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Efficient algorithms for geometric optimization
 ACM Comput. Surv
, 1998
"... We review the recent progress in the design of efficient algorithms for various problems in geometric optimization. We present several techniques used to attack these problems, such as parametric searching, geometric alternatives to parametric searching, pruneandsearch techniques for linear progra ..."
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Cited by 114 (10 self)
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We review the recent progress in the design of efficient algorithms for various problems in geometric optimization. We present several techniques used to attack these problems, such as parametric searching, geometric alternatives to parametric searching, pruneandsearch techniques for linear programming and related problems, and LPtype problems and their efficient solution. We then describe a variety of applications of these and other techniques to numerous problems in geometric optimization, including facility location, proximity problems, statistical estimators and metrology, placement and intersection of polygons and polyhedra, and ray shooting and other querytype problems.
Arrangements and Their Applications
 Handbook of Computational Geometry
, 1998
"... The arrangement of a finite collection of geometric objects is the decomposition of the space into connected cells induced by them. We survey combinatorial and algorithmic properties of arrangements of arcs in the plane and of surface patches in higher dimensions. We present many applications of arr ..."
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Cited by 81 (17 self)
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The arrangement of a finite collection of geometric objects is the decomposition of the space into connected cells induced by them. We survey combinatorial and algorithmic properties of arrangements of arcs in the plane and of surface patches in higher dimensions. We present many applications of arrangements to problems in motion planning, visualization, range searching, molecular modeling, and geometric optimization. Some results involving planar arrangements of arcs have been presented in a companion chapter in this book, and are extended in this chapter to higher dimensions. Work by P.A. was supported by Army Research Office MURI grant DAAH049610013, by a Sloan fellowship, by an NYI award, and by a grant from the U.S.Israeli Binational Science Foundation. Work by M.S. was supported by NSF Grants CCR9122103 and CCR9311127, by a MaxPlanck Research Award, and by grants from the U.S.Israeli Binational Science Foundation, the Israel Science Fund administered by the Israeli Ac...
Differentially Constrained Mobile Robot Motion Planning in State Lattices
, 2008
"... We present an approach to the problem of differentially constrained mobile robot motion planning in arbitrary cost fields. The approach is based on deterministic search in a specially discretized state space. We compute a set of elementary motions that connects each discrete state value to a set of ..."
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Cited by 39 (4 self)
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We present an approach to the problem of differentially constrained mobile robot motion planning in arbitrary cost fields. The approach is based on deterministic search in a specially discretized state space. We compute a set of elementary motions that connects each discrete state value to a set of its reachable neighbors via feasible motions. Thus, this set of motions induces a connected search graph. The motions are carefully designed to terminate at discrete states, whose dimensions include relevant state variables (e.g., position, heading, curvature, and velocity). The discrete states, and thus the motions, repeat at regular intervals, forming a lattice. We ensure that all paths in the graph encode feasible motions via the imposition of continuity constraints on state variables at graph vertices and compliance of the graph edges with a differential equation comprising the vehicle model. The resulting state lattice permits fast full configuration space cost evaluation and collision detection. Experimental results with research prototype rovers demonstrate that the planner allows us to exploit the entire envelope of vehicle maneuverability in rough terrain, while featuring realtime performance. C ○ 2009 Wiley Periodicals, Inc. 1.
Rotational polygon containment and minimum enclosure using only robust 2D constructions
 Computational Geometry
, 1998
"... An algorithm and a robust floating point implementation is given for rotational polygon containment:given polygons P 1 ,P 2 ,P 3 ,...,P k and a container polygon C, find rotations and translations for the k polygons that place them into the container without overlapping. A version of the algorithm a ..."
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Cited by 36 (6 self)
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An algorithm and a robust floating point implementation is given for rotational polygon containment:given polygons P 1 ,P 2 ,P 3 ,...,P k and a container polygon C, find rotations and translations for the k polygons that place them into the container without overlapping. A version of the algorithm and implementation also solves rotational minimum enclosure: givenaclass C of container polygons, find a container C in C of minimum area for which containment has a solution. The minimum enclosure is approximate: it bounds the minimum area between (1epsilon)A and A. Experiments indicate that finding the minimum enclosure is practical for k = 2, 3 but not larger unless optimality is sacrificed or angles ranges are limited (although these solutions can still be useful). Important applications for these algorithm to industrial problems are discussed. The paper also gives practical algorithms and numerical techniques for robustly calculating polygon set intersection, Minkowski sum, and range in...
Largest Placement of One Convex Polygon inside Another
 Geom
, 1995
"... We show that the largest similar copy of a convex polygon P with m edges inside a convex polygon Q with n edges can be computed in O(mn 2 log n) time. We also show that the combinatorial complexity of the space of all similar copies of P inside Q is O(mn 2 ), and that it can also be computed in ..."
