激光SLAM学习分享--里程计标定

1.基于模型的方法--线性最小二乘法。

激光SLAM学习分享--里程计标定_第1张图片

激光SLAM学习分享--里程计标定_第2张图片

 激光SLAM学习分享--里程计标定_第3张图片激光SLAM学习分享--里程计标定_第4张图片

 2.代码实践

在odom_calib文件夹下打开终端,运行cmake . make进行编译,./odom_calib运行可执行文件。

激光SLAM学习分享--里程计标定_第5张图片

 激光SLAM学习分享--里程计标定_第6张图片

 3.代码展示。

odom_calib.cpp

#include 
#include 
#include 
#include 
#include 

#include 
#include 
#include 

using namespace std;

string scan_match_file = "./scan_match.txt"; //存放雷达数据的文件
string odom_file = "./odom.txt";  //存放轮速计数据的文件

int main(int argc, char** argv)
{
    // 放置激光雷达的时间和匹配值 t_s s_x s_y s_th
    
    vector> s_data;
    // 放置轮速计的时间和左右轮角速度 t_r w_L w_R
   
    vector> r_data;

    ifstream fin_s(scan_match_file);
    ifstream fin_r(odom_file);
    if (!fin_s || !fin_r)
    {
        cerr << "请在有scan_match.txt和odom.txt的目录下运行此程序" << endl;
        return 1;
    }

    // 读取激光雷达的匹配值
    while (!fin_s.eof()) {
        double s_t, s_x, s_y, s_th;
        fin_s >> s_t >> s_x >> s_y >> s_th;
        s_data.push_back(vector({s_t, s_x, s_y, s_th}));
    }
    fin_s.close();

    // 读取两个轮子的角速度
    while (!fin_r.eof()) {
        double t_r, w_L, w_R;
        fin_r >> t_r >> w_L >> w_R;
        r_data.push_back(vector({t_r, w_L, w_R}));
    }
    fin_r.close();

    // 第一步:计算中间变量J_21和J_22
    Eigen::MatrixXd A;
    Eigen::VectorXd b;
    // 设置数据长度
    A.conservativeResize(5000, 2);
    b.conservativeResize(5000);
    A.setZero();
    b.setZero();

    size_t id_r = 0;
    size_t id_s = 0;
    double last_rt = r_data[0][0];
    double w_Lt = 0;
    double w_Rt = 0;
    while (id_s < 5000)
    {
        // 激光的匹配信息
        const double &s_t = s_data[id_s][0];
        const double &s_th = s_data[id_s][3];
        // 里程计信息
        const double &r_t = r_data[id_r][0];
        const double &w_L = r_data[id_r][1];
        const double &w_R = r_data[id_r][2];
        ++id_r;
        // 在2帧激光匹配时间内进行里程计角度积分
        if (r_t < s_t)
        {
            double dt = r_t - last_rt;
            w_Lt += w_L * dt;
            w_Rt += w_R * dt;
            last_rt = r_t;
        }
        else
        {
            double dt = s_t - last_rt;
            w_Lt += w_L * dt;
            w_Rt += w_R * dt;
            last_rt = s_t;
            // 填充A, b矩阵
            A(id_s,0) = w_Lt;
            A(id_s,1) = w_Rt;
            b(id_s) = s_th;
            //TODO: (3~5 lines)
            //end of TODO
            w_Lt = 0;
            w_Rt = 0;
            ++id_s;
        }
    }
    // 进行最小二乘求解
    Eigen::Vector2d J21J22;
    //TODO: (1~2 lines)
    J21J22 = A.colPivHouseholderQr().solve(b);
    //end of TODO
    const double &J21 = J21J22(0);
    const double &J22 = J21J22(1);
    cout << "J21: " << J21 << endl;
    cout << "J22: " << J22 << endl;

    // 第二步,求解轮间距b
    Eigen::VectorXd C;
    Eigen::VectorXd S;
    // 设置数据长度
    C.conservativeResize(10000);
    S.conservativeResize(10000);
    C.setZero();
    S.setZero();

    id_r = 0;
    id_s = 0;
    last_rt = r_data[0][0];
    double th = 0;
    double cx = 0;
    double cy = 0;
    while (id_s < 5000)
    {
        // 激光的匹配信息
        const double &s_t = s_data[id_s][0];
        const double &s_x = s_data[id_s][1];
        const double &s_y = s_data[id_s][2];
        // 里程计信息
        const double &r_t = r_data[id_r][0];
        const double &w_L = r_data[id_r][1];
        const double &w_R = r_data[id_r][2];
        ++id_r;
        // 在2帧激光匹配时间内进行里程计位置积分
        if (r_t < s_t)
        {
            double dt = r_t - last_rt;
            cx += 0.5 * (-J21 * w_L * dt + J22 * w_R * dt) * cos(th);
            cy += 0.5 * (-J21 * w_L * dt + J22 * w_R * dt) * sin(th);
            th += (J21 * w_L + J22 * w_R) * dt;
            last_rt = r_t;
        }
        else
        {
            double dt = s_t - last_rt;
            cx += 0.5 * (-J21 * w_L * dt + J22 * w_R * dt) * cos(th);
            cy += 0.5 * (-J21 * w_L * dt + J22 * w_R * dt) * sin(th);
            th += (J21 * w_L + J22 * w_R) * dt;
            last_rt = s_t;
            // 填充C, S矩阵
            C(2*id_s) = cx;
            C(2*id_s+1) = cy;
            S(2*id_s) = s_x;
            S(2*id_s+1) = s_y;
            //TODO: (4~5 lines)
            //end of TODO
            cx = 0;
            cy = 0;
            th = 0;
            ++id_s;
        }
    }
    // 进行最小二乘求解,计算b, r_L, r_R
    double b_wheel;
    double r_L;
    double r_R;
    b_wheel = C.colPivHouseholderQr().solve(S)[0];
    r_L = -J21*b_wheel;
    r_R = J22*b_wheel;
    //TODO: (3~5 lines)
    //end of TODO
    cout << "b: " << b_wheel << endl;
    cout << "r_L: " << r_L << endl;
    cout << "r_R: " << r_R << endl;

    cout << "参考答案:轮间距b为0.6m左右,两轮半径为0.1m左右" << endl;

    return 0;
}

 CMakeLists.txt

cmake_minimum_required( VERSION 2.8 )
project( odom_calib )

set( CMAKE_CXX_COMPILER "g++" )
set( CMAKE_BUILD_TYPE "Release" )
set( CMAKE_CXX_FLAGS "-std=c++11 -march=native -O3" )
set( CMAKE_RUNTIME_OUTPUT_DIRECTORY ${PROJECT_SOURCE_DIR} )

include_directories( "/usr/include/eigen3" )

add_executable( odom_calib odom_calib.cpp )

 

 

 

你可能感兴趣的:(自动驾驶,算法,机器学习)