![](/images/graphics-bg.png)
Potential Odor Intensity Grid Based UAV Path Planning Algorithm with Particle Swarm Optimization Approach
Joint Authors
Zhang, Xuejun
Liu, Yang
Guan, Xiangmin
Delahaye, Daniel
Source
Mathematical Problems in Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-09-14
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
This paper proposes a potential odor intensity grid based optimization approach for unmanned aerial vehicle (UAV) path planning with particle swarm optimization (PSO) technique.
Odor intensity is created to color the area in the searching space with highest probability where candidate particles may locate.
A potential grid construction operator is designed for standard PSO based on different levels of odor intensity.
The potential grid construction operator generates two potential location grids with highest odor intensity.
Then the middle point will be seen as the final position in current particle dimension.
The global optimum solution will be solved as the average.
In addition, solution boundaries of searching space in each particle dimension are restricted based on properties of threats in the flying field to avoid prematurity.
Objective function is redesigned by taking minimum direction angle to destination into account and a sampling method is introduced.
A paired samples t-test is made and an index called straight line rate (SLR) is used to evaluate the length of planned path.
Experiments are made with other three heuristic evolutionary algorithms.
The results demonstrate that the proposed method is capable of generating higher quality paths efficiently for UAV than any other tested optimization techniques.
American Psychological Association (APA)
Liu, Yang& Zhang, Xuejun& Guan, Xiangmin& Delahaye, Daniel. 2016. Potential Odor Intensity Grid Based UAV Path Planning Algorithm with Particle Swarm Optimization Approach. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1112604
Modern Language Association (MLA)
Liu, Yang…[et al.]. Potential Odor Intensity Grid Based UAV Path Planning Algorithm with Particle Swarm Optimization Approach. Mathematical Problems in Engineering No. 2016 (2016), pp.1-16.
https://search.emarefa.net/detail/BIM-1112604
American Medical Association (AMA)
Liu, Yang& Zhang, Xuejun& Guan, Xiangmin& Delahaye, Daniel. Potential Odor Intensity Grid Based UAV Path Planning Algorithm with Particle Swarm Optimization Approach. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-16.
https://search.emarefa.net/detail/BIM-1112604
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1112604