ORB-SLAM2源码学习（一）——系统结构及System.cc

开始阅读学习ORB-SLAM2的源码了，在这里做个学习记录，另外也是督促自己的学习的更加深入。

前言

首先ORB-SLAM2作为一个完整的slam系统，作者即提供了论文也有对应的源码，它的github主页：

https://github.com/raulmur/ORB_SLAM2

系统包括了单目、双目、rgbd的实现，这里我主要学习单目slam系统，就以单目slam的流程来学习。

另外感谢泡泡机器人提供的有很好的注释版本（吴博）：

https://gitee.com/paopaoslam/ORB-SLAM2

一、系统结构

ORB-SLAM2系统的代码非常整齐，简洁，便于阅读，作者将项目做了良好的封装，文件分布如下：

其中src中为slam系统源码，Examples中为对应不同传感器的例程源码，Thirdparty存放的是用到的第三方库，Vocabulary存放的是回环检测中BoW用到的视觉词典；

首先，我们看看怎么来调用ORB-SLAM2，学习一下例程源码mono_tum.cc。

二、mono_tum.cc（单目tum数据集例程）

主体源码，做过修剪：

int main(int argc, char **argv)
{
    if(argc != 4)
    {
        cerr << endl << "Usage: ./mono_tum path_to_vocabulary path_to_settings path_to_sequence" << endl;
        return 1;
    }

    // Retrieve paths to images
    vector vstrImageFilenames;
    vector vTimestamps;
    string strFile = string(argv[3])+"/rgb.txt";
    LoadImages(strFile, vstrImageFilenames, vTimestamps);

    int nImages = vstrImageFilenames.size();

    // Create SLAM system. It initializes all system threads and gets ready to process frames.
    ORB_SLAM2::System SLAM(argv[1],argv[2],ORB_SLAM2::System::MONOCULAR,true);

    // Vector for tracking time statistics
    vector vTimesTrack;
    vTimesTrack.resize(nImages);

    cout << endl << "-------" << endl;
    cout << "Start processing sequence ..." << endl;
    cout << "Images in the sequence: " << nImages << endl << endl;

    // Main loop
    cv::Mat im;
    for(int ni=0; ni >(t2 - t1).count();

        vTimesTrack[ni]=ttrack;

        // Wait to load the next frame
        double T=0;
        if(ni0)
            T = tframe-vTimestamps[ni-1];

        if(ttrack

可以看到使用ORB-SLAM2系统对外接口为下流程：

1. 创建ORB_SLAM2::System对象 

   ORB_SLAM2::System SLAM(argv[1],argv[2],ORB_SLAM2::System::MONOCULAR,true);

    

2. 循环读取每一帧图片及其时间戳

   SLAM.TrackMonocular(im,tframe);

    

3. 关闭SLAM系统 

   SLAM.Shutdown();

    

4. 将相机轨线保存到硬盘中

SLAM.SaveKeyFrameTrajectoryTUM("KeyFrameTrajectory.txt");

eg：在我第一次尝试使用编译好的mono_tum时，想要使用自己的数据来跑跑ORB-SLAM2，但因为没有考虑到文件时间戳问题（当时文件命名就是自然数），于是程序帧数几乎一秒一帧，可以看到上面的代码里有一段 usleep((T-ttrack)*1e6)，这就是讲这个程序的运行速度和你提供的时间戳有关。

三、System.cc

在上面可以看到ORB-SLAM2系统的主入口通过System这个类定义的，这里来看下这个类的头文件。

class System
{
public:
    // Input sensor
    enum eSensor{
        MONOCULAR=0,
        STEREO=1,
        RGBD=2
    };

public:

    // Initialize the SLAM system. It launches the Local Mapping, Loop Closing and Viewer threads.
    System(const string &strVocFile, const string &strSettingsFile, const eSensor sensor, const bool bUseViewer = true);

    // Proccess the given stereo frame. Images must be synchronized and rectified.
    // Input images: RGB (CV_8UC3) or grayscale (CV_8U). RGB is converted to grayscale.
    // Returns the camera pose (empty if tracking fails).
    cv::Mat TrackStereo(const cv::Mat &imLeft, const cv::Mat &imRight, const double ×tamp);

    // Process the given rgbd frame. Depthmap must be registered to the RGB frame.
    // Input image: RGB (CV_8UC3) or grayscale (CV_8U). RGB is converted to grayscale.
    // Input depthmap: Float (CV_32F).
    // Returns the camera pose (empty if tracking fails).
    cv::Mat TrackRGBD(const cv::Mat &im, const cv::Mat &depthmap, const double ×tamp);

