Open Access System for Information Sharing

Login Library

 

Article
Cited 21 time in webofscience Cited 23 time in scopus
Metadata Downloads

Variants of Quantized Visibility Graph for Efficient Path Planning SCIE SCOPUS

Title
Variants of Quantized Visibility Graph for Efficient Path Planning
Authors
Jung Tae KimMun Sang KimKim, D
Date Issued
2011-12
Publisher
VSP
Abstract
We propose variants of the quantized visibility graph (QVG) for efficient path planning. Conventional visibility graphs have been used for path planning when the obstacles are polygonal. The QVG extends its usability to arbitrarily-shaped objects by representing the obstacles as polygons. We propose QVG variants which represent all combinations of three factors, each with two alternatives: (i) quantization level (fixed-level or multiple-level), (ii) object representation method (inner and boundary cells together or boundary cells only), and (iii) methods used to check whether pairs of points are mutually visible (rotational plane sweep algorithm or sign inequality discrimination (SID) algorithm). In the verification of the efficiency of the proposed QVGs, (i) all QVGs produced the same best path, which was shorter than the convectional algorithms, (ii) computational cost to find the shortest path is lower when using QVGs than when using the convectional algorithms and (iii) the QVG that uses multi-level quantization, partial obstacle representation and SID visibility checking provides the shortest best path and has lower computational cost than all other methods. (C) Koninklijke Brill NV, Leiden and The Robotics Society of Japan, 2011
Keywords
Path planning; fixed cell decomposition; adaptive cell decomposition; visibility graph; quantized visibility graph; OBSTACLES
URI
https://oasis.postech.ac.kr/handle/2014.oak/16572
DOI
10.1163/016918611X603855
ISSN
0169-1864
Article Type
Article
Citation
ADVANCED ROBOTICS, vol. 25, no. 18, page. 2341 - 2360, 2011-12
Files in This Item:
There are no files associated with this item.

qr_code

  • mendeley

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher

김대진KIM, DAI JIN
Dept of Computer Science & Enginrg
Read more

Views & Downloads

Browse