Directory: | ./ |
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File: | src/BV/kDOP.cpp |
Date: | 2025-04-01 09:23:31 |
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1 | /* | ||
2 | * Software License Agreement (BSD License) | ||
3 | * | ||
4 | * Copyright (c) 2011-2014, Willow Garage, Inc. | ||
5 | * Copyright (c) 2014-2015, Open Source Robotics Foundation | ||
6 | * All rights reserved. | ||
7 | * | ||
8 | * Redistribution and use in source and binary forms, with or without | ||
9 | * modification, are permitted provided that the following conditions | ||
10 | * are met: | ||
11 | * | ||
12 | * * Redistributions of source code must retain the above copyright | ||
13 | * notice, this list of conditions and the following disclaimer. | ||
14 | * * Redistributions in binary form must reproduce the above | ||
15 | * copyright notice, this list of conditions and the following | ||
16 | * disclaimer in the documentation and/or other materials provided | ||
17 | * with the distribution. | ||
18 | * * Neither the name of Open Source Robotics Foundation nor the names of its | ||
19 | * contributors may be used to endorse or promote products derived | ||
20 | * from this software without specific prior written permission. | ||
21 | * | ||
22 | * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS | ||
23 | * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT | ||
24 | * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS | ||
25 | * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE | ||
26 | * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, | ||
27 | * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, | ||
28 | * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; | ||
29 | * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER | ||
30 | * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT | ||
31 | * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN | ||
32 | * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE | ||
33 | * POSSIBILITY OF SUCH DAMAGE. | ||
34 | */ | ||
35 | |||
36 | /** \author Jia Pan */ | ||
37 | |||
38 | #include "coal/collision_data.h" | ||
39 | #include "coal/BV/kDOP.h" | ||
40 | |||
41 | #include <limits> | ||
42 | #include <iostream> | ||
43 | |||
44 | namespace coal { | ||
45 | |||
46 | /// @brief Find the smaller and larger one of two values | ||
47 | ✗ | inline void minmax(Scalar a, Scalar b, Scalar& minv, Scalar& maxv) { | |
48 | ✗ | if (a > b) { | |
49 | ✗ | minv = b; | |
50 | ✗ | maxv = a; | |
51 | } else { | ||
52 | ✗ | minv = a; | |
53 | ✗ | maxv = b; | |
54 | } | ||
55 | } | ||
56 | /// @brief Merge the interval [minv, maxv] and value p/ | ||
57 | 90674648 | inline void minmax(Scalar p, Scalar& minv, Scalar& maxv) { | |
58 |
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90674648 | if (p > maxv) maxv = p; |
59 |
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90674648 | if (p < minv) minv = p; |
60 | 90674648 | } | |
61 | |||
62 | /// @brief Compute the distances to planes with normals from KDOP vectors except | ||
63 | /// those of AABB face planes | ||
64 | template <short N> | ||
65 | void getDistances(const Vec3s& /*p*/, Scalar* /*d*/) {} | ||
66 | |||
67 | /// @brief Specification of getDistances | ||
68 | template <> | ||
69 | 3126712 | inline void getDistances<5>(const Vec3s& p, Scalar* d) { | |
70 | 3126712 | d[0] = p[0] + p[1]; | |
71 | 3126712 | d[1] = p[0] + p[2]; | |
72 | 3126712 | d[2] = p[1] + p[2]; | |
73 | 3126712 | d[3] = p[0] - p[1]; | |
74 | 3126712 | d[4] = p[0] - p[2]; | |
75 | 3126712 | } | |
76 | |||
77 | template <> | ||
