fitting.rar_matlab激光标定_平面标定_激光_线激光_线激光标定

%% 读取L1，L2中点的坐标进行平面拟合，求出平面方程参数 %12-18 clc; clear all; %% 读取点坐标 % L1 = load('Line1.mat'); % L2 = load('Line2.mat'); % % Data = [L1.L1 L2.L2];%两直线上的点 load('Data.mat');%平面上随机取点 Data = data; X = Data(1,:)'; Y = Data(2,:)'; Z = Data(3,:)'; %增加干扰噪音 Z = Z + randn(size(X)); %function [a,b,c] = fitting(X,Y,Z) %% 回归分析 % F = [X,Y,ones(size(X))]; % A = F\Z;%方程系数 % % fprintf('a = %f, b = %f ,c = %f \n',A(1),A(2),A(3)); % fprintf('z = %f*x + %f*y + %f \n',A(1),A(2),A(3)); % % % 求回归误差 % e = (A(1)*X + A(2)*Y +A(3)) -Z; %stem(1:202,e,'-'); %% 定义误差最大值，当点误差超过该范围则抛弃该点,再进行回归，直到误差值都属于允许范围内。 E = 1; flag = true; e = zeros(length(Data),1); while(flag) len = length(e); pointNumber = length(e);%回归分析使用的点数量 useful = ones(pointNumber,1);%标示每个点是否属于噪声 regress = false; %回归分析 F = [X,Y,ones(size(X))]; A = F\Z;%方程系数 fprintf('a = %f, b = %f ,c = %f \n',A(1),A(2),A(3)); fprintf('z = %f*x + %f*y + %f \n',A(1),A(2),A(3)); % 求回归误差 e = (A(1)*X + A(2)*Y +A(3)) -Z; for i = 1:len if(abs(e(i)) > E) pointNumber = pointNumber -1; useful(i) =0; regress = true;%存在噪声点，需要剔除该点再进行回归 end end if(regress == false) flag = false; break; else flag = true; end %过滤数据 newX = zeros(pointNumber,1); newY = zeros(pointNumber,1); newZ = zeros(pointNumber,1); count= 1; for j = 1:len if(useful(j) == 1) newX(count) = X(j); newY(count) = Y(j); newZ(count) = Z(j); count = count +1; else continue; end end X = zeros(pointNumber,1); Y = zeros(pointNumber,1); Z = zeros(pointNumber,1); X = newX; Y = newY; Z = newZ; e = zeros(pointNumber,1); end