激光相机数据融合（5）--Gazebo仿真数据融合

这一节将用ROS+Gazebo 环境获取激光获取点云，并用PCL和OPENCV处理，源代码在：https://github.com/ZouCheng321/5_laser_camera_sim

 由于激光的视角远大于相机，所以我们使用了5个相机来获取图像,这类似于Ladybug相机：

相机获取的五张图像：

 

接下来我们用来构建彩色点云：

相机与激光的位置变换，由于是正五边形分别，这很容易求得：

  Eigen::Matrix4f rt0,rt1,rt2,rt3,rt4;
    rt0<< 0,0,-1,0,  0,1,0,0,  1,0,0,0, 0,0,0,1;
    rt1<< 0,0,-1,0,  -0.95105651629,0.30901699437,0,0,  0.30901699437,0.95105651629,0,0, 0,0,0,1;
    rt2 << 0,0,-1,0,  -0.58778525229,-0.80901699437,0,0,  -0.80901699437,0.58778525229,0,0, 0,0,0,1;
    rt3 << 0,0,-1,0,  0.58778525229,-0.80901699437,0,0,  -0.80901699437,-0.58778525229,0,0, 0,0,0,1;
    rt4 << 0,0,-1,0,  0.95105651629,0.30901699437,0,0,  0.30901699437,-0.95105651629,0,0, 0,0,0,1;
    Eigen::Matrix4f inv0,inv1,inv2,inv3,inv4;
    inv0=rt0.inverse();
    inv1=rt1.inverse();
    inv2=rt2.inverse();
    inv3=rt3.inverse();
    inv4=rt4.inverse();

    RT.push_back(rt0);
    RT.push_back(rt1);
    RT.push_back(rt2);
    RT.push_back(rt3);
    RT.push_back(rt4);

    INV.push_back(inv0);
    INV.push_back(inv1);
    INV.push_back(inv2);
    INV.push_back(inv3);
    INV.push_back(inv4);

相机的内参，已经在仿真软件中设定：

 std::vector imagePoints;

    cv::Mat intrisicMat(3, 3, cv::DataType<double>::type); // Intrisic matrix
    intrisicMat.at<double>(0, 0) = 476.715669286;
    intrisicMat.at<double>(1, 0) = 0;
    intrisicMat.at<double>(2, 0) = 0;

    intrisicMat.at<double>(0, 1) = 0;
    intrisicMat.at<double>(1, 1) = 476.715669286;
    intrisicMat.at<double>(2, 1) = 0;

    intrisicMat.at<double>(0, 2) = 400;
    intrisicMat.at<double>(1, 2) = 400;
    intrisicMat.at<double>(2, 2) = 1;



    cv::Mat rVec(3, 1, cv::DataType<double>::type); // Rotation vector
    rVec.at<double>(0) = 0;
    rVec.at<double>(1) = 0;
    rVec.at<double>(2) = 0;

    cv::Mat tVec(3, 1, cv::DataType<double>::type); // Translation vector
    tVec.at<double>(0) = 0.4;
    tVec.at<double>(1) = 0;
    tVec.at<double>(2) = -0.1;

    cv::Mat distCoeffs(5, 1, cv::DataType<double>::type);   // Distortion vector
    distCoeffs.at<double>(0) = 0;
    distCoeffs.at<double>(1) = 0;
    distCoeffs.at<double>(2) = 0;
    distCoeffs.at<double>(3) = 0;
    distCoeffs.at<double>(4) = 0;

去除相机后方的点云：

std::vector Generate3DPoints(pcl::PointCloud::Ptr cloud,int num)
{
    std::vector points;
    pcl::PointCloud::Ptr cloud_f (new pcl::PointCloud);

    Eigen::Matrix4f TR;
    TR << 0,0,-1,0,  0,1,0,0,  1,0,0,0, 0,0,0,1;
    pcl::transformPointCloud (*cloud, *cloud_f, RT[num]);

    pcl::PassThrough pass;
    pass.setInputCloud (cloud_f);
    pass.setFilterFieldName ("z");
    pass.setFilterLimits (0.0, 10);
    //pass.setFilterLimitsNegative (true);
    pass.filter (*cloud);
    cout<<"size:"<size()<<endl;



    for(int i=0;i<=cloud->points.size();i++)
    {
        points.push_back(cv::Point3d(cloud->points[i].x, cloud->points[i].y, cloud->points[i].z));
    }

    return points;
}

将前方的点云投影到相机平面，这里直接用opencv自带的projectPoints函数：

        cv::projectPoints(objectPoints, rVec, tVec, intrisicMat, distCoeffs, imagePoints);

保留图像内的点云：

 for(int i=0;i)
        {
            if(imagePoints[i].x>=0&&imagePoints[i].x<800&&imagePoints[i].y>=0&&imagePoints[i].y<800)
            {

                pcl::PointXYZRGB point;
                point.x = cloud->points[i].x;
                point.y = cloud->points[i].y;
                point.z = cloud->points[i].z;
                point.r = _I(round(imagePoints[i].x),round(imagePoints[i].y))[2];
                point.g = _I(round(imagePoints[i].x),round(imagePoints[i].y))[1];
                point.b = _I(round(imagePoints[i].x),round(imagePoints[i].y))[0];

                colored_cloud->points.push_back (point);
            }
        }

最后显示所有点云：

  pcl::visualization::PCLVisualizer viewer("Cloud viewer");
    viewer.addPointCloud(colored_cloud_sum, "sample cloud");
    viewer.setBackgroundColor(0,0,0);

    while(!viewer.wasStopped())
        //while (!viewer->wasStopped ())
        viewer.spinOnce(100);

要构建这个项目：

cd 5_laser_camera_sim
mkdir build
cd build
cmake ..
make
./color

将看到如下显示：

 

转载于:https://www.cnblogs.com/zoucheng/p/7867986.html