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Cited by 12 (3 self)
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We show that the largest similar copy of a convex polygon P with m edges inside a convex polygon Q with n edges can be computed in O(mn 2 log n) time. We also show that the combinatorial complexity of the space of all similar copies of P inside Q is O(mn 2 ), and that it can also be computed in O(mn 2 log n) time. Let P be a convex polygon with m edges and Q a convex polygon with n edges. Our goal is to find the largest similar copy of P inside Q (allowing translation, rotation, and scaling of P ); see Figure 1. A restricted version of this problem, in which we just determine whether P can be placed inside Q without scaling, was solved by Chazelle [4], in O(mn 2 ) time. See also [1, 6, 12] for other approaches to the more general problem, in which Q is an arbitrary polygonal region. (We remark that the complexity of the algorithms for the general case is considerably higher, about O(m 2 n 2 ) in [1], O(m 3 n 2 ) in [12], and O(m 4 n 2 ) in [6].) Problems concernin...
Randomized algorithms for geometric optimization problems
 Handbook of Randomized Computation
, 2001
"... This chapter reviews randomization algorithms developed in the last few years to solve a wide range of geometric optimization problems. We rst review a number of general techniques, including randomized binary search, randomized linearprogramming algorithms, and random sampling. Next, we describe s ..."
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Cited by 11 (0 self)
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This chapter reviews randomization algorithms developed in the last few years to solve a wide range of geometric optimization problems. We rst review a number of general techniques, including randomized binary search, randomized linearprogramming algorithms, and random sampling. Next, we describe several applications of these and other techniques, including facility location, proximity problems, statistical estimators, nearest neighbor searching, and Euclidean TSP.
Optimal, Smooth, Nonholonomic Mobile Robot Motion Planning in State Lattices
, 2007
"... We present an approach to the problem of mobile robot motion planning in arbitrary cost fields subject to differential constraints. Given a model of vehicle maneuverability, a trajectory generator solves the two point boundary value problem of connecting two points in state space with a feasible mot ..."
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Cited by 10 (6 self)
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We present an approach to the problem of mobile robot motion planning in arbitrary cost fields subject to differential constraints. Given a model of vehicle maneuverability, a trajectory generator solves the two point boundary value problem of connecting two points in state space with a feasible motion. We use this capacity to compute a control set which connects any state to its reachable neighbors in a limited neighborhood. Equivalence classes of paths are used to implement a path sampling policy which preserves expressiveness while eliminating redundancy. The implicit repetition of the resulting minimal control set throughout state space produces a reachability graph that encodes all feasible motions consistent with this sampling policy. The graph encodes only feasible motions by construction and, by appropriate choice of state space dimension, can permit full configuration space collision detection while imposing heading and curvature continuity constraints at nodes. Nonholonomic constraints are satisfied by construction in the trajectory generator. We also use the trajectory generator to compute an ideal admissible heuristic and significantly improve planning efficiency. Comparisons
On the union of κround objects in three and four dimensions
 Geom
, 2004
"... A compact set c in R d is κround if for every point p ∈ ∂c there exists a closed ball that contains p, is contained in c, and has radius κ diam c. We show that, for any fixed κ> 0, the combinatorial complexity of the union of n κround, not necessarily convex objects in R 3 (resp., in R 4) of co ..."
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Cited by 8 (5 self)
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A compact set c in R d is κround if for every point p ∈ ∂c there exists a closed ball that contains p, is contained in c, and has radius κ diam c. We show that, for any fixed κ> 0, the combinatorial complexity of the union of n κround, not necessarily convex objects in R 3 (resp., in R 4) of constant description complexity is O(n 2+ε) (resp., O(n 3+ε)) for any ε> 0, where the constant of proportionality depends on ε, κ, and the algebraic complexity of the objects. The bound is almost tight in the worst case. 1
Rotational Polygon Overlap Minimization
 Computational Geometry: Theory and Applications
, 1997
"... An effective and fast algorithm is given for rotational overlap minimization: given an overlapping layout of polygons P1 ; P2 ; P3 ; : : : ; Pk in a container polygon C, translate and rotate the polygons to a layout that minimizes an overlap measure. A (local) overlap minimum has the property that ..."
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Cited by 5 (1 self)
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An effective and fast algorithm is given for rotational overlap minimization: given an overlapping layout of polygons P1 ; P2 ; P3 ; : : : ; Pk in a container polygon C, translate and rotate the polygons to a layout that minimizes an overlap measure. A (local) overlap minimum has the property that any perturbation of the polygons increases the chosen measure of overlap. Experiments show that the algorithm works well in practice. It is shown how to apply overlap minimization to create algorithms for other layout tasks: compaction, containment, and minimal enclosure. Compaction: starting with a nonoverlapping layout in a rectangular container, plan a nonoverlapping motion that minimizes the length or area of the container. Containment: place the polygons into a (possibly nonconvex container) without overlapping. Minimal enclosure: find a nonoverlapping layout inside a minimumlength, fixedwidth rectangle or inside a minimum area rectangle. All of these algorithms have important i...