Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm

To improve property of artificial bee colony algorithm in multi-robot path planning,the optimized artificial bee colony algorithm is proposed. A new environment modeling method is given,which makes barrier border smooth. The principle of artificial bee colony algorithm is analyzed,adaptive searching...

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Main Authors: Zhang Lin, Zhan Weipeng, Zhu Lingfen, Wu Guoxing
Format: Article
Language:zho
Published: Editorial Office of Journal of Mechanical Transmission 2017-01-01
Series:Jixie chuandong
Subjects:
Online Access:http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.12.026
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author Zhang Lin
Zhan Weipeng
Zhu Lingfen
Wu Guoxing
author_facet Zhang Lin
Zhan Weipeng
Zhu Lingfen
Wu Guoxing
author_sort Zhang Lin
collection DOAJ
description To improve property of artificial bee colony algorithm in multi-robot path planning,the optimized artificial bee colony algorithm is proposed. A new environment modeling method is given,which makes barrier border smooth. The principle of artificial bee colony algorithm is analyzed,adaptive searching factor is proposed to improve new food source generation method,which balances searching range and convergence rate.The robot path point is improved by location angle,and by using this way,the location parameter is reduced.The path length,path smoothness and path safety is synthesized to a goal function by weight. The simulation trial shows that path length and time cost of improved algorithm is superior to primary algorithm. And with robot quantity increasing,the gap of the two algorithms is bigger and bigger.
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spelling doaj.art-9312561ff28a4cc6829f8d647bcc10442023-05-26T09:46:55ZzhoEditorial Office of Journal of Mechanical TransmissionJixie chuandong1004-25392017-01-014112913229933965Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony AlgorithmZhang LinZhan WeipengZhu LingfenWu GuoxingTo improve property of artificial bee colony algorithm in multi-robot path planning,the optimized artificial bee colony algorithm is proposed. A new environment modeling method is given,which makes barrier border smooth. The principle of artificial bee colony algorithm is analyzed,adaptive searching factor is proposed to improve new food source generation method,which balances searching range and convergence rate.The robot path point is improved by location angle,and by using this way,the location parameter is reduced.The path length,path smoothness and path safety is synthesized to a goal function by weight. The simulation trial shows that path length and time cost of improved algorithm is superior to primary algorithm. And with robot quantity increasing,the gap of the two algorithms is bigger and bigger.http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.12.026Multi-robot;Collaborative planning;Optimized artificial bee colony algorithm;Adaptive searching factor
spellingShingle Zhang Lin
Zhan Weipeng
Zhu Lingfen
Wu Guoxing
Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm
Jixie chuandong
Multi-robot;Collaborative planning;Optimized artificial bee colony algorithm;Adaptive searching factor
title Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm
title_full Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm
title_fullStr Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm
title_full_unstemmed Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm
title_short Multi-robot Collaborative Planning based on Optimized Artificial Bee Colony Algorithm
title_sort multi robot collaborative planning based on optimized artificial bee colony algorithm
topic Multi-robot;Collaborative planning;Optimized artificial bee colony algorithm;Adaptive searching factor
url http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2017.12.026
work_keys_str_mv AT zhanglin multirobotcollaborativeplanningbasedonoptimizedartificialbeecolonyalgorithm
AT zhanweipeng multirobotcollaborativeplanningbasedonoptimizedartificialbeecolonyalgorithm
AT zhulingfen multirobotcollaborativeplanningbasedonoptimizedartificialbeecolonyalgorithm
AT wuguoxing multirobotcollaborativeplanningbasedonoptimizedartificialbeecolonyalgorithm