[1]梁爽,曹其新,王雯珊,等.基于强化学习的多定位组件自动选择方法[J].智能系统学报编辑部,2016,11(2):149-154.[doi:10.11992/tis.201510031]
LIANG Shuang,CAO Qixin,WANG Wenshan,et al.An automatic switching method for multiple location components based on reinforcement learning[J].CAAI Transactions on Intelligent Systems,2016,11(2):149-154.[doi:10.11992/tis.201510031]
点击复制
LIANG Shuang,CAO Qixin,WANG Wenshan,et al.An automatic switching method for multiple location components based on reinforcement learning[J].CAAI Transactions on Intelligent Systems,2016,11(2):149-154.[doi:10.11992/tis.201510031]
基于强化学习的多定位组件自动选择方法
《智能系统学报》编辑部[ISSN 1673-4785/CN 23-1538/TP] 卷:
11
期数:
2016年第2期
页码:
149-154
栏目:
学术论文—机器学习
出版日期:
2016-04-25
- Title:
- An automatic switching method for multiple location components based on reinforcement learning
- Keywords:
- mobile robot; location; reinforcement learning; middleware; Monte Carlo; multi-sensor; modularization; distributed system
- 分类号:
- TP242.6
- 摘要:
- 在一个大规模的动态环境中,针对机器人各种定位传感器的局限性,提出了一种基于强化学习的定位组件自动选择方法。系统采用分布式架构,将机器人不同的定位传感器与定位方法封装为不同的组件。采用强化学习的方法,寻找最优策略,实现多定位组件的实时切换。仿真结果表明,该方法可以解决大型环境中,单一定位方法不能适用于整个环境的问题,能够依靠多定位组件提供可靠的机器人定位信息;环境发生改变时,通过学习的方法不需要重新配置组件,且与直接遍历组件后切换组件的方法相比,极大地减小了延时。
- Abstract:
- To address the limitations of location sensors in large-scale dynamic environments, an automatic switching method for multiple robotic components based on reinforcement learning is proposed. This system uses distributed architecture and encapsulates different location sensors and methods into different middleware components. Reinforcement learning is employed to find the optimal strategy for deciding how to switch between components in real time. The simulation result shows that this method can solve problems that a single location method cannot in a large-scale environment and can provide reliable location information depending on multiple location components. This method can also effectively reduce the time delay compared with a method that first traverses all the components directly and then switches components.
- 参考文献/References:
-
[1] 李群明, 熊蓉, 褚健. 室内自主移动机器人定位方法研究综述[J]. 机器人, 2003, 25(6): 560-567, 573. LI Qunming, XIONG Rong, CHU Jian. Localization approaches for indoor autonomous mobile robots: A review[J]. Robot, 2003, 25(6): 560-567, 573.
[2] 张雪华, 刘华平, 孙富春, 等. 采用Kinect的移动机器人目标跟踪[J]. 智能系统学报, 2014, 9(1): 34-39. ZHANG Xuehua, LIU Huaping, SUN Fuchun, et al. Target tracking of mobile robot using Kinect[J]. CAAI transactions on intelligent systems, 2014, 9(1): 34-39.
[3] ANDO N, SUEHIRO T, KITAGAKI K, et al. RT-middleware: distributed component middleware for RT (robot technology)[C]//Proceedings of 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005. (IROS 2005). Edmonton, Alta., Canada: IEEE, 2005: 3933-3938.
[4] ANDO N, SUEHIRO T, KOTOKU T. A software platform for component based RT-system development: OpenRTM-aist[M]//CARPIN S, NODA I, PAGELLO E, et al. Simulation, Modeling, and Programming for Autonomous Robots. Berlin Heidelberg: Springer, 2008: 87-98.
[5] 庄严, 王伟, 王珂, 等. 移动机器人基于激光测距和单目视觉的室内同时定位和地图构建[J]. 自动化学报, 2005, 31(6): 925-933. ZHUANG Yan, WANG Wei, WANG Ke, et al. Mobile robot indoor simultaneous localization and mapping using laser range finder and monocular vision[J]. Acta automatica sinica, 2005, 31(6): 925-933.
[6] GERKEY B P. AMCL[EB/OL]. http://www.ros.org/wiki/amcl, 2011.
[7] 刘洞波, 刘国荣, 胡慧, 等. 基于激光测距的温室移动机器人全局定位方法[J]. 农业机械学报, 2010, 41(5): 158-163. LIU Dongbo, LIU Guorong, HU Hui, et al. Method of mobile robot global localization based on laser range finder in greenhouse[J]. Transactions of the Chinese society for agricultural machinery, 2010, 41(5): 158-163.
[8] 李振伟, 陈翀, 赵有. 基于OpenCV的运动目标跟踪及其实现[J]. 现代电子技术, 2008, 31(20): 128-130, 138. LI Zhenwei, CHEN Chong, ZHAO You. Moving object tracking method and implement based on OpenCV[J]. Modern electronics technique, 2008, 31(20): 128-130, 138.
[9] 张汝波, 顾国昌, 刘照德, 等. 强化学习理论、算法及应用[J]. 控制理论与应用, 2000, 17(5): 637-642. ZHANG Rubo, GU Guochang, LIU Zhaode, et al. Reinforcement learning theory, algorithms and its application[J]. Control Theory & Applications, 2000, 17(5): 637-642.
[10] 黄炳强, 曹广益, 王占全. 强化学习原理、算法及应用[J]. 河北工业大学学报, 2007, 35(6): 34-38. HUANG Bingqiang, CAO Guangyi, WANG Zhanquan. Reinforcement learning theory, algorithms and application[J]. Journal of Hebei University of Technology, 2007, 35(6): 34-38.
