Improved Artificial Potential Field Method for Dual-manipulator Path Planning Algorithm

Aiming at the problem that the traditional artificial potential field method cannot constrain the overall posture of the dual manipulator system when planning the path of the dual manipulator system,and it is easy to fall into the local extreme point,the artificial potential field method is improved...

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Main Authors: Haonan Ma, Zhian Zhang, Qingliang Li
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2021-06-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.06.012
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author Haonan Ma
Zhian Zhang
Qingliang Li
author_facet Haonan Ma
Zhian Zhang
Qingliang Li
author_sort Haonan Ma
collection DOAJ
description Aiming at the problem that the traditional artificial potential field method cannot constrain the overall posture of the dual manipulator system when planning the path of the dual manipulator system,and it is easy to fall into the local extreme point,the artificial potential field method is improved. Use the D-H method to analyze the kinematics of the dual-manipulator system,use the cylindrical-hemisphere bounding box model as the collision detection model. The construction of a new potential energy function dual-manipulator system is used to plan the path,use the method of constructing virtual target points to help the manipulator escape local extreme points. Simulation experiments show that the improved algorithm overcomes the shortcomings of local minima and realizes the path planning of the dual-manipulator system.
format Article
id doaj-art-e9948d5d712b4e63bb47cea973b6975b
institution Kabale University
issn 1004-2539
language zho
publishDate 2021-06-01
publisher Editorial Office of Journal of Mechanical Transmission
record_format Article
series Jixie chuandong
spelling doaj-art-e9948d5d712b4e63bb47cea973b6975b2025-01-10T14:48:47ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392021-06-0145778411255429Improved Artificial Potential Field Method for Dual-manipulator Path Planning AlgorithmHaonan MaZhian ZhangQingliang LiAiming at the problem that the traditional artificial potential field method cannot constrain the overall posture of the dual manipulator system when planning the path of the dual manipulator system,and it is easy to fall into the local extreme point,the artificial potential field method is improved. Use the D-H method to analyze the kinematics of the dual-manipulator system,use the cylindrical-hemisphere bounding box model as the collision detection model. The construction of a new potential energy function dual-manipulator system is used to plan the path,use the method of constructing virtual target points to help the manipulator escape local extreme points. Simulation experiments show that the improved algorithm overcomes the shortcomings of local minima and realizes the path planning of the dual-manipulator system.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.06.012Dual manipulator systemPath planningArtificial potential field methodLocal minimum
spellingShingle Haonan Ma
Zhian Zhang
Qingliang Li
Improved Artificial Potential Field Method for Dual-manipulator Path Planning Algorithm
Jixie chuandong
Dual manipulator system
Path planning
Artificial potential field method
Local minimum
title Improved Artificial Potential Field Method for Dual-manipulator Path Planning Algorithm
title_full Improved Artificial Potential Field Method for Dual-manipulator Path Planning Algorithm
title_fullStr Improved Artificial Potential Field Method for Dual-manipulator Path Planning Algorithm
title_full_unstemmed Improved Artificial Potential Field Method for Dual-manipulator Path Planning Algorithm
title_short Improved Artificial Potential Field Method for Dual-manipulator Path Planning Algorithm
title_sort improved artificial potential field method for dual manipulator path planning algorithm
topic Dual manipulator system
Path planning
Artificial potential field method
Local minimum
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2021.06.012
work_keys_str_mv AT haonanma improvedartificialpotentialfieldmethodfordualmanipulatorpathplanningalgorithm
AT zhianzhang improvedartificialpotentialfieldmethodfordualmanipulatorpathplanningalgorithm
AT qingliangli improvedartificialpotentialfieldmethodfordualmanipulatorpathplanningalgorithm