参考：https://blog.csdn.net/qq_41839222/article/details/86552367
https://blog.csdn.net/weixin_44580210/article/details/89789416
https://blog.csdn.net/Chasinglight/article/details/128328183
https://blog.csdn.net/zardforever123/article/details/129042974
前置要求：
1.已经安装完成Ubuntu20.04系统
2.已经安装完成ROS-noetic
3.更换过国内源，并且有梯子（有些步骤如果下载缓慢就需要梯子）
直接进入VINS-Mono在Github的开源地址：
https://github.com/HKUST-Aerial-Robotics/VINS-Mono
根据里面的步骤：
sudo apt-get install ros-noetic-cv-bridge ros-noetic-tf ros-noetic-message-filters ros-noetic-image-transport
http://ceres-solver.org/installation.html
根据官网步骤：
首先安装依赖glog和eigen3：终端中逐行输入以下代码
# CMake
sudo apt-get install cmake
# google-glog + gflags
sudo apt-get install libgoogle-glog-dev libgflags-dev
# Use ATLAS for BLAS & LAPACK
sudo apt-get install libatlas-base-dev
# Eigen3
sudo apt-get install libeigen3-dev
# SuiteSparse (optional)
sudo apt-get install libsuitesparse-dev
将下载好的ceres-solver-2.1.0.tar.gz移到主目录下，在主目录下打开终端：逐行输入以下代码
tar zxf ceres-solver-2.1.0.tar.gz
mkdir ceres-bin
cd ceres-bin
cmake ../ceres-solver-2.1.0
make -j3
make test
# Optionally install Ceres, it can also be exported using CMake which
# allows Ceres to be used without requiring installation, see the documentation
# for the EXPORT_BUILD_DIR option for more information.
sudo make install
安装完成后验证安装：
bin/simple_bundle_adjuster ../ceres-solver-2.1.0/data/problem-16-22106-pre.txt
输出跟官网一致则ceres solver安装成功：
iter cost cost_change |gradient| |step| tr_ratio tr_radius ls_iter iter_time total_time
0 4.185660e+06 0.00e+00 1.09e+08 0.00e+00 0.00e+00 1.00e+04 0 7.59e-02 3.37e-01
1 1.062590e+05 4.08e+06 8.99e+06 5.36e+02 9.82e-01 3.00e+04 1 1.65e-01 5.03e-01
2 4.992817e+04 5.63e+04 8.32e+06 3.19e+02 6.52e-01 3.09e+04 1 1.45e-01 6.48e-01
3 1.899774e+04 3.09e+04 1.60e+06 1.24e+02 9.77e-01 9.26e+04 1 1.43e-01 7.92e-01
4 1.808729e+04 9.10e+02 3.97e+05 6.39e+01 9.51e-01 2.78e+05 1 1.45e-01 9.36e-01
5 1.803399e+04 5.33e+01 1.48e+04 1.23e+01 9.99e-01 8.33e+05 1 1.45e-01 1.08e+00
6 1.803390e+04 9.02e-02 6.35e+01 8.00e-01 1.00e+00 2.50e+06 1 1.50e-01 1.23e+00
Solver Summary (v 2.1.0-eigen-(3.4.0)-lapack-suitesparse-(5.10.1)-acceleratesparse-eigensparse-no_openmp)
Original Reduced
Parameter blocks 22122 22122
Parameters 66462 66462
Residual blocks 83718 83718
Residuals 167436 167436
Minimizer TRUST_REGION
Dense linear algebra library EIGEN
Trust region strategy LEVENBERG_MARQUARDT
Given Used
Linear solver DENSE_SCHUR DENSE_SCHUR
Threads 1 1
Linear solver ordering AUTOMATIC 22106,16
Schur structure 2,3,9 2,3,9
Cost:
Initial 4.185660e+06
Final 1.803390e+04
Change 4.167626e+06
Minimizer iterations 7
Successful steps 7
Unsuccessful steps 0
Time (in seconds):
