安装rtabmap_ros包
一、前言
RTAB-Map (Real-Time Appearance-Based Mapping)是一种基于全局贝叶斯闭环检测的RGB-D Graph SLAM方法。它可以用kinect的深度信息结合kinect变换得到的激光数据进行即时定位与建图（gmapping算法志只用到了kinect转换得到的激光数据，而把深度信息丢弃了）。
官网地址：http://introlab.github.io/rtabmap/
ROS下面安装请看：https://github.com/introlab/rtabmap_ros#rtabmap_ros
教程请看：https://github.com/introlab/rtabmap/wiki/Tutorials
在机器人上使用RTAB-Map：Setup RTAB-Map on Your Robot!
二、deb方式安装
嫌麻烦采用deb方式安装
Jade: $ sudo apt-get install ros-jade-rtabmap-ros
Indigo: $ sudo apt-get install ros-indigo-rtabmap-ros
Hydro: $ sudo apt-get install ros-hydro-rtabmap-ros 三、源码安装
请看github上的安装说明：https://github.com/introlab/rtabmap_ros#rtabmap_ros
简单的安装方法是：
indigo:
$ sudo apt-get install libsqlite3-dev libpcl-1.7-all libfreenect-dev libopencv-dev hydro:
$ sudo apt-get install libsqlite3-dev libpcl-1.7-all ros-hydro-libfreenect ros-hydro-opencv2然后下载RTAB-Map源码编译安装：
$ git clone https://github.com/introlab/rtabmap.git rtabmap
$ cd rtabmap/build
$ cmake ..
$ make -j4
$ make install安装完之后插上Kinect在终端运行命令：
$ rtabmap出现GUI，然后选择“File”——“New database”，再点击开始按键就可以出现图像了
在catkin工作空间中安装RTAB-Map ros-pkg
$ cd ~/catkin_ws
$ git clone https://github.com/introlab/rtabmap_ros.git src/rtabmap_ros
$ catkin_make1、安装可选的依赖项
（1）如果你需要用到SURF/SIFT那就装一下opencv吧
请看：http://blog.csdn.net/u013453604/article/details/49781771
由于cv-bridge依赖的是opencv2，所以装opencv3的话rtabmap_ros里面有些库会冲突，这里建议装opencv 2.4.11。
（2）安装g2o，这是在闭环检测中实现图优化的包
先安装依赖项
$ sudo apt-get install cmake libeigen3-dev libsuitesparse-dev下载源码编译安装
$ cd
$ git clone https://github.com/RainerKuemmerle/g2o.git
$ cd g2o/
$ mkdir build
$ cd build/
$ cmake ../
$ make安装完之后库文件在/usr/local/lib，头文件在/usr/local/include/g2o
（3）安装其他依赖项Qt, PCL, dc1394, OpenNI, OpenNI2, Freenect, g2o, Costmap2d, Rviz, Octomap, CvBridge
$ sudo apt-get install libqt4-dev libpcl-1.7-all-dev libdc1394-22-dev ros-indigo-openni-launch ros-indigo-openni2-launch ros-indigo-freenect-launch ros-indigo-costmap-2d ros-indigo-octomap-ros ros-indigo-rviz ros-indigo-cv-bridge如果按照github上的命令安装依赖项不成功就运行上述命令吧，其中opencv和g2o我是源码安装的，所以相对于github上的命令我这里把ros-indigo-g2o去掉了，把libdc1394-dev改成了libdc1394-22-dev
（4）安装GTSAM
GTSAM is a library of C++ classes that implement smoothing and mapping (SAM) in robotics and vision, using factor graphs and Bayes networks as the underlying computing paradigm rather than sparse matrices.把gtsam包下载到某处进行编译安装:
$ cd software/
$ git clone https://bitbucket.org/gtborg/gtsam.git
$ cd gtsam
$ mkdir build
$ cd build
$ cmake ..
$ make check
$ make install（5）安装cvsba
cvsba is an OpenCV wrapper for the well-known Sparse Bundle Adjustment library (sba) by M. Lourakis.安装依赖项
$ sudo apt-get install liblapack-dev libf2c2-dev 下载cvsba：http://sourceforge.net/projects/cvsba/files/latest/download?source=typ_redirect
解压得到cvsba-1.0.0文件夹，我把它放到～/software/文件夹下
$ cd ~/software/cvsba-1.0.0
$ mkdir build
$ cd build
$ cmake ..
$ make
$ sudo make install安装完之后还要执行以下命令才可以让rtabmap_ros找到它
$ sudo mkdir /usr/local/lib/cmake/cvsba
$ sudo mv /usr/local/lib/cmake/Findcvsba.cmake /usr/local/lib/cmake/cvsba/cvsbaConfig.cmake（6）安装Freenect2
请看这里：https://github.com/OpenKinect/libfreenect2#debianubuntu-1404-perhaps-earlier
Driver for Kinect for Windows v2 (K4W2) devices (release and developer preview).
Note: libfreenect2 does not do anything for either Kinect for Windows v1 or Kinect for Xbox 360 sensors. Use libfreenect1 for those sensors.
This driver supports:
RGB image transfer
IR and depth image transfer
registration of RGB and depth images
先下载Freenect2源代码
$ cd ~/software
$ git clone https://github.com/OpenKinect/libfreenect2.git安装依赖项
$ sudo apt-get install build-essential cmake pkg-config libturbojpeg libjpeg-turbo8-dev mesa-common-dev freeglut3-dev libxrandr-dev libxi-dev安装libusb
$ sudo apt-get install libusb-1.0-0-dev注意libusb版本要大于1.0.20，否则编译freenect2的时候会报错：
CMake Error: The following variables are used in this project, but they are set to NOTFOUND.
