改进人工鱼群算法的机器人路径规划及跟踪
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摘要
为了使移动机器人在已知环境中规划出最优路径并对路径进行跟踪,提出了基于改进人工鱼群算法的机器人路径规划方法和PID跟踪方法。使用栅格法建立了环境模型;分析了传统人工鱼群算法原理,对算法的视觉范围、移动步长、可行走区域进行了重新定义,使之能够适用于栅格环境;提出了加权平均视觉范围和自适应拥挤度因子,兼顾了算法前期大范围搜索和后期细致搜索;使用改进人工鱼群算法优化PID控制参数;经实验,相比于传统算法,改进算法规划出的路径长度减少了11.4%,改进算法优化的PID参数在超调量、上升时间、震荡次数等方面优势明显。
To plan optimal path in the known environment for mobile robot,path panning and tracking method based on improved artificial fish swarm algorithm is proposed. Grid method is used to model the environment,traditional algorithm is analyzed. Visual range,step length,can-walking area is redefined to st to grid environment. Weighted average visual range and adaptive crowding factor are raised,which balances large-scope searching at earlier stage and careful searching at later stage. PID tracking parameters are optimized by improved artificial fish swarm algorithm. By trial,compared with algorithm,path planned by improved algorithm decreased by 11.4%,and PID parameters optimized by improved algorithm possess advantages of overshoot,rise time,and null.
To plan optimal path in the known environment for mobile robot,path panning and tracking method based on improved artificial fish swarm algorithm is proposed. Grid method is used to model the environment,traditional algorithm is analyzed. Visual range,step length,can-walking area is redefined to st to grid environment. Weighted average visual range and adaptive crowding factor are raised,which balances large-scope searching at earlier stage and careful searching at later stage. PID tracking parameters are optimized by improved artificial fish swarm algorithm. By trial,compared with algorithm,path planned by improved algorithm decreased by 11.4%,and PID parameters optimized by improved algorithm possess advantages of overshoot,rise time,and null.
引文
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[2]段朋.与人共融的家庭服务机器人定位与导航[D].济南:山东大学,2015.(Duan Peng.Localization and navigation of home service robot in considering of human-robot harmony[D].Jinan:Shandong University,2015.)
[3]陈超,唐坚,靳祖光.一种基于可视图法导盲机器人路径规划的研究[J].机械科学与技术,2014,33(4):490-495.(Chen Chao,Tang Jian,Qi Zu-guang.A path planning algorithm for seeing eye robots based on v-graph[J].Mechanical Science and Technology for Aerospace Engineering,2014,33(4):490-495.)
[4]柴寅,唐秋华,邓明星.机器人路径规划的栅格模型构建与蚁群算法求解[J].机械设计与制造,2016(4):178-181.(Chai Yin,Tang Qiu-hua,Deng Ming-xing.Grid model and ant colony algorithm for robot path planning[J].Machinery Design&Manufacture,2016(4):178-181.)
[5]刘传领.基于势场法和遗传算法的机器人路径规划技术研究[D].南京:南京理工大学,2012.(Liu Chuan-ling.Researches on technologies for robot path planning based on artificial potential field and genetic algorithm[D].Nanjing:Nanjing University of Science&Technology,2012.)
[6]樊建.基于增强学习和ART2神经网络的移动机器人路径规划研究[D].上海:上海大学,2006.(Fan Jian.The research of mobile robot path planning based on reinforcement learning and ART2 neural network[D].Shanghai:Shanghai University,2006.)
[7]Hong C Y,Zhang Y F,Zhang M X.Application of FBG sensors for geotechnical health monitoring,a review of sensor design,implementation methods and packaging techniques[J].Sensors&Actuators A Physical,2016,244(6):184-197.
[8]刘晓磊,蒋林,金祖飞.非结构化环境中基于栅格法环境建模的移动机器人路径规划[J].机床与液压,2016,44(17):1-7.(Liu Xiao-lei,Jiang Lin,Jin Zu-fei.Mobile robot path planning based on environment modeling of grid method in unstructured environment[J].Machine Tool&Hydraulcs,2016,44(17):1-7.)
[9]Kumar K P,Saravanan B,Swarup K S.Optimization of renewable energy sources in a microgrid using artificial fish swarm algorithm[J].Energy Procedia,2016,90(12):107-113.
[10]薛亚娣.改进的人工鱼群算法及其应用研究[D].兰州:兰州大学,2015.(Xue Ya-di.The research and application of improved artificial fish swarm algorithm[D].Lanzhou:Lanzhou University,2015.)