Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function

Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function

We present one algorithm based on particle swarm optimization (PSO) with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions) with obstacles. The shortest path of the mobile object is set as goal function, which is constrai...

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Main Authors: Yong Ma, M. Zamirian, Yadong Yang, Yanmin Xu, Jing Zhang
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2013/613964
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spelling doaj-1515fc1eaec4484988f502156a2565a22020-11-25T00:24:57ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472013-01-01201310.1155/2013/613964613964Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty FunctionYong Ma0M. Zamirian1Yadong Yang2Yanmin Xu3Jing Zhang4Navigation College, Wuhan University of Technology, Wuhan, Hubei 430063, ChinaDepartment of Mathematics, Islamic Azad University, Bojnourd Branch, Bojnourd 94186-54145, IranNavigation College, Wuhan University of Technology, Wuhan, Hubei 430063, ChinaNavigation College, Wuhan University of Technology, Wuhan, Hubei 430063, ChinaChutian College, Huazhong Agricultural University, Wuhan, Hubei 430205, ChinaWe present one algorithm based on particle swarm optimization (PSO) with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions) with obstacles. The shortest path of the mobile object is set as goal function, which is constrained by conflict-free criterion, path smoothness, and velocity and acceleration requirements. This problem is formulated as a calculus of variation problem (CVP). With parametrization method, the CVP is converted to a time-varying nonlinear programming problem (TNLPP). Constraints of TNLPP are transformed to general TNLPP without any constraints through penalty functions. Then, by using a little calculations and applying the algorithm PSO, the solution of the CVP is consequently obtained. Approach efficiency is confirmed by numerical examples.http://dx.doi.org/10.1155/2013/613964
collection DOAJ
language English
format Article
sources DOAJ
author Yong Ma
M. Zamirian
Yadong Yang
Yanmin Xu
Jing Zhang
spellingShingle Yong Ma
M. Zamirian
Yadong Yang
Yanmin Xu
Jing Zhang
Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function
Mathematical Problems in Engineering
author_facet Yong Ma
M. Zamirian
Yadong Yang
Yanmin Xu
Jing Zhang
author_sort Yong Ma
title Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function
title_short Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function
title_full Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function
title_fullStr Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function
title_full_unstemmed Path Planning for Mobile Objects in Four-Dimension Based on Particle Swarm Optimization Method with Penalty Function
title_sort path planning for mobile objects in four-dimension based on particle swarm optimization method with penalty function
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2013-01-01
description We present one algorithm based on particle swarm optimization (PSO) with penalty function to determine the conflict-free path for mobile objects in four-dimension (three spatial and one-time dimensions) with obstacles. The shortest path of the mobile object is set as goal function, which is constrained by conflict-free criterion, path smoothness, and velocity and acceleration requirements. This problem is formulated as a calculus of variation problem (CVP). With parametrization method, the CVP is converted to a time-varying nonlinear programming problem (TNLPP). Constraints of TNLPP are transformed to general TNLPP without any constraints through penalty functions. Then, by using a little calculations and applying the algorithm PSO, the solution of the CVP is consequently obtained. Approach efficiency is confirmed by numerical examples.
url http://dx.doi.org/10.1155/2013/613964
work_keys_str_mv AT yongma pathplanningformobileobjectsinfourdimensionbasedonparticleswarmoptimizationmethodwithpenaltyfunction
AT mzamirian pathplanningformobileobjectsinfourdimensionbasedonparticleswarmoptimizationmethodwithpenaltyfunction
AT yadongyang pathplanningformobileobjectsinfourdimensionbasedonparticleswarmoptimizationmethodwithpenaltyfunction
AT yanminxu pathplanningformobileobjectsinfourdimensionbasedonparticleswarmoptimizationmethodwithpenaltyfunction
AT jingzhang pathplanningformobileobjectsinfourdimensionbasedonparticleswarmoptimizationmethodwithpenaltyfunction
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