Please set them or make sure they are set and tested correctly in the CMake files:
LibUSB_LIBRARY
linked by target "freenect2" in directory /home/siat/libfreenect2如果libusb版本太低可以先卸载libusb-1.0-0-dev更新软件源重装libusb-1.0-0-dev，运行如下命令
$ sudo apt-get remove libusb-1.0-0-dev
$ sudo apt-add-repository ppa:floe/libusb
$ sudo apt-get update
$ sudo apt-get upgrade
$ sudo apt-get install libusb-1.0-0-dev安装 GLFW3
$ sudo apt-get install libglfw3-dev如果上面命令无效请使用下面命令：
$ cd libfreenect2/depends
$ sh install_ubuntu.sh
$ sudo dpkg -i libglfw3*_3.0.4-1_*.deb安装OPENCL依赖
对于AMD GPU：
$ apt-get install opencl-headers
对于Nvidia GPU：（前提是你已经安装Nvidia驱动）
$ apt-get install opencl-headers
对于Intel GPU：
$ apt-get install beignet-dev
不行的话运行：
$ sudo apt-add-repository ppa:pmjdebruijn/beignet-testing编译Freenect2
$ mkdir build && cd build
$ cmake ..
$ make
$ sudo make install # without sudo if cmake -DCMAKE_INSTALL_PREFIX=$HOME/...运行测试
$ ./bin/Protonect2、下载安装RTAB-Map
$ cd ~
$ git clone https://github.com/introlab/rtabmap.git rtabmap
$ cd rtabmap/build
$ cmake -DCMAKE_INSTALL_PREFIX=~/catkin_ws/devel ..
$ make -j4
$ make install3、在catkin工作空间中安装RTAB-Map ros-pkg
$ cd ~/catkin_ws
$ git clone https://github.com/introlab/rtabmap_ros.git src/rtabmap_ros
$ catkin_make4、更新版本
$ cd rtabmap
$ git pull origin master
$ cd build
$ make
$ make install
$ roscd rtabmap_ros
$ git pull origin master
$ cd ~/catkin_ws
$ catkin_make四、遇到的报错
编译时遇到如下报错，最后发现是关于openni的库有问题，因为我用源码装过openni驱动，有可能是版本冲突了，其实根本没必要从源码安装，可以从其他电脑上把usr/include下面的ni文件夹拷过来，我是重装了Ubuntu和ros indigo，然后按照前面简单的安装方法安装的，过程中自动安装了openni
siat@ThinkPad-siat:~/rtabmap/build$ make -j4
[ 7%] Built target rtabmap_utilite
[ 7%] Built target uresourcegenerator
[ 8%] Built target imagesJoiner
[ 9%] Built target extractObject
[ 10%] Building CXX object corelib/src/CMakeFiles/rtabmap_core.dir/CameraThread.cpp.o
[ 10%] [ 11%] [ 12%] Building CXX object corelib/src/CMakeFiles/rtabmap_core.dir/CameraRGBD.cpp.o
Building CXX object corelib/src/CMakeFiles/rtabmap_core.dir/VisualWord.cpp.o
Building CXX object corelib/src/CMakeFiles/rtabmap_core.dir/EpipolarGeometry.cpp.o
In file included from /usr/include/ni/XnOS.h:27:0,
from /usr/include/pcl-1.7/pcl/io/openni_camera/openni.h:47,
from /usr/include/pcl-1.7/pcl/io/openni_camera/openni_depth_image.h:44,
from /home/siat/rtabmap/corelib/src/../include/rtabmap/core/CameraRGBD.h:37,
from /home/siat/rtabmap/corelib/src/CameraRGBD.cpp:28:
/usr/include/ni/XnPlatform.h:73:3: error: #error OpenNI Platform Abstraction Layer - Unsupported Platform!
#error OpenNI Platform Abstraction Layer - Unsupported Platform!
^
.
.
.
In file included from /usr/include/pcl-1.7/pcl/io/openni_camera/openni.h:50:0,
from /usr/include/pcl-1.7/pcl/io/openni_camera/openni_depth_image.h:44,
from /home/siat/rtabmap/corelib/src/../include/rtabmap/core/CameraRGBD.h:37,
from /home/siat/rtabmap/corelib/src/CameraThread.cpp:31:
/usr/include/ni/XnCppWrapper.h:10045:76: error: macro "XN_VALIDATE_NEW" passed 4 arguments, but takes just 2
XN_VALIDATE_NEW(pTrans, StateChangedCallbackTranslator, handler, pCookie);
^
/usr/include/ni/XnCppWrapper.h:10104:75: error: macro "XN_VALIDATE_NEW" passed 4 arguments, but takes just 2
XN_VALIDATE_NEW(pTrans, StateChangedCallbackTranslator, handler, pCookie);
^
[ 13%] Building CXX object corelib/src/CMakeFiles/rtabmap_core.dir/VWDictionary.cpp.o
In file included from /usr/include/ni/XnStatusCodes.h:27:0,
from /usr/include/ni/XnMacros.h:27,
from /usr/include/ni/XnOS.h:28,
from /usr/include/pcl-1.7/pcl/io/openni_camera/openni.h:47,
from /usr/include/pcl-1.7/pcl/io/openni_camera/openni_depth_image.h:44,
from /home/siat/rtabmap/corelib/src/../include/rtabmap/core/CameraRGBD.h:37,
from /home/siat/rtabmap/corelib/src/CameraRGBD.cpp:28:
/usr/include/ni/XnStatus.h:33:9: error: ‘XnUInt32’ does not name a type
typedef XnUInt32 XnStatus;
^