped, modify the yaml file in the above code.
ORBextractor.nFeatures: 2000
Change it to 3000. If it still doesn’t work, increase it. This problem has been stuck for a long time when running orb_slam2 before. After testing, the final values are not much different. The following content will give the results.
evo installation and evaluation
1. evo installation
pip3 install -i https://pypi.tuna.tsinghua.edu.cn/simple/ evo --upgrade --no-binary evo
Afterwards, enter the evo tap key completion in the terminal and other commands will appear. That means the installation is successful. If not, don’t worry, just restart the computer and it will be fine.
sudo apt-get install python-tk sudo apt-get install python3-tk
2. vins_mono test
The trajectory generated by vins_mono cannot be used directly for testing, so the code needs to be modified.
Ubuntu 18.04 — Evaluation and use of VINS-Mono operation and EVO_vins-mono implementation ubuntu18.04-CSDN blog
Refer to this article
After the modification is completed, there will be a file vins_result_loop.txt, which is the file to be evaluated. In the data set we mentioned above, which is the data set run by orb_slam3, the file MH_01_easy/mav0/state_groundtruth_estimate0/data.csv is in euroc format and needs to be Convert to tum format
evo_traj euroc data.csv --save_as_tum
Then put vins_result_loop.txt and data.tum in the same directory, and execute the following code to get the results.
evo_ape tum data.tum vins_result_loop.txt -p --plot_mode=xyz -a --correct_scale --save_results ./test.zip
Just give the compressed package of the last saved results a random name.
There may be an error ModuleNotFoundError: No module named ‘_tkinter’
Just install it
sudo apt-get install python-tk sudo apt-get install python3-tk
Execute it again and you will see the result.
3. ORB_SLAM3 test
The files generated by ORB_SLAM2 can be used directly. Note that the file to be evaluated is not KeyFrameTrajectory.txt but CameraTrajectory.txt.
Similarly, put it in the same directory as data.tum and execute the code to see the results.
evo_ape tum data.tum CameraTrajectory.txt -p --plot_mode=xyz -a --correct_scale --save_results ./test.zip
Result comparison and follow-up thoughts
orb_slam2
vin_mono
ORB_SLAM3_3000 (modified yaml file)
ORB_SLAM3_2000 (I ran 70% to 80% core dump, but the trajectory file can also be used)
After analysis, although only one data set was run, the data was very intuitive. The effect of ORB_SLAM3 was great. Then I modified the yaml file and the difference between the two sets of data was very small. Later, I will test multiple sets of data sets with different values of ORBextractor.nFeatures.
But in the final analysis, we still want to build a qualified map. There is a long way to go and we need to work together to encourage each other.