ORB-SLAM跑通笔记本摄像头

环境：Ubuntu 14.04 + ROS indigo + ORB-SLAM2 (Thinkpad T460s)

1. 安装ORB-SLAM:

Pangolin

Pangolin有一些依赖库，按照提示安装好

git clone https://github.com/stevenlovegrove/Pangolin.git
cd Pangolin
mkdir build
cd build
cmake ..
make -j

OpenCV

2.4.8版本，2.4.11版本均可以用，3.2版本没有测试，应该也行

注意OpenCV兼容性经常出问题，包括头文件的路径各版本也有变化．

因此从source编译比较好，可以在电脑中编译好几个常用版本的OpenCV，以后想卸载，直接在build目录中sudo make uninstall即可，想安装，在build目录中sudo make install，这样切换不同版本还是比较快的．

Eigen

sudo apt-get install libeigen3-dev

Eigen是一个只有头文件的库，默认安装在/usr/include/eigen3/中，由于Eigen的位置经常有问题，导致CMakeLists.txt找不到这个库，因此ORB-SLAM提供了一个FindEigen3.cmake文件帮助寻找Eigen3，在自己的工程中也可以去使用这个文件来帮助寻找Eigen库的位置．

DBow和g2o

这两个库ORB-SLAM的Thirdparty目录中提供了，下载ORB-SLAM源代码后使用提供的脚本即可．

将ORB-SLAM安装在ROS的工作路径catkin_ws中，不理解ROS原理的需要去ROS官网把Beginner Level Tutorial看完．

cd catkin_ws/src
git clone https://github.com/raulmur/ORB_SLAM2.git

运行ORB-SLAM目录下的build.sh脚本:

cd ORB-SLAM2
./build.sh

// build.sh
echo "Configuring and building Thirdparty/DBoW2 ..."

cd Thirdparty/DBoW2
mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j

cd ../../g2o

echo "Configuring and building Thirdparty/g2o ..."

mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j

cd ../../../

echo "Uncompress vocabulary ..."

cd Vocabulary
tar -xf ORBvoc.txt.tar.gz
cd ..

echo "Configuring and building ORB_SLAM2 ..."

mkdir build
cd build
cmake .. -DCMAKE_BUILD_TYPE=Release
make -j

完成DBow，g2o，ORB-SLAM的编译，解压DBow字典文件．ORB-SLAM启动时，也需要载入这个100多M的文件，比较耗时．

2. 笔记本摄像头驱动安装和相机标定

1. 使用博世公司的　"usb_cam"：A ROS Driver for V4L USB Cameras

cd catkin_ws/src
git clone https://github.com/bosch-ros-pkg/usb_cam.git
cd ../
catkin_make

下载需要标定的黑白棋盘，打印后贴在平板上．

2. 编译ROS相机标定包

rosdep install camera_calibration
rosmake camera_calibration

3. 启动usb_cam，获取笔记本摄像头的图像

// sudo apt-get install ros-indigo-usb-cam optional 若没有安装usb_cam驱动时安装
roslaunch usb_cam usb-cam-test.launch

4. 启动标定程序

rosrun camera_calibration cameracalibrator.py --size 8x6 --square 0.025 image:=/usb_cam/image_raw camera:=/usb_cam

标定界面出现后，按照x（左右）、y（上下）、size（前后）、skew（倾斜）等方式移动棋盘，直到x,y,size,skew的进度条都变成绿色位置．

此时可以按下CALIBRATE按钮，等一段时间就可以完成标定。

完成后Commit，在终端后会有标定结果yaml文件地址．打开后，按照TUM1.yaml的格式修改，命名为mycam.yaml．复制到/home/shang/catkin_ws/src/ORB_SLAM2/Examples/Monocular/目录下

只是需要加上camera的尺寸Camera.width和Camera.height

我的T460s摄像头标定结果和ORB-SLAM参数是

%YAML:1.0

#--------------------------------------------------------------------------------------------
# Camera Parameters. Adjust them!
#--------------------------------------------------------------------------------------------

