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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Online Access: | http://dx.doi.org/10.1155/2013/438576 |
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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 |
work_keys_str_mv |
AT longqin dynamicdetectionoftopologicalinformationfromgridbasedgeneralizedvoronoidiagrams AT quanjunyin dynamicdetectionoftopologicalinformationfromgridbasedgeneralizedvoronoidiagrams AT yabingzha dynamicdetectionoftopologicalinformationfromgridbasedgeneralizedvoronoidiagrams AT yongpeng dynamicdetectionoftopologicalinformationfromgridbasedgeneralizedvoronoidiagrams |
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1725637486140456960 |