Preprocessor 0.121654
Residual only evaluation 0.065968 (7)
Jacobian & residual evaluation 0.303356 (7)
Linear solver 0.436650 (7)
Minimizer 0.890535
Postprocessor 0.001684
Total 1.013873
Termination: CONVERGENCE (Function tolerance reached. |cost_change|/cost: 1.769756e-09 <= 1.000000e-06)
主目录下新建一个工作空间，拷下VINS-Mono的github代码
mkdir -p ~/vinsmono_ws/src
cd ~/vinsmono_ws/src
git clone https://github.com/HKUST-Aerial-Robotics/VINS-Mono.git
然后需要对拷下来的代码进行更改以适配Ubuntu20.04和ros noetic
更改1：将所有文件夹下的CMakeLists.txt文件由C++11全部修改为C++14编译，具体有ar_demo，benchmark_publisher，camera_model，feature_tracker，pose_graph，vins_estimator这些文件夹
#set(CMAKE_CXX_FLAGS "-std=c++11")
set(CMAKE_CXX_FLAGS "-std=c++14")
ROS noetic版本自带OpenCV4，而VINS-Mono中开发使用的是OpenCV3，修改VINS-Mono代码兼容OpenCV4。
更改2：在camera_model/include/chessboard下的头文件Chessboard.h中添加
#include <opencv2/imgproc/types_c.h>
#include <opencv2/calib3d/calib3d_c.h>
更改3：在camera_model/include/calib的头文件CameraCalibration.h、pose_graph/src下的头文件pose_graph.h和keyframe.h以及pose_graph/src/ThirdParty/DVision下的头文件BRIEF.h中添加
#include <opencv2/imgproc/types_c.h>
#include <opencv2/imgproc/imgproc_c.h>
更改完成，之后编译文件
cd ~/vinsmono_ws
catkin_make
echo "source ~/vinsmono_ws/devel/setup.bash" >> ~/.bashrc
运行之前在对应的配置文件***_config.yaml中修改结果输出目录，比如要运行Euroc数据集，则在euroc_config.yaml中更改
output_path: "your_path/output"
Euroc数据集可前往官网下载，从官网给的下载地址中下载，下载其中的bag文件，比如V1_01_easy.bag。将其放在目录~/dataset/下，然后分别打开三个终端
roslaunch vins_estimator euroc.launch
roslaunch vins_estimator vins_rviz.launch
rosbag play ~/dataset/V1_01_easy.bag
运行结果如下图，如果运行起来了那就表示VINS-Mono安装成功
进入realsense官网的linux安装驱动链接，首先注册公钥：
sudo mkdir -p /etc/apt/keyrings
curl -sSf https://librealsense.intel.com/Debian/librealsense.pgp | sudo tee /etc/apt/keyrings/librealsense.pgp > /dev/null
确认https支持是否已经下载：
sudo apt-get install apt-transport-https
将服务器添加到存储库列表：
echo "deb [signed-by=/etc/apt/keyrings/librealsense.pgp] https://librealsense.intel.com/Debian/apt-repo `lsb_release -cs` main" | \
sudo tee /etc/apt/sources.list.d/librealsense.list
sudo apt-get update
安装库：
sudo apt-get install librealsense2-dkms
sudo apt-get install librealsense2-utils
可选择安装developer和debug包
sudo apt-get install librealsense2-dev
sudo apt-get install librealsense2-dbg
都安装完成后，插上相机，运行realsense，注意D435i需要连接USB3.0的口
realsense-viewer
运行结果如下图，注意左上方是否是USB3.*，USB2传输速率不足会很卡。
还是进realsense-ros的github官网，跟着官网的步骤来：
https://github.com/IntelRealSense/realsense-ros/tree/ros1-legacy
根据步骤：首先创建工作空间
mkdir -p ~/realsense_ws/src
cd ~/realsense_ws/src/
拷下realsense-ros的代码：
git clone https://github.com/IntelRealSense/realsense-ros.git
cd realsense-ros/
git checkout `git tag | sort -V | grep -P "^2.\d+\.\d+" | tail -1`
cd ..
