Publication detail
Narrow passage identification using cell decomposition approximation and minimum spanning tree
ABBADI, A. MATOUŠEK, R. KNISPEL, L.
Czech title
Identifikace "narrow passage" s využitím aproximativní dekompozice prostoru a minimální kostry grafu
English title
Narrow passage identification using cell decomposition approximation and minimum spanning tree
Type
journal article in Scopus
Language
en
Original abstract
Narrow passage problem is a problematic issue facing the sampling-based motion planner. In this paper, a new approach for narrow areas identification is proposed. The quad-tree cell-decomposition approximation is used to divide the free workspace into smaller cells, and build a graph of adjacency for these. The proposed method follows the graph edges and finds a sequence of cells, which have the same size, preceded and followed by a bigger cell size. The sequence, which has the pattern bigger-smaller-bigger cells size, is more likely to be located in a narrow area. The minimum spanning tree algorithm is used, to linearize adjacency graph. Many methods have been proposed to manipulate the edges cost in the graph, in order to make the generated spanning tree traverse through narrow passages in detectable ways. Five methods have been proposed, some of them give bad results, and the others give better on in simulations
Czech abstract
Narrow passage problem is a problematic issue facing the sampling-based motion planner. In this paper, a new approach for narrow areas identification is proposed. The quad-tree cell-decomposition approximation is used to divide the free workspace into smaller cells, and build a graph of adjacency for these. The proposed method follows the graph edges and finds a sequence of cells, which have the same size, preceded and followed by a bigger cell size. The sequence, which has the pattern bigger-smaller-bigger cells size, is more likely to be located in a narrow area. The minimum spanning tree algorithm is used, to linearize adjacency graph. Many methods have been proposed to manipulate the edges cost in the graph, in order to make the generated spanning tree traverse through narrow passages in detectable ways. Five methods have been proposed, some of them give bad results, and the others give better on in simulations
English abstract
Narrow passage problem is a problematic issue facing the sampling-based motion planner. In this paper, a new approach for narrow areas identification is proposed. The quad-tree cell-decomposition approximation is used to divide the free workspace into smaller cells, and build a graph of adjacency for these. The proposed method follows the graph edges and finds a sequence of cells, which have the same size, preceded and followed by a bigger cell size. The sequence, which has the pattern bigger-smaller-bigger cells size, is more likely to be located in a narrow area. The minimum spanning tree algorithm is used, to linearize adjacency graph. Many methods have been proposed to manipulate the edges cost in the graph, in order to make the generated spanning tree traverse through narrow passages in detectable ways. Five methods have been proposed, some of them give bad results, and the others give better on in simulations
Keywords in English
Narrow passage, cell decomposition, minimum spanning tree MST, Motion planning, sampling based
RIV year
2015
Released
23.06.2015
Location
Brno
ISSN
1803-3814
Book
Mendel 2015, 21st International Conference on Soft Computing
Volume
2015
Number
21
Pages from–to
131–138
Pages count
8
BIBTEX
@article{BUT115144,
author="Ahmad {Abbadi} and Radomil {Matoušek} and Lukáš {Knispel},
title="Narrow passage identification using cell decomposition approximation and minimum spanning tree",
booktitle="Mendel 2015, 21st International Conference on Soft Computing",
year="2015",
volume="2015",
number="21",
month="June",
pages="131--138",
address="Brno",
issn="1803-3814"
}