[1]寿佳鑫,张志明,苏永清,等.基于ROS和激光雷达的室内移动机器人定位和导航系统设计与实现[J].机械与电子,2018,(11):76-80.
　SHOU Jiaxin,ZHANG Zhiming,SU Yongqing,et al.Design and Implementation of Indoor Positioning and Navigation System of MobileRobot Based on ROS and LiDAR[J].Machinery & Electronics,2018,(11):76-80.
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基于ROS和激光雷达的室内移动机器人定位和导航系统设计与实现
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2018年11期
页码:
76-80
栏目:
智能工程
出版日期:
2018-11-24

文章信息/Info

Title:
Design and Implementation of Indoor Positioning and Navigation System of Mobile Robot Based on ROS and LiDAR
文章编号:
1001-2257(2018)11-0076-05
作者:
寿佳鑫; 张志明; 苏永清; 钟 政
(同济大学电子与信息工程学院, 上海 200092)
Author(s):
SHOU Jiaxin;  ZHANG Zhiming;  SU Yongqing;  ZHONG Zheng
(College of Electronics and Information Engineering, Tongji University, Shanghai 200092, China)
关键词:
机器人操作系统;  同步定位与地图构建;  激光雷达;  室内定位与导航
Keywords:
robot operating system;  simultaneous localization and mapping;  light detection and ranging;  indoor position and navigation
分类号:
TP242; TH39
文献标志码:
A
摘要:
根据自主运动机器人的室内定位需求,设计并实现基于机器人操作系统ROS和激光雷达的室内移动机器人定位和导航系统。机器人系统采用树莓派控制器作为控制核心平台,利用激光雷达采集环境信息,在ROS分布式框架下进行软件算法的开发,实现基于扫描匹配算法的SLAM功能、基于最优路径算法路径规划以及基于粒子滤波算法的导航功能。理论仿真及实验实测结果表明,系统可构建精度较高的环境地图,并对机器人进行定位,有效完成室内定位和导航任务,具有低成本、开源、模块化、易于拓展等优点。
Abstract:
According to the requirements of indoor positioning of autonomous robots, an indoor mobile robot positioning and navigation system based on ROS and LiDAR was designed and implemented. The robot system uses Raspberry Pi as the core controller of the platform with LiDAR collecting environment information. The system was developed under the distributed framework of ROS to achieve the SLAM based on scan-matching algorithm, the path plan function based on Dijkstra algorithm and the navigation function based on particle filter. The results of theoretical simulation and real experimental measurement show that the system can construct a high-precision environment map, locate the robot precisely and effectively complete the indoor positioning and navigation tasks with the characteristics of low cost, open source, modularization, and easy expansion.

参考文献/References:

[1] JIN M, LIU S, SCHIAVON S, et al. Automated mobile sensing: Towards high-granularity agile indoor environmental quality monitoring[J]. Building and Environment, 2018, 127(1): 268-276.
[2] 李建勇, 刘雪梅, 刘雄. 基于XTION的机器人室内三维地图实时创建[J]. 机械与电子, 2017, 35(4): 70-74.
[3] 权美香, 朴松昊, 李国. 视觉SLAM综述[J]. 智能系统学报, 2016, 11(6): 768–776.
[4] 徐曙. 基于SLAM的移动机器人导航系统研究[D]. 武汉: 华中科技大学, 2014.
[5] KHAN S, WOLLHERR D, BUSS M. Modeling laser intensities for simultaneous localization and mapping[J]. IEEE Robotics and Automation Letters, 2016, 1(2): 692-699.
[6] ARTAMONOV S, GRYAZNOV N, KUPRENYUK V, et al. Selection of scanners for use in lidar systems[J]. Journal of Optical Technology, 2016, 83(9): 549-555.
[7] 柯博文. 树莓派Raspberry Pi实战指南[M]. 北京: 清华大学出版社, 2015.
[8] COUSINS S,GERKEY B,CONLEY K, et al. Sharing software with ROS[J]. IEEE Robotics & Automation Magazine, 2010, 17(2): 12-14.
[9] 周兴社. 机器人操作系统ROS原理与应用[M]. 北京: 机械工业出版社, 2016.
[10] KAMARUDIN K, MAMDUH S M, SHAKAFF AYM, et al. Performance analysis of the microsoft kinect sensor for 2D simultaneous localization and mapping techniques[J]. Sensors, 2014, 14(12): 23365-23387.

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备注/Memo

备注/Memo:
收稿日期:2018-07-24
基金项目:教育部高等教育司产学合作协同育人项目(201702008060); 同济大学本科交叉课程建设项目(TJ0800104239); 同济大学大学生学科竞赛项目(TJ4250142301/004)
作者简介:寿佳鑫(1996-),男,浙江诸暨人,硕士研究生,研究方向为控制工程; 张志明(1975-),男,江苏常熟人,博士,讲师,研究方向为检测技术及自动化装置; 苏永清(1972-),男,安徽砀山人,博士,副教授,研究方向为过程控制、流体传动控制等;
更新日期/Last Update: 2018-11-24