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Journal of Robotics
Volume 2017, Article ID 8796531, 11 pages
https://doi.org/10.1155/2017/8796531
Research Article

A Global Path Planning Algorithm Based on Bidirectional SVGA

1School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
2School of Information Technology, Jiangsu Maritime Institute, Nanjing 211170, China

Correspondence should be addressed to Taizhi Lv; moc.361@ihziatvl

Received 3 August 2016; Revised 29 November 2016; Accepted 4 January 2017; Published 2 February 2017

Academic Editor: Yuan F. Zheng

Copyright © 2017 Taizhi Lv et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

For path planning algorithms based on visibility graph, constructing a visibility graph is very time-consuming. To reduce the computing time of visibility graph construction, this paper proposes a novel global path planning algorithm, bidirectional SVGA (simultaneous visibility graph construction and path optimization by ). This algorithm does not construct a visibility graph before the path optimization. However it constructs a visibility graph and searches for an optimal path at the same time. At each step, a node with the lowest estimation cost is selected to be expanded. According to the status of this node, different through lines are drawn. If this line is free-collision, it is added to the visibility graph. If not, some vertices of obstacles which are passed through by this line are added to the OPEN list for expansion. In the SVGA process, only a few visible edges which are in relation to the optimal path are drawn and the most visible edges are ignored. For taking advantage of multicore processors, this algorithm performs SVGA in parallel from both directions. By SVGA and parallel performance, this algorithm reduces the computing time and space. Simulation experiment results in different environments show that the proposed algorithm improves the time and space efficiency of path planning.