# Camera calibration and distortion parameters (OpenCV) 
Camera.fx: 626.3131886043523
Camera.fy: 624.0872390416225
Camera.cx: 280.8331825622062
Camera.cy: 234.9590765749035

Camera.k1: 0.1226796723026339
Camera.k2: -0.1753096021786491
Camera.p1: 0.003319071389844154
Camera.p2: -0.01267716347709299
Camera.k3: 0

Camera.width: 640
Camera.width: 480

# Camera frames per second 
Camera.fps: 30.0

# Color order of the images (0: BGR, 1: RGB. It is ignored if images are grayscale)
Camera.RGB: 1

#--------------------------------------------------------------------------------------------
# ORB Parameters
#--------------------------------------------------------------------------------------------

# ORB Extractor: Number of features per image
ORBextractor.nFeatures: 1000

# ORB Extractor: Scale factor between levels in the scale pyramid     
ORBextractor.scaleFactor: 1.2

# ORB Extractor: Number of levels in the scale pyramid    
ORBextractor.nLevels: 8

# ORB Extractor: Fast threshold
# Image is divided in a grid. At each cell FAST are extracted imposing a minimum response.
# Firstly we impose iniThFAST. If no corners are detected we impose a lower value minThFAST
# You can lower these values if your images have low contrast            
ORBextractor.iniThFAST: 20
ORBextractor.minThFAST: 7

#--------------------------------------------------------------------------------------------
# Viewer Parameters
#--------------------------------------------------------------------------------------------
Viewer.KeyFrameSize: 0.05
Viewer.KeyFrameLineWidth: 1
Viewer.GraphLineWidth: 0.9
Viewer.PointSize:2
Viewer.CameraSize: 0.08
Viewer.CameraLineWidth: 3
Viewer.ViewpointX: 0
Viewer.ViewpointY: -0.7
Viewer.ViewpointZ: -1.8
Viewer.ViewpointF: 500

３. 使用笔记本摄像头运行ORB-SLAM

至此，准备工作完成．

1. 将ORB-SLAM的ROS包路径添加到环境变量

export ROS_PACKAGE_PATH=${ROS_PACKAGE_PATH}:/home/shang/catkin_ws/ORB_SLAM2/Examples/ROS // you should change /home/shang/catkin_ws to your catkin workspace

2. 编译ORB-SLAM的ROS节点

cd src/ORB_SLAM2/Examples/ROS/ORB_SLAM2
mkdir build
cd build
cmake .. -DROS_BUILD_TYPE=Release
make -j

3. 这一步是最重要的！

ORB ROS节点订阅的topic和usb_cam发布的topic名称不同！

有两种方法，第一中较费事，但是可以帮助理解ROS的工作过程，第二种很简单，去ORB_SLAM中将其订阅的代码改掉，重新编译。

方法一：

编写自定义的ROS包，让ORB-SLAM的ROS节点订阅笔记本摄像头发布图像的topic

问题是，ORB-SLAM ROS节点订阅的topic为/camera/image_view，而笔记本摄像头图像流发布topic为/usb_cam/image_raw，这些可以通过rostopic list -v / rosnode list看到．

因此需要自己写一个ROS node程序，将这两个topic联合起来，我们选择自己重新定义一个ros packge

cd catkin_ws/src
catkin_create_pkg orb_image_transport image_transport cv_bridge
cd ..
catkin_make
cd orb_image_transport
gedit orb_image_converter.cpp

orb_image_converter.cpp文件负责将笔记本摄像头图像publish到一个topic，让ORB-SLAM订阅这个topic

#include 
#include 
#include 
#include 
#include  //include the headers for OPENCV's image processing and GUI module
#include   //
 
static const std::string OPENCV_WINDOW = "Image window";   //define show image gui
 
