genGriddedPoints.m

%{
 * Copyright (C) 2020-2030, The Regents of The University of Michigan.
 * All rights reserved.
 * This software was developed in the Biped Lab (https://www.biped.solutions/) 
 * under the direction of Jessy Grizzle, grizzle@umich.edu. This software may 
 * be available under alternative licensing terms; contact the address above.
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 1. Redistributions of source code must retain the above copyright notice, this
 *    list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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 * 
 * AUTHOR: Bruce JK Huang (bjhuang[at]umich.edu)
 * WEBSITE: https://www.brucerobot.com/
%}


function [x,y,z] = genGriddedPoints(app)
    % contruct grid on the target frame
    %             n = ceil(sqrt(app.num_points_target));
    %             y = linspace(0, app.target_len_, n);
    %             z = linspace(0, app.target_len_, n);
    %             app.noise_free_points_ = zeros(4, n^2); % x
    %
    %             for i = 1:n
    %                 for j = 1:n
    %                     app.noise_free_points_(2,(i-1)*n + j) = y(j) - app.target_len_/2;
    %                     app.noise_free_points_(3,(i-1)*n + j) = z(i) - app.target_len_/2;
    %                 end
    %             end
    n = ceil(sqrt(app.num_points_target));
    [y, z] = genGrid(app, n, app.target_len_);
    app.noise_free_points_ = zeros(4, n^2); % x
    app.noise_free_points_(2,:) = y;
    app.noise_free_points_(3,:) = z;
    app.noise_free_points_(4,:) = ones(1 ,n^2);

    % mimic LiDAR's performance
    rand_z = getNoise(app, 0, app.noise_sigma_(3), n^2); % ring
    rand_y = getNoise(app, 0, app.noise_sigma_(2), n^2); % noise on ring
    rand_x = getNoise(app, 0, app.noise_sigma_(1), n^2); % noise on depth

    % noisy data
    z = app.noise_free_points_(3,:) + rand_z;
    y = app.noise_free_points_(2,:) + rand_y;
    x = app.noise_free_points_(1,:) + rand_x;
end