A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method

To improve the performance of multi-unmanned aerial vehicle path planning in plateau narrow area, a control strategy based on Cauchy mutant pigeon-inspired optimization algorithm is proposed in this article. The Cauchy mutation operator is chosen to improve the pigeon-inspired optimization algorithm...

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Main Authors: Bo Hang Wang, Dao Bo Wang, Zain Anwar Ali
Format: Article
Language:English
Published: SAGE Publishing 2020-01-01
Series:Measurement + Control
Online Access:https://doi.org/10.1177/0020294019885155
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spelling doaj-91511fec8a8e4e769e37eee73807cc952020-11-25T03:52:31ZengSAGE PublishingMeasurement + Control0020-29402020-01-015310.1177/0020294019885155A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning methodBo Hang WangDao Bo WangZain Anwar AliTo improve the performance of multi-unmanned aerial vehicle path planning in plateau narrow area, a control strategy based on Cauchy mutant pigeon-inspired optimization algorithm is proposed in this article. The Cauchy mutation operator is chosen to improve the pigeon-inspired optimization algorithm by comparing and analyzing the changing trend of fitness function of the local optimum position and the global optimum position when dealing with unmanned aerial vehicle path planning problems. The plateau topography model and plateau wind field model are established. Furthermore, a variety of control constrains of unmanned aerial vehicles are summarized and modeled. By combining with relative positions and total flight duration, a cooperative path planning strategy for unmanned aerial vehicle group is put forward. Finally, the simulation results show that the proposed Cauchy mutant pigeon-inspired optimization method gives better robustness and cooperative path planning strategy which are effective and advanced as compared with traditional pigeon-inspired optimization algorithm.https://doi.org/10.1177/0020294019885155
collection DOAJ
language English
format Article
sources DOAJ
author Bo Hang Wang
Dao Bo Wang
Zain Anwar Ali
spellingShingle Bo Hang Wang
Dao Bo Wang
Zain Anwar Ali
A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method
Measurement + Control
author_facet Bo Hang Wang
Dao Bo Wang
Zain Anwar Ali
author_sort Bo Hang Wang
title A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method
title_short A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method
title_full A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method
title_fullStr A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method
title_full_unstemmed A Cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method
title_sort cauchy mutant pigeon-inspired optimization–based multi-unmanned aerial vehicle path planning method
publisher SAGE Publishing
series Measurement + Control
issn 0020-2940
publishDate 2020-01-01
description To improve the performance of multi-unmanned aerial vehicle path planning in plateau narrow area, a control strategy based on Cauchy mutant pigeon-inspired optimization algorithm is proposed in this article. The Cauchy mutation operator is chosen to improve the pigeon-inspired optimization algorithm by comparing and analyzing the changing trend of fitness function of the local optimum position and the global optimum position when dealing with unmanned aerial vehicle path planning problems. The plateau topography model and plateau wind field model are established. Furthermore, a variety of control constrains of unmanned aerial vehicles are summarized and modeled. By combining with relative positions and total flight duration, a cooperative path planning strategy for unmanned aerial vehicle group is put forward. Finally, the simulation results show that the proposed Cauchy mutant pigeon-inspired optimization method gives better robustness and cooperative path planning strategy which are effective and advanced as compared with traditional pigeon-inspired optimization algorithm.
url https://doi.org/10.1177/0020294019885155
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