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optimizeCost.m
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optimizeCost.m
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%{
* 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, [email protected]. 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
* ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
* (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
* SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
* The views and conclusions contained in the software and documentation are those
* of the authors and should not be interpreted as representing official policies,
* either expressed or implied, of the Regents of The University of Michigan.
*
* AUTHOR: Bruce JK Huang (bjhuang[at]umich.edu)
* WEBSITE: https://www.brucerobot.com/
%}
function opt = optimizeCost(opt, X, target_size, box_width)
R_init = rotx(opt.rpy_init(1)) * roty(opt.rpy_init(2)) * rotz(opt.rpy_init(3));
opt.H_init(1:3, 1:3) = R_init;
if opt.UseCentroid
centroid = mean(X, 2);
opt.H_init(1:3, 4) = -centroid(1:3);
else
opt.H_init(1:3, 4) = opt.T_init;
end
switch opt.method
case 'Customize'
opt.metric = "PointToAxis";
opt.unit = "L1-inspired";
tic;
optimizeCustomizedCost(opt);
opt.computation_time = toc;
case 'Constraint Customize'
opt.metric = "PointToAxis";
opt.unit = "L1-inspired";
tic;
opt = optimizeConstraintCustomizedCost(opt, X, target_size, box_width);
opt.computation_time = toc;
case 'The Wall'
opt.metric = "PointToAxis";
opt.unit = "L1-inspired";
tic;
opt = optimizeBoundaries(opt, opts, X);
opt.computation_time = toc;
case 'Coherent Point Drift'
opt.metric = "--";
opt.unit = "RMSE";
tic;
optimizeCPD(opt);
opt.computation_time = toc;
case 'Iterative Closest Point (point)'
opt.metric = "PointToPoint";
opt.unit = "RMSE";
tic;
optimizeICPPoint(opt);
opt.computation_time = toc;
case 'Iterative Closest Point (plane)'
opt.metric = "PointToPlane";
opt.unit = "RMSE";
tic;
optimizeICPPlane(opt);
opt.computation_time = toc;
case 'Normal-distributions Transform'
opt.metric = "--";
opt.unit = "RMSE";
tic;
optimizeNDT(opt);
opt.computation_time = toc;
case 'GICP-SE3'
tic;
optimizeGICP_SE3(opt)
opt.computation_time = toc;
case 'GICP-SE3 (plane)'
tic;
optimizeGICPPlane_SE3(opt)
opt.computation_time = toc;
case 'GICP-SE3-costimized'
tic;
optimizeCustomizedGICP_SE3(opt);
opt.computation_time = toc;
case 'Two Hollow Strips'
tic;
optimizeHollowStrips(opt);
opt.computation_time = toc;
case '3D IoU'
case 'Project'
tic;
OptimizeUsingRobustNormalVector(opt);
opt.computation_time = toc;
otherwise
disp('no such optimization method')
return
end
end