基于烟花混合蚁群的移动机器人路径规划研究
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摘要
目的以应用于包装车间的移动机器人的路径规划作为研究对象,解决蚁群算法收敛速度慢、寻找到的路径不优等缺陷。方法引入改进烟花和蚁群融合的方法进行搜索,首先建立移动机器人的栅格地图,其次采用改进烟花算法进行路径粗搜索,将得到的路径作为信息素增量,再运用蚁群细搜索求解。结果文中方法与传统方法相比,收敛速度得到提高,并寻找到了更优的路径。结论通过采用融合算法,弥补了烟花寻优的不足,加快了蚁群的收敛,可以对2种算法互相取长补短。
The paper aims to solve the slow convergence speed and inferior path of ACO algorithm with the path planning of mobile robot applied in packaging workshop as the research object. The method of fusing IFWA and ACO was applied for searching. Firstly, the raster map of mobile robot was established. Secondly, the IFWA was used to search the path roughly to take the path obtained as the pheromone increment. Then the ACO subtle search was used for solution.Compared with the traditional method, the method adopted in this paper improved the convergence speed and found the optimal path. The proposed fusion method covers the shortage of FWA and accelerates the convergence of ACO. The two algorithms could be used for mutual complementation.
The paper aims to solve the slow convergence speed and inferior path of ACO algorithm with the path planning of mobile robot applied in packaging workshop as the research object. The method of fusing IFWA and ACO was applied for searching. Firstly, the raster map of mobile robot was established. Secondly, the IFWA was used to search the path roughly to take the path obtained as the pheromone increment. Then the ACO subtle search was used for solution.Compared with the traditional method, the method adopted in this paper improved the convergence speed and found the optimal path. The proposed fusion method covers the shortage of FWA and accelerates the convergence of ACO. The two algorithms could be used for mutual complementation.
引文
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[14]SHUANG B,CHEN J P,LI Z B.Study on Hybrid PS-ACO Algorithm[J].Applied Intelligence,2011,34(1):64-73.
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[16]朱大奇,颜明重.移动机器人路径规划技术综述[J].控制与决策,2010,25(7):961-967.ZHU Da-qi,YAN Ming-chong.Survey on Technology of Mobile Robot Path Planning[J].Control and Decision,2010,25(7):961-967.
[2]徐敏,陈州尧,李俊蒂.基于模拟退火算法的码垛机器人码垛路径规划[J].包装工程,2015,36(15):95-103.XU Min,CHEN Zhou-yao,LI Jun-di.Path Planning of Palletizing Robot Stacking Based on Simulated Annealing Algorithm[J].Packaging Engineering,2015,36(15):95-103.
[3]李悝.基于混沌粒子群优化算法的AGV路径规划研究[J].包装工程,2018,39(23):32-37.LI Kui.AGV Path Planning Based on Chaos Particle Swarm Optimization Algorithm[J].Packaging Engineering,2018,39(23):32-37.
[4]徐雪松,杨胜杰,陈荣元.复杂环境移动群机器人最优路径规划方法[J].电子测量与仪器学报,2016,30(2):274-282.XU Xue-song,YANG Sheng-jie,CHEN Rong-yuan.Dynamic Differential Evolution Algorithm for Swarm Robots Search Path Planning[J].Journal of Electronic Measurement and Instrumentation,2016,30(2):274-282.
[5]魏欣,孙玥.一种新型包装码垛机器人路径规划方法[J].包装工程,2018,39(15):173-177.WEI Xin,SUN Yue.A New Path Planning Method for Packaging Palletizing Robot[J].Packaging Engineering,2018,39(15):173-177.
[6]邓高峰,张雪萍,刘彦萍.一种障碍环境下机器人路径规划的蚁群粒子群算法[J].控制理论与应用,2009,26(8):879-883.DENG Gao-feng,ZHANG Xue-ping,LIU Yan-ping.Ant Colony Optimization and Particle Swarm Optimization for Robot-path Planning in Obstacle Environment[J].Control Theory&Applications,2009,26(8):879-883.
[7]于红斌,李孝安.基于栅格法的机器人快速路径规划[J].微电子学与计算机,2005,22(6):98-100.YU Hong-bin,LI Xiao-an.Fast Path Planning Based on Grid Model of Robot[J].Microelectronics&Computer,2005,22(6):98-100.
[8]CIMURS R,HWANG J,SUH I H.Bezier Curve-based Smoothing for Path Planner with Curvature Constraint[C]//IEEE International Conference on Robotic Computing,IEEE,2017.
[9]WANG Z Q,ZHU X G,HAN Q Y.Mobile Robot Path Planning Based on Parameter Optimization Ant Colony Algorithm[J].Procedia Engineering,2011,15(8):2738-2741.
[10]朱亮吉.基于烟花算法的移动机器人路径规划仿真研究[D].西安:西南交通大学,2018.ZHU Liang-ji.Research on Simulation of Path Planning of Mobile Robot Based on Firework Algorithm[D].Xi'an:Southwest Jiao-tong University,2018.
[11]国海涛,朱庆保,徐守江.基于栅格法的机器人路径规划快速搜索随机树算法[J].南京师范大学学报,2007,7(2):58-61.GUO Hai-tao,ZHU Qing-bao,XU Shou-jiang.Rapid-Exploring Random Tree Algorithm for Path Planning[J].Journal of Nanjing Normal University,2007,7(2):58-61.
[12]ABIYEV R,IBRAHIM D,ERIN B.Navigation of Mobile Robots in the Presence of Obstacles[J].Advances in Engineering Software,2010,41(10):1179-1186.
[13]ZHU W R,DUAN H B.Chaotic Predator-prey Biogeography-based Optimization Approach for UCAV Path Planning[J].Aerospace Science and Technology,2014,32(1):153-161.
[14]SHUANG B,CHEN J P,LI Z B.Study on Hybrid PS-ACO Algorithm[J].Applied Intelligence,2011,34(1):64-73.
[15]罗德林,吴顺祥.基于势场蚁群算法的机器人路径规划[J].系统工程与电子技术,2010,32(6):1277-1280.LUO De-lin,WU Shun-xiang.Ant Colony Optimization with Potential Field Heuristic for Robot Path Planning[J].Systems Engineering and Electronics,2010,32(6):1277-1280.
[16]朱大奇,颜明重.移动机器人路径规划技术综述[J].控制与决策,2010,25(7):961-967.ZHU Da-qi,YAN Ming-chong.Survey on Technology of Mobile Robot Path Planning[J].Control and Decision,2010,25(7):961-967.