3D Minkowski Sum of Polyhedra

Peter Hachenberger

The Minkowski sum of two point sets P and Q in ℝ^{d}, denoted by
P ⊕ Q, is defined as the set {p+q:p ∈ P, q ∈ Q
}. Minkowski sums are used in a wide range of applications such as
robot motion planning [Lat91] and computer-aided
design [EK99]. Figure 30.2 shows
an example how Minkowski sums can be used to plan the motion of a
translational robot. We want to know which are legal positions of the
robot, and where can the robot go to from a specified starting
position. If we model both the robot and the obstacles as a polyhedron
and compute the Minkowski sum of the inverted robot (robot reflected
at the origin) and the obstacles, then this Minkowski sum represents
all illegal positions of the robot, i.e., all positions where it
intersects the obstacle. Of course, the complement of that polyhedron
describes all legal positions of the robot, i.e., all positions where
it does not intersect an obstacle.

The Minkowski sum can be illustrated as follows. Pick an arbitrary reference point r of P (black dot in the lower left corner of the robot in Figure 30.2). Then place the inverted set -P on Q, such that -r is on the boundary of Q. Finally, move -P along the complete boundary of Q. The union of Q and the points swept by -P is the Minkowski sum of P and Q.

Implementing the Minkowski sum, the reference point does not need to be chosen. It is implicitly given as the origin of the coordinate system. Choosing a different reference point is equivalent to translating the coordinate system. Such a translation does not change the shape of the Minkowski sum; it only translates the Minkowski sum by the same vector.

This package provides a function *minkowski_sum_3* that computes
the Minkowski sum of two Nef polyhedra. We do not support arbitrary
Nef polyhedra, yet. The restrictions are discussed in detail in
Section 30.3.

The decomposition method for computing the Minkowski sum of non-convex polyhedra makes use of the fact that Minkowski sums of convex polyhedra are rather easy to compute. It decomposes both polyhedra into convex pieces, computes all pairwise Minkowski sums of the convex pieces, and merges the pairwise sums [dBvKOS97].

Minkowski sum are inherently complex to compute. Using the
decomposition method, each polyhedron might be divided into a
quadratic number of pieces, which is worst-case optimal. Then up to
n^{2}m^{2} pairwise sums have to be computed and merged, where n and
m are the complexities of the two input polyhedra (the complexity of
a *Nef_polyhedron_3* is the sum of its *Vertices*,
*Halfedges* and *SHalfedges*). In total the operation runs in
O(n^{3}m^{3}) time.

Since the computation of the Minkowski sum takes quite some time, we
give the running times of some Minkowski sum computations. They were
computed with Cgal 3.3 on a machine with a 2.4 GHz AMD Opteron
processor and 4 GB RAM. The code was compiled with
g++ 3.2 and compiler options -O2. The
*Nef_polyhedron_3* class was instantiated with the geometric
kernel *Homogeneous<leda_integer>*. The Minkowski sum of the spoon
and the star is illustrated in Figure 30.1.

model 1 | model 2 | running | ||||

name | facets | conv. pcs. | name | facets | conv. pcs. | time |

mushroom | 448 | 255 | cube | 6 | 1 | 204s |

mushroom | 448 | 255 | ball1 | 128 | 1 | 553s |

spoon | 336 | 186 | star | 24 | 5 | 882s |

cup | 1000 | 774 | ball2 | 1000 | 1 | 9851s |

This package was written to allow the computation of Minkowski sums of full-dimensional polyhedra even in so-called tight-passage scenarios. Tight passage scenarios occur in robot motion planning, when a robot is just as wide as a passage it needs to traverse. In these scenarios at least one polyhedron - the obstacles or the robot - must be modeled as an open set. Then the Minkowski sum will also be an open set and tight passages will occur as lower-dimensional exclusions, i.e., as facets, lines, or vertices that are, in contrast to the volume around them, not part of the resulting point set. Figure 30.2 shows such a tight passage scenario.

Our implementation uses *Nef_polyhedron_3* to model the input
polyhedra and the result polyhedron. An instance of
*Nef_polyhedron_3* represents a subdivision of the
three-dimensional space into vertices, edges, facets, and
volumes. Some of these items form the polyhedron (selected), while
others represent the outer volume or holes within the polyhedron
(unselected). As an example, the unit cube is the point set
[0,1]^{3}. The smallest subdivision that represents the unit cube has
8 vertices, 12 edges, 6 facets, and 2 volumes. The volumes enclosed by
the vertices, edges, and facets is the interior of the cube and
therefore selected. The volume outside the cube does not belong to it
and is therefore unselected. The vertices, edges, and facets - also
denoted as boundary items - are needed to separate the two volumes,
but are also useful for representing topological properties. In case
of the (closed) unit cube the boundary items are part of the
polyhedron and therefore selected, but in case of the open unit cube
[0,1)^{3} they are unselected. Each item has its own selection mark,
which allows the correct representation of Nef polyhedra, which are
closed under Boolean and topological operations. Details can be found
in the chapter on 3D Boolean operations on Nef polyhedra 28.

