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Interval Routing Schemes for CircularArc Graphs
, 2012
"... Interval routing is a space efficient method to realize a distributed routing function. In this paper, we show that every circulararc graph allows a shortest path strict 2interval routing scheme, i.e., a routing function that only implies shortest paths can be realized in every circulararc graph, ..."
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Interval routing is a space efficient method to realize a distributed routing function. In this paper, we show that every circulararc graph allows a shortest path strict 2interval routing scheme, i.e., a routing function that only implies shortest paths can be realized in every circulararc graph
Efficient Algorithms for the Domination Problems on Interval and CircularArc Graphs
 SIAM J. Comput
, 1998
"... Abstract. This paper first presents a unified approach to design efficient algorithms for the weighted domination problem and its three variants, i.e., the weighted independent, connected, and total domination problems, on interval graphs. Given an interval model with endpoints sorted, these algorit ..."
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Cited by 14 (1 self)
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Abstract. This paper first presents a unified approach to design efficient algorithms for the weighted domination problem and its three variants, i.e., the weighted independent, connected, and total domination problems, on interval graphs. Given an interval model with endpoints sorted
Bounded, minimal, and short representations of unit interval and unit circulararc graphs
"... We consider the unrestricted, minimal, and bounded representation problems for unit interval (UIG) and unit circulararc (UCA) graphs. In the unrestricted version, a proper circulararc (PCA) modelM is given and the goal is to obtain an equivalent UCA model U. We show a linear time algorithm with ne ..."
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We consider the unrestricted, minimal, and bounded representation problems for unit interval (UIG) and unit circulararc (UCA) graphs. In the unrestricted version, a proper circulararc (PCA) modelM is given and the goal is to obtain an equivalent UCA model U. We show a linear time algorithm
Shape modeling with front propagation: A level set approach
 IEEE Transactions on Pattern Analysis and Machine Intelligence
, 1995
"... Abstract Shape modeling is an important constituent of computer vision as well as computer graphics research. Shape models aid the tasks of object representation and recognition. This paper presents a new approach to shape modeling which retains some of the attractive features of existing methods ..."
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Cited by 804 (20 self)
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Abstract Shape modeling is an important constituent of computer vision as well as computer graphics research. Shape models aid the tasks of object representation and recognition. This paper presents a new approach to shape modeling which retains some of the attractive features of existing methods
Optimal Distance Labeling for Interval and Circulararc Graphs
, 2003
"... In this paper we design a distance labeling scheme with O(log n) bit labels for interval graphs and circulararc graphs with n vertices. The set of all the labels is constructible in O(n) time if the interval representation of the graph is given and sorted. As a byproduct we give a new and simpl ..."
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Cited by 2 (0 self)
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and simpler O(n) space datastructure computable after O(n) preprocessing time, and supporting constant worstcase time distance queries for interval and circulararc graphs. These optimal bounds improve the previous scheme of Katz, Katz, and Peleg (STACS '00) by a log n factor. To the best of our
Robust Monte Carlo Localization for Mobile Robots
, 2001
"... Mobile robot localization is the problem of determining a robot's pose from sensor data. This article presents a family of probabilistic localization algorithms known as Monte Carlo Localization (MCL). MCL algorithms represent a robot's belief by a set of weighted hypotheses (samples), whi ..."
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Cited by 826 (88 self)
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to mobile robots equipped with range finders, a kernel density tree is learned that permits fast sampling. Systematic empirical results illustrate the robustness and computational efficiency of the approach.
Primitives for the manipulation of general subdivisions and the computations of Voronoi diagrams
 ACM Tmns. Graph
, 1985
"... The following problem is discussed: Given n points in the plane (the sites) and an arbitrary query point 4, find the site that is closest to q. This problem can be solved by constructing the Voronoi diagram of the given sites and then locating the query point in one of its regions. Two algorithms ar ..."
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Cited by 543 (11 self)
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The following problem is discussed: Given n points in the plane (the sites) and an arbitrary query point 4, find the site that is closest to q. This problem can be solved by constructing the Voronoi diagram of the given sites and then locating the query point in one of its regions. Two algorithms
Convex Analysis
, 1970
"... In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a lo ..."
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Cited by 5350 (67 self)
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In this book we aim to present, in a unified framework, a broad spectrum of mathematical theory that has grown in connection with the study of problems of optimization, equilibrium, control, and stability of linear and nonlinear systems. The title Variational Analysis reflects this breadth. For a
Planning Algorithms
, 2004
"... This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning ..."
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Cited by 1108 (51 self)
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This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensorbased planning, visibility, decisiontheoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.
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