    // Proccess the given monocular frame
    // Input images: RGB (CV_8UC3) or grayscale (CV_8U). RGB is converted to grayscale.
    // Returns the camera pose (empty if tracking fails).
    cv::Mat TrackMonocular(const cv::Mat &im, const double ×tamp);

    // This stops local mapping thread (map building) and performs only camera tracking.
    void ActivateLocalizationMode();
    // This resumes local mapping thread and performs SLAM again.
    void DeactivateLocalizationMode();

    // Reset the system (clear map)
    void Reset();

    // All threads will be requested to finish.
    // It waits until all threads have finished.
    // This function must be called before saving the trajectory.
    void Shutdown();

    // Save camera trajectory in the TUM RGB-D dataset format.
    // Only for stereo and RGB-D. This method does not work for monocular.
    // Call first Shutdown()
    // See format details at: http://vision.in.tum.de/data/datasets/rgbd-dataset
    void SaveTrajectoryTUM(const string &filename);

    // Save keyframe poses in the TUM RGB-D dataset format.
    // This method works for all sensor input.
    // Call first Shutdown()
    // See format details at: http://vision.in.tum.de/data/datasets/rgbd-dataset
    void SaveKeyFrameTrajectoryTUM(const string &filename);

    // Save camera trajectory in the KITTI dataset format.
    // Only for stereo and RGB-D. This method does not work for monocular.
    // Call first Shutdown()
    // See format details at: http://www.cvlibs.net/datasets/kitti/eval_odometry.php
    void SaveTrajectoryKITTI(const string &filename);

    // TODO: Save/Load functions
    // SaveMap(const string &filename);
    // LoadMap(const string &filename);

private:

    // Input sensor
    eSensor mSensor;

    // ORB vocabulary used for place recognition and feature matching.
    ORBVocabulary* mpVocabulary;

    // KeyFrame database for place recognition (relocalization and loop detection).
    KeyFrameDatabase* mpKeyFrameDatabase;

    // Map structure that stores the pointers to all KeyFrames and MapPoints.
    Map* mpMap;

    // Tracker. It receives a frame and computes the associated camera pose.
    // It also decides when to insert a new keyframe, create some new MapPoints and
    // performs relocalization if tracking fails.
    Tracking* mpTracker;

    // Local Mapper. It manages the local map and performs local bundle adjustment.
    LocalMapping* mpLocalMapper;

    // Loop Closer. It searches loops with every new keyframe. If there is a loop it performs
    // a pose graph optimization and full bundle adjustment (in a new thread) afterwards.
    LoopClosing* mpLoopCloser;

    // The viewer draws the map and the current camera pose. It uses Pangolin.
    Viewer* mpViewer;

    FrameDrawer* mpFrameDrawer;
    MapDrawer* mpMapDrawer;

    // System threads: Local Mapping, Loop Closing, Viewer.
    // The Tracking thread "lives" in the main execution thread that creates the System object.
    std::thread* mptLocalMapping;
    std::thread* mptLoopClosing;
    std::thread* mptViewer;

    // Reset flag
    std::mutex mMutexReset;
    bool mbReset;

    // Change mode flags
    std::mutex mMutexMode;
    bool mbActivateLocalizationMode;
    bool mbDeactivateLocalizationMode;
};

类的成员有：

1. ORB词袋的对象 
2. 关键帧的数据库对象
3. 地图点数据对象 
4. Tracking对象 
5. Local Mapping对象 
6. Loop Closing对象

成员函数主要功能为：

1. 构造函数初始化具体slam系统
2. TrackMonocular将每一帧输入slam中进行处理

3. Shutdown停止slam线程

4. SaveKeyFrameTrajectoryTUM将关键帧位置做具体数据集格式的输出

接下来我们看看System.cc里的具体内容：

首先，System的构造函数里：

1. 系统参数设置文件读取
2. ORB词袋文件读取（txt或bin）
3. 成员的初始化

4. LocalMapping、LoopClosing、Viewer线程直接启动（Tracking线程实际是主线程）

其次TrackMonocular函数里：调用了tracking的GrabImageMonocular函数对每一帧进行处理；这里就进入了tracking模块，在之后我们再来学习Tracking.cc。

最后在Shutdown函数里关闭LocalMapping、LoopClosing、Viewer线程。