On the Complexity of the Union of Geometric Objects

Given a family C of regions bounded by simple closed curves in the plane, the complexity of their union is denned as the number of points along the boundary of ?C, which belong to more than one curve Similarly, one can define the complexity of the union of 3-dimensional bodies, as the number of points on the boundary of the union, belonging to the surfaces of at least three distinct members of the family. We survey some upper bounds on the complexity of the union of n geometric objects satisfying various natural conditions. These problems play a central role in the design and analysis of many geometric algorithms arising in motion planning and computer graphics.

[1]  J. Schwartz,et al.  On the “piano movers'” problem I. The case of a two‐dimensional rigid polygonal body moving amidst polygonal barriers , 1983 .

[2]  János Pach,et al.  Combinatorial Geometry , 2012 .

[3]  P. Erdös On extremal problems of graphs and generalized graphs , 1964 .

[4]  Leonidas J. Guibas,et al.  On arrangements of Jordan arcs with three intersections per pair , 2018, SCG '88.

[5]  Micha Sharir,et al.  Davenport-Schinzel sequences and their geometric applications , 1995, Handbook of Computational Geometry.

[6]  Micha Sharir,et al.  The upper envelope of piecewise linear functions and the boundary of a region enclosed by convex plates: Combinatorial analysis , 2011, Discret. Comput. Geom..

[7]  Micha Sharir,et al.  An efficient motion-planning algorithm for a convex polygonal object in two-dimensional polygonal space , 1990, Discret. Comput. Geom..

[8]  Deepak Kapur,et al.  Geometric reasoning , 1989 .

[9]  Micha Sharir,et al.  Nonlinearity of davenport—Schinzel sequences and of generalized path compression schemes , 1986, FOCS.

[10]  Leonidas J. Guibas,et al.  Combinatorics and Algorithms of Arrangements , 1993 .

[11]  Micha Sharir,et al.  Computing Depth Orders for Fat Objects and Related Problems , 1995, Comput. Geom..

[12]  Mariette Yvinec,et al.  Voronoi Diagrams in Higher Dimensions under Certain Polyhedral Distance Functions , 1998, Discret. Comput. Geom..

[13]  Gyula O. H. Katona On a problem of L. Fejes Tóth , 1977 .

[14]  János Pach,et al.  On the boundary complexity of the union of fat triangles , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[15]  Michiel H. M. Smid,et al.  A Technique for Adding Range Restrictions to Generalized Searching Problems , 1997, Inf. Process. Lett..

[16]  Marc J. van Kreveld On fat partitioning, fat covering and the union size of polygons , 1998, Comput. Geom..

[17]  Micha Sharir,et al.  On Translational Motion Planning of a Convex Polyhedron in 3-Space , 1997, SIAM J. Comput..

[18]  Tomás Lozano-Pérez,et al.  An algorithm for planning collision-free paths among polyhedral obstacles , 1979, CACM.

[19]  J. Pach,et al.  Combinatorial geometry , 1995, Wiley-Interscience series in discrete mathematics and optimization.

[20]  Micha Sharir,et al.  The union of congruent cubes in three dimensions , 2001, SCG '01.

[21]  P. McMullen,et al.  On the upper-bound conjecture for convex polytopes , 1971 .

[22]  Micha Sharir,et al.  Fat Triangles Determine Linearly Many Holes , 1994, SIAM J. Comput..

[23]  Micha Sharir,et al.  On the Complexity of the Union of Fat Convex Objects in the Plane , 2000, Discret. Comput. Geom..

[24]  Matthew J. Katz,et al.  On the union of k-curved objects , 1999, Comput. Geom..

[25]  Matthew J. Kaltz 3-D vertical ray shooting and 2-D point enclosure, range searching, and arc shooting amidst convex fat objects , 1997 .

[26]  Micha Sharir,et al.  Planar realizations of nonlinear davenport-schinzel sequences by segments , 1988, Discret. Comput. Geom..

[27]  Alon Efrat,et al.  The complexity of the union of (α, β)-covered objects , 1999, SCG '99.

[28]  Micha Sharir,et al.  Planning a purely translational motion for a convex object in two-dimensional space using generalized Voronoi diagrams , 2016, Discret. Comput. Geom..

[29]  Mark H. Overmars,et al.  Motion planning amidst fat obstacles (extended abstract) , 1994, SCG '94.

[30]  Micha Sharir,et al.  On the Number of Regular Vertices of the Union of Jordan Regions , 1998, SWAT.

[31]  M. Sharir,et al.  Pipes, Cigars, and Kreplach: the Union of Minkowski Sums in Three Dimensions , 2000 .

[32]  Mark de Berg,et al.  Realistic input models for geometric algorithms , 1997, SCG '97.

[33]  Ch. Chojnacki,et al.  Über wesentlich unplättbare Kurven im dreidimensionalen Raume , 1934 .

[34]  Micha Sharir,et al.  On the union of Jordan regions and collision-free translational motion amidst polygonal obstacles , 1986, Discret. Comput. Geom..

[35]  Thomas Ottmann,et al.  Algorithms for Reporting and Counting Geometric Intersections , 1979, IEEE Transactions on Computers.

[36]  W. T. Tutte Toward a theory of crossing numbers , 1970 .

[37]  J. Van Leeuwen,et al.  Handbook of theoretical computer science - Part A: Algorithms and complexity; Part B: Formal models and semantics , 1990 .

[38]  M. Sharir,et al.  New bounds for lower envelopes in three dimensions, with applications to visibility in terrains , 1993, SCG '93.

[39]  Leonidas J. Guibas,et al.  Combinatorial complexity bounds for arrangements of curves and spheres , 1990, Discret. Comput. Geom..

[40]  Mark H. Overmars,et al.  The Complexity of the Free Space for a Robot Moving Amidst Fat Obstacles , 1992, Comput. Geom..

[41]  M. Atallah Some dynamic computational geometry problems , 1985 .

[42]  Micha Sharir,et al.  On the Boundary of the Union of Planar Convex Sets , 1999, Discret. Comput. Geom..

[43]  Micha Sharir,et al.  Algorithmic motion planning in robotics , 1991, Computer.

[44]  Micha Sharir Almost tight upper bounds for lower envelopes in higher dimensions , 1994, Discret. Comput. Geom..

[45]  László Lovász,et al.  On Conway's Thrackle Conjecture , 1997 .

[46]  Micha Sharir,et al.  On the Union of Fat Wedges and Separating a Collection of Segments By a Line , 1993, Comput. Geom..

[47]  Micha Sharir,et al.  A Survey of Motion Planning and Related Geometric Algorithms , 1988, Artificial Intelligence.