1.将启动项改为SSD启动
(待续)
2.环境配置(Ubuntu 18.04)
(0)Cuda 10.2
用sdkmanager的刷镜像方式一般没有预装cuda。装系统之后安装更简单一些。
sudo apt-get update
sudo apt-get install cuda-toolkit-10-2
安装好之后,在 .bashrc中配置环境变量。source之后,nvcc — version 即可查看cuda版本。
export PATH=/usr/local/cuda-10.2/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
export CUDA_ROOT=/usr/local/cuda
(1)Eigen
# Remove pre-built Eigen
sudo apt-get remove libeigen3-dev
cd ~/Downloads/
wget -O eigen.zip https://gitlab.com/libeigen/eigen/-/archive/3.3.7/eigen-3.3.7.zip #check version
unzip eigen.zip
mkdir eigen-build && cd eigen-build
cmake ../eigen-3.3.7/ && sudo make install
pkg-config --modversion eigen3 # Check Eigen Version
(2)Ceres solver
cd ~/Downloads/
sudo apt-get install -y cmake libgoogle-glog-dev libatlas-base-dev libsuitesparse-dev
wget http://ceres-solver.org/ceres-solver-1.14.0.tar.gz
tar zxf ceres-solver-1.14.0.tar.gz
mkdir ceres-bin
mkdir solver && cd ceres-bin
cmake ../ceres-solver-1.14.0 -DEXPORT_BUILD_DIR=ON -DCMAKE_INSTALL_PREFIX="../solver"
#good for build without being root privileged and at wanted directory
make -j3 # 6 : number of cores
make install
bin/simple_bundle_adjuster ../ceres-solver-1.14.0/data/problem-16-22106-pre.txt # to check version
(3) Opencv
# remove prebuilt opencv
sudo apt-get purge libopencv* python-opencv
sudo apt-get update
sudo apt-get install -y build-essential pkg-config
## libeigen3-dev # recommend to build from source
sudo apt-get install -y cmake libavcodec-dev libavformat-dev libavutil-dev \
libglew-dev libgtk2.0-dev libgtk-3-dev libjpeg-dev libpng-dev libpostproc-dev \
libswscale-dev libtbb-dev libtiff5-dev libv4l-dev libxvidcore-dev \
libx264-dev qt5-default zlib1g-dev libgl1 libglvnd-dev pkg-config \
libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev mesa-utils
sudo apt-get install python2.7-dev python3-dev python-numpy python3-numpy
# To fix OpenGL related compilation problems
cd /usr/lib/aarch64-linux-gnu/
sudo ln -sf libGL.so.1.0.0 libGL.so
sudo vim /usr/local/cuda/include/cuda_gl_interop.h
# Comment (line #62~68) of cuda_gl_interop.h
//#if defined(__arm__) || defined(__aarch64__)
//#ifndef GL_VERSION
//#error Please include the appropriate gl headers before including cuda_gl_interop.h
//#endif
//#else
#include <GL/gl.h>
//#endif
# Then once linking is done, go to Downloads to begin opencv installation
cd ~/Downloads/
wget -O opencv.zip https://github.com/opencv/opencv/archive/3.4.1.zip # check version
unzip opencv.zip
cd opencv-3.4.1/ && mkdir build && cd build
cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D WITH_CUDA=ON \
-D CUDA_ARCH_BIN=6.2 \
-D CUDA_ARCH_PTX="" \
-D ENABLE_FAST_MATH=ON \
-D CUDA_FAST_MATH=ON \
-D WITH_CUBLAS=ON \
-D WITH_LIBV4L=ON \
-D WITH_GSTREAMER=ON \
-D WITH_GSTREAMER_0_10=OFF \
-D WITH_QT=ON \
-D WITH_OPENGL=ON \
-D CUDA_NVCC_FLAGS="--expt-relaxed-constexpr" \
-D WITH_TBB=ON \
../
make # running in single core is good to resolve the compilation issues
sudo make install
cd ../../ && sudo rm -rf opencv-3.4.1 # optional (can save 10GB Disk Space)
pkg-config --modversion opencv # Check opencv Version
(3) ROS 安装
参考ros.org 自行安装。此处与教程(vins-fusion-gpu-tx2-nano)略有差异,我直接使用了ros内置的cv_bridge。因为涉及到源码安装opencv,cv_bridgeConfig.cmake中include的地址要做修改,否则后续编译报错,可以参考上一篇文章。
3.VINS-Fusion-GPU 安装及编译
具体参数可看源文档
https://github.com/pjrambo/VINS-Fusion-gpu
cd ~/catkin_ws/src && git clone https://github.com/pjrambo/VINS-Fusion-gpu #GPU
sudo apt-get install ros-melodic-tf
sudo apt-get install ros-melodic-image-transport
sudo apt-get install ros-melodic-rviz
# Edit CMakeLists.txt for loop_fusion and vins_estimator
cd ~/catkin_ws/src/VINS-Fusion-gpu/loop_fusion && gedit CMakeLists.txt
##For loop_fusion : line 19
#find_package(OpenCV)
include(/usr/local/share/OpenCV/OpenCVConfig.cmake)
cd ~/catkin_ws/src/VINS-Fusion-gpu/vins_estimator && gedit CMakeLists.txt
##For vins_estimator : line 20
#find_package(OpenCV REQUIRED)
include(/usr/local/share/OpenCV/OpenCVConfig.cmake)
cd ~/catkin_ws/
source devel/setup.bash
catkin_make
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