确认ddynamic_reconfigure是否已经安装：
sudo apt-get install ros-noetic-ddynamic-reconfigure
编译文件：
catkin_init_workspace
cd ..
catkin_make clean
catkin_make -DCATKIN_ENABLE_TESTING=False -DCMAKE_BUILD_TYPE=Release
catkin_make install
添加.bashrc
echo "source ~/realsense_ws/devel/setup.bash" >> ~/.bashrc
source ~/.bashrc
验证安装：
启动相机节点：
roslaunch realsense2_camera rs_camera.launch
查看话题列表，列表如下图所示：
rostopic list
运行以下代码可查看rgb图和深度图：
rosrun rqt_image_view rqt_image_view
运行如下代码可以查看点云图：
roslaunch realsense2_camera demo_pointcloud.launch
这里再贴一下参考：
从零开始使用Realsense D435i运行VINS-Mono
如何用Realsense D435i运行VINS-Mono等VIO算法 获取IMU同步数据
第一处，修改unite_imu_method如下，这里是让IMU的角速度和加速度作为一个topic输出
<arg name="unite_imu_method" default="copy"/>
第二处，修改enable_sync参数为true，这里是开机相机和IMU的同步
<arg name="enable_sync" default="true"/>
然后是第三处，realsense默认图片流开启，但imu流却是关闭的，需要打开imu流：不然就会出现错误：执行roslaunch vins_estimator realsense_color.launch指令时提示：no previous pose graph，且打开rviz时无轨迹，fixed frame报错unknown frame world，这个上述博主都没讲到，不知是否是版本原因。
<arg name="enable_gyro" default="true"/>
<arg name="enable_accel" default="true"/>
第一处，修改订阅的topic
imu_topic: "/camera/imu"
image_topic: "/camera/color/image_raw"
第二处，修改相机内参，这里先再次打开运行realsesne
roslaunch realsense2_camera rs_camera.launch
然后可以通过如下命令获取相机内参
rostopic echo /camera/color/camera_info
图片的宽和高分别填入：
image_width: 1280
image_height: 720
K里面第1个是fx，第3个是cx，第5个是fy，第6个是cy，照读出来的对应填写即可。
projection_parameters:
fx: 910.2757568359375
fy: 909.9263305664062
cx: 652.0943603515625
cy: 379.8188781738281
第三处，IMU到相机的变换矩阵，这里因为没有去搞外参，所以选2自动修正
# Extrinsic parameter between IMU and Camera.
estimate_extrinsic: 2 # 0 Have an accurate extrinsic parameters. We will trust the following imu^R_cam, imu^T_cam, don't change it.
# 1 Have an initial guess about extrinsic parameters. We will optimize around your initial guess.
# 2 Don't know anything about extrinsic parameters. You don't need to give R,T. We will try to calibrate it. Do some rotation movement at beginning.
#If you choose 0 or 1, you should write down the following matrix.
第四处，IMU参数，这里全部修改注释给的参数
#imu parameters The more accurate parameters you provide, the better performance
acc_n: 0.2 # accelerometer measurement noise standard deviation. #0.2
gyr_n: 0.05 # gyroscope measurement noise standard deviation. #0.05
acc_w: 0.02 # accelerometer bias random work noise standard deviation. #0.02
gyr_w: 4.0e-5 # gyroscope bias random work noise standard deviation. #4.0e-5
g_norm: 9.805 # gravity magnitude
第五处，是否需要在线估计同步时差，因为realsense D435i已经做好了硬件同步，这里选择不需要
#unsynchronization parameters
estimate_td: 0 # online estimate time offset between camera and imu
td: 0.000 # initial value of time offset. unit: s. readed image clock + td = real image clock (IMU clock)
第六处，相机曝光改成全局曝光
#rolling shutter parameters
rolling_shutter: 0 # 0: global shutter camera, 1: rolling shutter camera
rolling_shutter_tr: 0.033 # unit: s. rolling shutter read out time per frame (from data sheet).
第七处，搜索output，把两个output_path改为自己的路径
output_path: "/home/zz/output/"
pose_graph_save_path: "/home/zz/output/pose_graph/"
首先对realsense_ws和vinsmono_ws进行重新编译
cd ~/realsense_ws
catkin_make
cd ~/vinsmono_ws
catkin_make
打开相机，运行VINS-Mono，分别打开三个终端输入如下代码
roslaunch realsense2_camera rs_camera.launch
roslaunch vins_estimator realsense_color.launch
roslaunch vins_estimator vins_rviz.launch
拿着D435i在房间内走了一下，结果如下图所示
这样整个过程就走通了，最后如果rviz的Global Status一开始显示错误的话，就把相机拿起来动一动就可以了。
整个过程有些是必须从国外的源下载的，碰到有下载缓慢的情况，就把梯子开全局，速度就会上去。