The use of *Nef_polyhedron_3* allows many scenarios beyond the
Minkowski sum of two solids. First, they can model the input and the
result of a tight passage scenario, i.e., they can model open and
closed solids as is needed for the input models, and they can model
tight passages, which are lower-dimensional exclusions represented as
unselected facets, edges, and vertices. We strive for extending the
package to work for arbitrary 3D Nef polyhedra. In addition to the
Minkowski sums of two solids, we added several features. At the moment
we allow an input polyhedron to consist of:

- singular vertices
- singular edges
- singular convex facets without holes
- surfaces with convex facets that have no holes.
- three-dimensional features, whose coplanar facets have common selection marks (this includes open and closed solids)

Taking a different viewpoint, the implementation is restricted as follows:

- The input polyhedra must be bounded (selected outer volume is ignored).
- All sets of coplanar facets of a full-dimensional feature must have the same selection mark (in case of different selection marks, unselected is assumed).
- All facets of lower-dimensional features need to be convex and must not have holes (non-convex facets and holes are ignored).

The second restriction might seem a bit odd. It stems from the fact that the Minkowski sum on convex polyhedra can only handle polyhedra, whose sides consist of a single facet. The decomposition process usually yields complex adjacency relations between a convex part, its adjacent convex parts, and the outer volume. The side of a convex piece is then decomposed into several facets, each of which represents one of these adjacency relations. For the convex Minkowski sum, we ignore the decompositions of the sides, but need to find a common selection mark. If there are two facets that are adjacent to the outer volume, but have different selections marks, we cannot set a common selection mark without spoiling the correctness of the Minkowski sum.

The function *minkowski_sum_3* should be used with the
*Exact_predicates_exact_constructions_kernel*, which often is
the most efficient choice and allows floating-point input. Consult
Section for more details.

The following example code illustrates the usage of the function
*minkowski_sum_3*. Note that either input polyhedra will be
modified by the function if it is non-convex. So, if they are needed
further on, they need to be copied, first. The copying is not done by
the function itself to keep the memory usage as small as possible.

File:examples/Minkowski_sum_3/cube_offset.cpp

#include <CGAL/Exact_predicates_exact_constructions_kernel.h> #include <CGAL/Nef_polyhedron_3.h> #include <CGAL/IO/Nef_polyhedron_iostream_3.h> #include <CGAL/minkowski_sum_3.h> #include <fstream> #include <iostream> typedef CGAL::Exact_predicates_exact_constructions_kernel Kernel; typedef CGAL::Nef_polyhedron_3<Kernel> Nef_polyhedron; int main() { Nef_polyhedron N0, N1; std::ifstream in("cube.nef3"); in >> N0; std::cin >> N1; Nef_polyhedron result = CGAL::minkowski_sum_3(N0, N1); }

With the function *minkowski_sum_3* it is also possible to realize
other interesting geometric operations like the glide operation, which
computes the point set swept by a polyhedron that moves along a
polygonal path. The following example shows how to construct a
polygonal path and then compute the glide operation by calling the
function *minkowski_sum_3*.

File:examples/Minkowski_sum_3/glide.cpp

#include <CGAL/Exact_predicates_exact_constructions_kernel.h> #include <CGAL/Nef_polyhedron_3.h> #include <CGAL/IO/Nef_polyhedron_iostream_3.h> #include <CGAL/minkowski_sum_3.h> #include <iostream> typedef CGAL::Exact_predicates_exact_constructions_kernel Kernel; typedef CGAL::Nef_polyhedron_3<Kernel> Nef_polyhedron; typedef Kernel::Point_3 Point_3; typedef Point_3* point_iterator; typedef std::pair<point_iterator,point_iterator> point_range; typedef std::list<point_range> polyline; int main(int argc, char* argv[]) { Nef_polyhedron N0; std::cin >> N0; Point_3 pl[6] = {Point_3(-100,0,0), Point_3(40,-70,0), Point_3(40,50,40), Point_3(-90,-60,60), Point_3(0, 0, -100), Point_3(30,0,150) }; polyline poly; poly.push_back(point_range(pl,pl+6)); Nef_polyhedron N1(poly.begin(), poly.end(), Nef_polyhedron::Polylines_tag()); Nef_polyhedron result = CGAL::minkowski_sum_3(N0, N1); }

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CGAL Open Source Project.
Release 3.9.
26 September 2011.