117 lines
3.9 KiB
C++
117 lines
3.9 KiB
C++
/*
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* Software License Agreement (BSD License)
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*
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* Copyright (c) 2011-2014, Willow Garage, Inc.
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* Copyright (c) 2014-2016, Open Source Robotics Foundation
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* Copyright (c) 2016, Toyota Research Institute
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* All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above
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* copyright notice, this list of conditions and the following
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* disclaimer in the documentation and/or other materials provided
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* with the distribution.
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* * Neither the name of Open Source Robotics Foundation nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
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* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
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* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
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* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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* POSSIBILITY OF SUCH DAMAGE.
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*/
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/** @author Jeongseok Lee */
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#include <gtest/gtest.h>
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#include <Eigen/Core>
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#include <unsupported/Eigen/AutoDiff>
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#include "fcl/narrowphase/distance.h"
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using namespace fcl;
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//==============================================================================
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template <typename S>
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S getDistance(const Vector3<S>& p)
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{
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detail::GJKSolver_libccd<S> solver;
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S dist;
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Sphere<S> s1(20);
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Sphere<S> s2(10);
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Transform3<S> tf1 = Transform3<S>::Identity();
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Transform3<S> tf2 = Transform3<S>::Identity();
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tf2.translation() = p;
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solver.shapeDistance(s1, tf1, s2, tf2, &dist);
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return dist;
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}
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//==============================================================================
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template <typename S>
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void test_basic()
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{
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using derivative_t = Eigen::Matrix<S, 3, 1>;
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using scalar_t = Eigen::AutoDiffScalar<derivative_t>;
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using input_t = Eigen::Matrix<scalar_t, 3, 1>;
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input_t pos(40, 0, 0);
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pos(0).derivatives() = derivative_t::Unit(3, 0);
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pos(1).derivatives() = derivative_t::Unit(3, 1);
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pos(2).derivatives() = derivative_t::Unit(3, 2);
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auto dist = getDistance(pos);
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EXPECT_EQ(dist, (S)10);
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EXPECT_EQ(dist.value(), (S)10);
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EXPECT_EQ(dist.derivatives(), Vector3<S>(1, 0, 0));
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pos << 0, 40, 0;
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pos(0).derivatives() = derivative_t::Unit(3, 0);
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pos(1).derivatives() = derivative_t::Unit(3, 1);
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pos(2).derivatives() = derivative_t::Unit(3, 2);
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dist = getDistance(pos);
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EXPECT_EQ(dist, (S)10);
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EXPECT_EQ(dist.value(), (S)10);
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EXPECT_EQ(dist.derivatives(), Vector3<S>(0, 1, 0));
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pos << 0, 0, 40;
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pos(0).derivatives() = derivative_t::Unit(3, 0);
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pos(1).derivatives() = derivative_t::Unit(3, 1);
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pos(2).derivatives() = derivative_t::Unit(3, 2);
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dist = getDistance(pos);
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EXPECT_EQ(dist, (S)10);
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EXPECT_EQ(dist.value(), (S)10);
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EXPECT_EQ(dist.derivatives(), Vector3<S>(0, 0, 1));
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}
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//==============================================================================
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GTEST_TEST(FCL_AUTO_DIFF, basic)
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{
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// test_basic<float>();
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test_basic<double>();
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}
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//==============================================================================
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int main(int argc, char* argv[])
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{
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::testing::InitGoogleTest(&argc, argv);
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return RUN_ALL_TESTS();
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}
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