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 <ros/ros.h>
#include <image_transport/image_transport.h>
#include <cv_bridge/cv_bridge.h>
#include <sensor_msgs/image_encodings.h>
#include <opencv2/imgproc/imgproc.hpp> //include the headers for OPENCV's image processing and GUI module
#include <opencv2/highgui/highgui.hpp>  //
 
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

 

posted @ 2017-04-19 14:24  徐尚  阅读(6864)  评论(0编辑  收藏  举报