78 | 3126712 | inline void getDistances<6>(const Vec3s& p, Scalar* d) { | |
79 | 3126712 | d[0] = p[0] + p[1]; | |
80 | 3126712 | d[1] = p[0] + p[2]; | |
81 | 3126712 | d[2] = p[1] + p[2]; | |
82 | 3126712 | d[3] = p[0] - p[1]; | |
83 | 3126712 | d[4] = p[0] - p[2]; | |
84 | 3126712 | d[5] = p[1] - p[2]; | |
85 | 3126712 | } | |
86 | |||
87 | template <> | ||
88 | 3126712 | inline void getDistances<9>(const Vec3s& p, Scalar* d) { | |
89 | 3126712 | d[0] = p[0] + p[1]; | |
90 | 3126712 | d[1] = p[0] + p[2]; | |
91 | 3126712 | d[2] = p[1] + p[2]; | |
92 | 3126712 | d[3] = p[0] - p[1]; | |
93 | 3126712 | d[4] = p[0] - p[2]; | |
94 | 3126712 | d[5] = p[1] - p[2]; | |
95 | 3126712 | d[6] = p[0] + p[1] - p[2]; | |
96 | 3126712 | d[7] = p[0] + p[2] - p[1]; | |
97 | 3126712 | d[8] = p[1] + p[2] - p[0]; | |
98 | 3126712 | } | |
99 | |||
100 | template <short N> | ||
101 | 1681932 | KDOP<N>::KDOP() { | |
102 | 1681932 | Scalar real_max = (std::numeric_limits<Scalar>::max)(); | |
103 |
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1681932 | dist_.template head<N / 2>().setConstant(real_max); |
104 |
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1681932 | dist_.template tail<N / 2>().setConstant(-real_max); |
105 | 1681932 | } | |
106 | |||
107 | template <short N> | ||
108 | ✗ | KDOP<N>::KDOP(const Vec3s& v) { | |
109 | ✗ | for (short i = 0; i < 3; ++i) { | |
110 | ✗ | dist_[i] = dist_[N / 2 + i] = v[i]; | |
111 | } | ||
112 | |||
113 | Scalar d[(N - 6) / 2]; | ||
114 | ✗ | getDistances<(N - 6) / 2>(v, d); | |
115 | ✗ | for (short i = 0; i < (N - 6) / 2; ++i) { | |
116 | ✗ | dist_[3 + i] = dist_[3 + i + N / 2] = d[i]; | |
117 | } | ||
118 | } | ||
119 | |||
120 | template <short N> | ||
121 | ✗ | KDOP<N>::KDOP(const Vec3s& a, const Vec3s& b) { | |
122 | ✗ | for (short i = 0; i < 3; ++i) { | |
123 | ✗ | minmax(a[i], b[i], dist_[i], dist_[i + N / 2]); | |
124 | } | ||
125 | |||
126 | Scalar ad[(N - 6) / 2], bd[(N - 6) / 2]; | ||
127 | ✗ | getDistances<(N - 6) / 2>(a, ad); | |
128 | ✗ | getDistances<(N - 6) / 2>(b, bd); | |
129 | ✗ | for (short i = 0; i < (N - 6) / 2; ++i) { | |
130 | ✗ | minmax(ad[i], bd[i], dist_[3 + i], dist_[3 + i + N / 2]); | |
131 | } | ||
132 | } | ||
133 | |||
134 | template <short N> | ||
135 | ✗ | bool KDOP<N>::overlap(const KDOP<N>& other) const { | |
136 | ✗ | if ((dist_.template head<N / 2>() > other.dist_.template tail<N / 2>()).any()) | |
137 | ✗ | return false; | |
138 | ✗ | if ((dist_.template tail<N / 2>() < other.dist_.template head<N / 2>()).any()) | |
139 | ✗ | return false; | |
140 | ✗ | return true; | |
141 | } | ||
142 | |||
143 | template <short N> | ||
144 | 41454528 | bool KDOP<N>::overlap(const KDOP<N>& other, const CollisionRequest& request, | |
145 | Scalar& sqrDistLowerBound) const { | ||
146 | 41454528 | const Scalar breakDistance(request.break_distance + request.security_margin); | |
147 | |||
148 |
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41454528 | Scalar a = (dist_.template head<N / 2>() - other.dist_.template tail<N / 2>()) |
149 |
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41454528 | .minCoeff(); |
150 |
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41454528 | if (a > breakDistance) { |
151 | 17488 | sqrDistLowerBound = a * a; | |
152 | 17488 | return false; | |
153 | } | ||
154 | |||
155 |
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41437040 | Scalar b = (other.dist_.template head<N / 2>() - dist_.template tail<N / 2>()) |
156 |
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41437040 | .minCoeff(); |
157 |
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41437040 | if (b > breakDistance) { |