class ImageConverter
{
  ros::NodeHandle nh_;                    //define Nodehandle
  image_transport::ImageTransport it_;    //use this to create a publisher or subscriber
  image_transport::Subscriber image_sub_; //
  image_transport::Publisher image_pub_;
   
public:
  ImageConverter()
    : it_(nh_)
  {
    // Subscrive to input video feed and publish output video feed
    image_sub_ = it_.subscribe("/usb_cam/image_raw", 1,
      &ImageConverter::imageCb, this);
    //image_pub_ = it_.advertise("/image_converter/output_video", 1);
    image_pub_ = it_.advertise("/camera/image_raw", 1);
    cv::namedWindow(OPENCV_WINDOW);    //Opencv HighGUI calls to create/destroy a display window on start-up / shutdon
  }
 
  ~ImageConverter()
  {
    cv::destroyWindow(OPENCV_WINDOW);
  }
 
  void imageCb(const sensor_msgs::ImageConstPtr& msg)
  {
    cv_bridge::CvImagePtr cv_ptr;
    try
    {
      cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8);
    }
    catch (cv_bridge::Exception& e)
    {
      ROS_ERROR("cv_bridge exception: %s", e.what());
      return;
    }
    cv::imshow(OPENCV_WINDOW, cv_ptr->image);
    cv::waitKey(3);
     
    // Output modified video stream
    image_pub_.publish(cv_ptr->toImageMsg());
  }
};
 
int main(int argc, char** argv)
{
  ros::init(argc, argv, "image_converter");
  ImageConverter ic;
  ros::spin();
  return 0;
}

并在CMakeLists.txt文件最后添加

add_executable(orb_image_converter orb_image_converter.cpp)
target_link_libraries(orb_image_converter ${catkin_LIBRARIES} ${OpenCV_LIBRARIES})

catkin_make后就完成了所有的工作．

注意这里没有使用自定义的消息类型，不需要对Package.xml和CMakeLists.txt做别的改动．

最后一次运行就可以完成ORB-SLAM在笔记本摄像头上的运行

roslaunch usb_cam usb_cam-test.launch

rosrun orb_image_transport orb_image_converter

rosrun ORB_SLAM2 Mono /home/shang/catkin_ws/src/ORB_SLAM2/Vocabulary/ORBvoc.txt /home/shang/catkin_ws/src/ORB_SLAM2/Examples/Monocular/mycam.yaml // change /home/shang to your directory

也可以使用一个脚本运行所有的节点：

demo.sh

gnome-terminal -x bash -c "rosrun orb_image_transport orb_image_converter; exec $SHELL"

gnome-terminal -x bash -c "rosrun ORB_SLAM2 Mono /home/shang/catkin_ws/src/ORB_SLAM2/Vocabulary/ORBvoc.txt /home/shang/catkin_ws/src/ORB_SLAM2/Examples/Monocular/mycam.yaml
; exec $SHELL"

roslaunch usb_cam usb_cam-test.launch

直接运行./demo.sh即可完成

方法二：

后来发现这种方法太笨，在安装了博世的ROS摄像头驱动包usb_cam以后，摄像头的图像将发布到/usb_cam/image_raw，因此在ORB的代码中将其订阅的topic从/camera/image_raw改为/usb_cam/image_raw即可，在ROS目录下的ros_mono.cc文件中修改即可，双目，深度以及AR demo同理。

这样，只需要使用以下两条命令即可。

roslaunch usb_cam usb_cam-test.launch
rosrun ORB_SLAM2 Mono /home/shang/catkin_ws/src/ORB_SLAM2/Vocabulary/ORBvoc.txt /home/shang/catkin_ws/src/ORB_SLAM2/Examples/ROS/ORB_SLAM2/mycam.yaml

参考：

１．　http://www.jianshu.com/p/c3e8c88edb64

２．　http://www.cnblogs.com/li-yao7758258/p/5912663.html

ORB-SLAM跑通笔记本摄像头

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