Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams

In the context of robotics, the grid-based Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent their surrounding area. Current approaches for incrementally constructing GVDs mainly focus on providing metric skeletons of underlying grids, while the connectivity among GVD...

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Main Authors: Long Qin, Quanjun Yin, Yabing Zha, Yong Peng
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/438576
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spelling doaj-982b88e1e1054752b9ba8434baff87772020-11-24T23:02:05ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/438576438576Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi DiagramsLong Qin0Quanjun Yin1Yabing Zha2Yong Peng3College of Information System and Management, National University of Defense Technology, Hunan, Changsha, 410073, ChinaCollege of Information System and Management, National University of Defense Technology, Hunan, Changsha, 410073, ChinaCollege of Information System and Management, National University of Defense Technology, Hunan, Changsha, 410073, ChinaCollege of Information System and Management, National University of Defense Technology, Hunan, Changsha, 410073, ChinaIn the context of robotics, the grid-based Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent their surrounding area. Current approaches for incrementally constructing GVDs mainly focus on providing metric skeletons of underlying grids, while the connectivity among GVD vertices and edges remains implicit, which makes high-level spatial reasoning tasks impractical. In this paper, we present an algorithm named Dynamic Topology Detector (DTD) for extracting a GVD with topological information from a grid map. Beyond the construction and reconstruction of a GVD on grids, DTD further extracts connectivity among the GVD edges and vertices. DTD also provides efficient repair mechanism to treat with local changes, making it work well in dynamic environments. Simulation tests in representative scenarios demonstrate that (1) compared with the static algorithms, DTD generally makes an order of magnitude improvement regarding computation times when working in dynamic environments; (2) with negligible extra computation, DTD detects topologies not computed by existing incremental algorithms. We also demonstrate the usefulness of the resulting topological information for high-level path planning tasks.http://dx.doi.org/10.1155/2013/438576
collection DOAJ
language English
format Article
sources DOAJ
author Long Qin
Quanjun Yin
Yabing Zha
Yong Peng
spellingShingle Long Qin
Quanjun Yin
Yabing Zha
Yong Peng
Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams
Mathematical Problems in Engineering
author_facet Long Qin
Quanjun Yin
Yabing Zha
Yong Peng
author_sort Long Qin
title Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams
title_short Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams
title_full Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams
title_fullStr Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams
title_full_unstemmed Dynamic Detection of Topological Information from Grid-Based Generalized Voronoi Diagrams
title_sort dynamic detection of topological information from grid-based generalized voronoi diagrams
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description In the context of robotics, the grid-based Generalized Voronoi Diagrams (GVDs) are widely used by mobile robots to represent their surrounding area. Current approaches for incrementally constructing GVDs mainly focus on providing metric skeletons of underlying grids, while the connectivity among GVD vertices and edges remains implicit, which makes high-level spatial reasoning tasks impractical. In this paper, we present an algorithm named Dynamic Topology Detector (DTD) for extracting a GVD with topological information from a grid map. Beyond the construction and reconstruction of a GVD on grids, DTD further extracts connectivity among the GVD edges and vertices. DTD also provides efficient repair mechanism to treat with local changes, making it work well in dynamic environments. Simulation tests in representative scenarios demonstrate that (1) compared with the static algorithms, DTD generally makes an order of magnitude improvement regarding computation times when working in dynamic environments; (2) with negligible extra computation, DTD detects topologies not computed by existing incremental algorithms. We also demonstrate the usefulness of the resulting topological information for high-level path planning tasks.
url http://dx.doi.org/10.1155/2013/438576
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AT quanjunyin dynamicdetectionoftopologicalinformationfromgridbasedgeneralizedvoronoidiagrams
AT yabingzha dynamicdetectionoftopologicalinformationfromgridbasedgeneralizedvoronoidiagrams
AT yongpeng dynamicdetectionoftopologicalinformationfromgridbasedgeneralizedvoronoidiagrams
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