[11] SUTTON R S, BARTO A G. Reinforcement learning: an Introduction[M]. Cambridge, Mass.: MIT Press, 1998: 114-116.
[12] WANG Wenshan, CAO Qixin, ZHU Xiaoxiao, et al. An automatic switching approach of robotic components for improving robot localization reliability in complicated environment[J]. Industrial robot: an international journal, 2014, 41(2): 135-144.
- 相似文献/References:
-
[1]蔡自兴,王 勇,王 璐.基于角点聚类的移动机器人自然路标检测与识别[J].智能系统学报编辑部,2006,1(1):52.
CAI Zi-xing,WANG Yong,WANG Lu.Corner clustering based detection and recognition of natural landmark for mobile robot[J].CAAI Transactions on Intelligent Systems,2006,1():52.
[2]杨甜甜,刘志远,陈 虹,等.移动机器人编队控制的现状与问题[J].智能系统学报编辑部,2007,2(4):21.
YANG Tian-tian,LIU Zhi-yuan,CHEN Hong,et al.Formation control of mobile robots: state and open prob lems[J].CAAI Transactions on Intelligent Systems,2007,2():21.
[3]李润伟,蔡自兴,童宇,等.基于ATM的提高狭窄环境探测精度的改进方法[J].智能系统学报编辑部,2008,3(4):283.
LI Run-wei,CAI Zi-xing,TONG Yu.Improving the accuracy of exploring the narrow environment by using ATM[J].CAAI Transactions on Intelligent Systems,2008,3():283.
[4]霍成立,谢 凡,秦世引.面向室内移动机器人的无迹滤波实时导航方法[J].智能系统学报编辑部,2009,4(4):295.
HUO Cheng-li,XIE Fan,QIN Shi-yin.A case study in realtime UKFbased navigation for indoor autonomous travel of mobile robots[J].CAAI Transactions on Intelligent Systems,2009,4():295.
[5]海 丹,李 勇,张 辉,等.无线传感器网络环境下基于粒子滤波的移动机器人SLAM算法[J].智能系统学报编辑部,2010,5(5):425.[doi:10.3969/j.issn.1673-4785.2010.05.008]
HAI Dan,LI Yong,ZHANG Hui,et al.Simultaneous localization and mapping of a mobile robot in wireless sensor networks based on particle filtering[J].CAAI Transactions on Intelligent Systems,2010,5():425.[doi:10.3969/j.issn.1673-4785.2010.05.008]
[6]房立金,王洪光.架空线移动机器人行走越障特点[J].智能系统学报编辑部,2010,5(6):492.
FANG Li-jin,WANG Hong-guang.Research on the characteristics of the movement and obstacleclearing processes of a wiresuspended mobile robot[J].CAAI Transactions on Intelligent Systems,2010,5():492.
[7]任立敏,王伟东,杜志江.移动机器人队形控制关键技术及其进展[J].智能系统学报编辑部,2013,8(5):381.[doi:10.3969/j.issn.1673-4785.201302011]
REN Limin,WANG Weidong,DU Zhijiang.Key technologies and development of? formation control of mobile robots[J].CAAI Transactions on Intelligent Systems,2013,8():381.[doi:10.3969/j.issn.1673-4785.201302011]
[8]贺超,刘华平,孙富春,等.采用Kinect的移动机器人目标跟踪与避障[J].智能系统学报编辑部,2013,8(5):426.[doi:10.3969/j.issn.1673-4785.201301028]
HE Chao,LIU Huaping,SUN Fuchun,et al.Target tracking and obstacle avoidance of mobile robot using Kinect[J].CAAI Transactions on Intelligent Systems,2013,8():426.[doi:10.3969/j.issn.1673-4785.201301028]
[9]阮晓钢,庞涛,张晓平,等.一种基于情感智能的机器人自主趋光行为研究[J].智能系统学报编辑部,2015,10(1):97.[doi:10.3969/j.issn.1673-4785.201312035]
RUAN Xiaogang,PANG Tao,ZHANG Xiaoping,et al.Research on the autonomous phototaxis behavior of a robot based on emotion intelligence[J].CAAI Transactions on Intelligent Systems,2015,10():97.[doi:10.3969/j.issn.1673-4785.201312035]
[10]沈博闻,于宁波,刘景泰.仓储物流机器人集群的智能调度和路径规划[J].智能系统学报编辑部,2014,9(6):659.[doi:10.3969/j.issn.1673-4785.201312048]
SHEN Bowen,YU Ningbo,LIU Jingtai.Intelligent scheduling and path planning of warehouse mobile robots[J].CAAI Transactions on Intelligent Systems,2014,9():659.[doi:10.3969/j.issn.1673-4785.201312048]
备注/Memo
收稿日期:2015-10-29;改回日期:。
基金项目:国家自然科学基金项目(61273331).
作者简介:梁爽,女,1993年生,硕士研究生,主要研究方向为移动机器人路径规划及模块化机器人技术。曹其新,男,1960年生,教授,博士生导师,主要研究方向为智能机器人与模块化系统、机器视觉与模式识别、移动机器人、泛在机器人技术。被EI、SCI检索论文90余篇,获得发明和实用新型专利50余项。王雯珊,女,1986年生,博士研究生,主要研究方向为泛在机器人、任务规划。
通讯作者:曹其新.E-mail:qxcao@sjtu.edu.cn.
更新日期/Last Update:
1900-01-01