158 | 32230 | sqrDistLowerBound = b * b; | |
159 | 32230 | return false; | |
160 | } | ||
161 | |||
162 | 41404810 | sqrDistLowerBound = std::min(a, b); | |
163 | 41404810 | return true; | |
164 | } | ||
165 | |||
166 | template <short N> | ||
167 | ✗ | bool KDOP<N>::inside(const Vec3s& p) const { | |
168 | ✗ | if ((p.array() < dist_.template head<3>()).any()) return false; | |
169 | ✗ | if ((p.array() > dist_.template segment<3>(N / 2)).any()) return false; | |
170 | |||
171 | enum { P = ((N - 6) / 2) }; | ||
172 | ✗ | Eigen::Array<Scalar, P, 1> d; | |
173 | ✗ | getDistances<P>(p, d.data()); | |
174 | |||
175 | ✗ | if ((d < dist_.template segment<P>(3)).any()) return false; | |
176 | ✗ | if ((d > dist_.template segment<P>(3 + N / 2)).any()) return false; | |
177 | |||
178 | ✗ | return true; | |
179 | } | ||
180 | |||
181 | template <short N> | ||
182 | 18760272 | KDOP<N>& KDOP<N>::operator+=(const Vec3s& p) { | |
183 |
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75041088 | for (short i = 0; i < 3; ++i) { |
184 |
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56280816 | minmax(p[i], dist_[i], dist_[N / 2 + i]); |
185 | } | ||
186 | |||
187 | Scalar pd[(N - 6) / 2]; | ||
188 |
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18760272 | getDistances<(N - 6) / 2>(p, pd); |
189 |
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143828752 | for (short i = 0; i < (N - 6) / 2; ++i) { |
190 |
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125068480 | minmax(pd[i], dist_[3 + i], dist_[3 + N / 2 + i]); |
191 | } | ||
192 | |||
193 | 18760272 | return *this; | |
194 | } | ||
195 | |||
196 | template <short N> | ||
197 | 39222 | KDOP<N>& KDOP<N>::operator+=(const KDOP<N>& other) { | |
198 |
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418368 | for (short i = 0; i < N / 2; ++i) { |
199 | 379146 | dist_[i] = std::min(other.dist_[i], dist_[i]); | |
200 | 379146 | dist_[i + N / 2] = std::max(other.dist_[i + N / 2], dist_[i + N / 2]); | |
201 | } | ||
202 | 39222 | return *this; | |
203 | } | ||
204 | |||
205 | template <short N> | ||
206 | 39222 | KDOP<N> KDOP<N>::operator+(const KDOP<N>& other) const { | |
207 |
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39222 | KDOP<N> res(*this); |
208 |
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78444 | return res += other; |
209 | } | ||
210 | |||
211 | template <short N> | ||
212 | ✗ | Scalar KDOP<N>::distance(const KDOP<N>& /*other*/, Vec3s* /*P*/, | |
213 | Vec3s* /*Q*/) const { | ||
214 | ✗ | std::cerr << "KDOP distance not implemented!" << std::endl; | |
215 | ✗ | return 0.0; | |
216 | } | ||
217 | |||
218 | template <short N> | ||
219 | ✗ | KDOP<N> translate(const KDOP<N>& bv, const Vec3s& t) { | |
220 | ✗ | KDOP<N> res(bv); | |
221 | ✗ | for (short i = 0; i < 3; ++i) { | |
222 | ✗ | res.dist(i) += t[i]; | |
223 | ✗ | res.dist(short(N / 2 + i)) += t[i]; | |
224 | } | ||
225 | |||
226 | Scalar d[(N - 6) / 2]; | ||
227 | ✗ | getDistances<(N - 6) / 2>(t, d); | |
228 | ✗ | for (short i = 0; i < (N - 6) / 2; ++i) { | |
229 | ✗ | res.dist(short(3 + i)) += d[i]; | |
230 | ✗ | res.dist(short(3 + i + N / 2)) += d[i]; | |
231 | } | ||
232 | |||
233 | ✗ | return res; | |
234 | } | ||
235 | |||
236 | template class KDOP<16>; | ||
237 | template class KDOP<18>; | ||
238 | template class KDOP<24>; | ||
239 | |||
240 | template KDOP<16> translate<16>(const KDOP<16>&, const Vec3s&); | ||
241 | template KDOP<18> translate<18>(const KDOP<18>&, const Vec3s&); | ||
242 | template KDOP<24> translate<24>(const KDOP<24>&, const Vec3s&); | ||
243 | |||
244 | } // namespace coal | ||
245 |