检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:陈岁繁 王浈元 李其朋 CHEN Suifan;WANG Zhenyuan;LI Qipeng(School of Mechanical and Energy Engineering,Zhejiang University ofScience and Technology,Hangzhou 310023,Zhejiang,China)
机构地区:[1]浙江科技大学机械与能源工程学院,杭州310023
出 处:《浙江科技学院学报》2024年第1期59-67,共9页Journal of Zhejiang University of Science and Technology
基 金:浙江省科技计划项目(2023C02008,2024C04037)。
摘 要:【目的】针对传统蚁群算法(ant colonyalgorithm, ACA)在移动机器人(automatic guided vehicle, AGV)路径规划中搜索效率低、寻找路径长、拐点个数多等问题,提出一种改进的蚁群优化算法(ant colony optimization, ACO)。【方法】首先,在蚁群算法中加入预估代价值策略来改进启发函数,增强目标点的引导作用,提升搜索效率;然后,结合狼群算法(wolf pack algorithm, WPA)分配机制来更新信息素,解决路径规划时易陷入局部最优的问题;接着加入拐点影响因子来降低路径拐点;最后,采用动态避障策略来解决死锁问题。【结果】运用改进蚁群优化算法后,移动机器人路径规划时,最佳路径长度、迭代次数和拐点数等比传统算法分别降低9.7%、57.8%、65.0%。【结论】本研究结果能为移动机器人在复杂环境下的路径选择提供重要参考。[Objective]Aiming at the problems of low search efficiency,long search path,and multiple inflection points in traditional ant colony algorithm(ACA)for automatic guided vehicle(AGV)path planning,an improved ant colony optimization(ACO)algorithm was proposed.[Method]First,an estimated surrogate value strategy was incorporated into the ant colony algorithm to improve the heuristic function,enhance the guiding effect of the target point,and boost search efficiency;then,the wolf pack algorithm(WPA)allocation mechanism was combined to update pheromones,solving the problem of easily falling into local optima during path planning,and adding inflection point influence factors to reduce path inflection points;finally,a dynamic obstacle avoidance strategy was adopted to solve the deadlock problem.[Result]After applying the improved ant colony optimization algorithm,the optimal path length,the number of iterations and the number of inflections in AGV path planning are reduced by 9.7%,57.8%,and 65.0%,respectively,compared to traditional algorithms,[Conclusion]This study provides important references for AGV to choose paths under complex environmental conditions.
关 键 词:蚁群优化算法 搜索效率 信息素 死锁 移动机器人
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:13.59.56.153