An effective initialization method for genetic algorithm-based robot path planning using a directed acyclic graph
- Authors
- Lee, Jaesung; Kim, Dae-Won
- Issue Date
- Mar-2016
- Publisher
- ELSEVIER SCIENCE INC
- Keywords
- Robot path planning; Genetic algorithm; Initialization; Directed acyclic graph
- Citation
- INFORMATION SCIENCES, v.332, pp 1 - 18
- Pages
- 18
- Journal Title
- INFORMATION SCIENCES
- Volume
- 332
- Start Page
- 1
- End Page
- 18
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/7164
- DOI
- 10.1016/j.ins.2015.11.004
- ISSN
- 0020-0255
1872-6291
- Abstract
- The goal of robot path planning is to find a feasible path that proceeds from a starting point to a destination point without intersecting any obstacles in the given environment. Recently, genetic algorithm-based robot path planning methods have been widely considered in the intelligent robotics community. Because the initialization process significantly influences the performance of the genetic algorithm, an effective initialization method is required. However, investigation on this subject is still lacking. In this paper, we propose an effective initialization method for genetic algorithm-based robot path planning. Experimental results comparing genetic algorithms with conventional initialization methods and the proposed initialization method showed that the proposed method leads to high quality paths in a significantly shorter execution time. (C) 2015 Elsevier Inc. All rights reserved.
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- Appears in
Collections - College of Software > School of Computer Science and Engineering > 1. Journal Articles
- College of Software > Department of Artificial Intelligence > 1. Journal Articles
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