1 //创建一个模型参数对象，用于记录结果
 2 pcl::ModelCoefficients::Ptr coefficients(new pcl::ModelCoefficients);
 3 //inliers表示误差能容忍的点，记录点云序号
 4 pcl::PointIndices::Ptr inliers(new pcl::PointIndices);
 5 //创建一个分割器
 6 pcl::SACSegmentation<pcl::PointXYZ> seg;
 7 //Optional,设置结果平面展示的点是分割掉的点还是分割剩下的点
 8 seg.setOptimizeCoefficients(true);
 9 //Mandatory-设置目标几何形状
10 seg.setModelType(pcl::SACMODEL_PLANE);
11 //分割方法：随机采样法
12 seg.setMethodType(pcl::SAC_RANSAC);
13 //设置误差容忍范围，也就是阈值
14 seg.setDistanceThreshold(0.01);
15 //输入点云
16 seg.setInputCloud (cloud);
17 //分割点云
18 seg.segment (*inliers, *coefficients);

while ((iterNum < iter_maxNum) && inPlaneNum_max <= RSample_pointsNum)
{inPlaneNum_t = 3;//当前拟合平面中点个数//随机抽3个点，验证不在一条直线上/*A(x1,y1)、B(x2,y2)、C(x3,y3)AB斜率：kAB=(y2-y1)/(x2-x1)BC斜率：kBC=(y3-y2)/(x3-x2)计算结果可得：kAB=kBC因为kAB=kBC，且共点B所以直线AB与直线BC共线。*/do {rand_i_1 = real(gen);rand_i_2 = real(gen);if (rand_i_1 == rand_i_2)continue;rand_i_3 = real(gen);if (rand_i_1 == rand_i_3 || rand_i_2 == rand_i_3)continue;x1 = r_sample[rand_i_1].x; x2 = r_sample[rand_i_2].x; x3 = r_sample[rand_i_3].x;y1 = r_sample[rand_i_1].y; y2 = r_sample[rand_i_2].y; y3 = r_sample[rand_i_3].y;} while (((y2 - y1)*(x3 - x2)) == ((y3 - y2)*(x2 - x1)));//x1 = r_sample[rand_i_1].x; x2 = r_sample[rand_i_2].x; x3 = r_sample[rand_i_3].x;//y1 = r_sample[rand_i_1].y; y2 = r_sample[rand_i_2].y; y3 = r_sample[rand_i_3].y;z1 = r_sample[rand_i_1].z; z2 = r_sample[rand_i_2].z; z3 = r_sample[rand_i_3].z;//求平面方程A_t = (y2 - y1)*(z3 - z1) - (z2 - z1)*(y3 - y1);B_t = (x3 - x1)*(z2 - z1) - (x2 - x1)*(z3 - z1);C_t = (x2 - x1)*(y3 - y1) - (x3 - x1)*(y2 - y1);D_t = -(A_t * x1 + B_t * y1 + C_t * z1);//求在平面内的点的个数temp = sqrt(A_t*A_t + B_t*B_t + C_t*C_t);//点到平面距离参数for (int i = 0; i < RSample_pointsNum; i++){temp_D = abs(A_t*r_sample[i].x + B_t*r_sample[i].y + C_t*r_sample[i].z + D_t) / temp;//点到平面距离if (temp_D < maxD){inPlaneNum_t++;}}//与最优（最大）个数比较，保留最优个数的平面公式if (inPlaneNum_t > inPlaneNum_max){A_best = A_t;B_best = B_t;C_best = C_t;D_best = D_t;inPlaneNum_max = inPlaneNum_t;}iterNum++;//迭代次数+1
}