[1]许志明,张秉天,邹嘉俊,等.ROS 系统的激光 SLAM 视觉智能勘察小车[J].计算机技术与发展,2020,30(05):84-87.[doi:10. 3969 / j. issn. 1673-629X. 2020. 05. 016]
　XU Zhi-ming,ZHANG Bing-tian,ZOU Jia-jun,et al.Intelligent Survey Car Based on Laser SLAM Vision for ROS System[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2020,30(05):84-87.[doi:10. 3969 / j. issn. 1673-629X. 2020. 05. 016]
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ROS 系统的激光 SLAM 视觉智能勘察小车()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年05期
页码:
84-87
栏目:
智能、算法、系统工程
出版日期:
2020-05-10

文章信息/Info

Title:
Intelligent Survey Car Based on Laser SLAM Vision for ROS System
文章编号:
1673-629X(2020)05-0084-04
作者:
许志明1 ; 张秉天1 ; 邹嘉俊1 ; 王 凤1 ; 鲁鹏程1 ; 倪伟传2*
1. 中山大学新华学院 信息科学学院,广东 广州 510520; 2. 中山大学新华学院 设备与实验室管理处,广东 广州 510520
Author(s):
XU Zhi-ming1 ; ZHANG Bing-tian1 ; ZOU Jia-jun1 ; WANG Feng1 ; LU Peng-cheng1 ; NI Wei-chuan2*
1. School of Information Science,Xinhua College,Sun Yat-sen University,Guangzhou 510520,China; 2. Department of Equipment and Laboratory Management,Xinhua College,Sun Yat-sen University,Guangzhou 510520,China
关键词:
智能小车; SLAM; ROS; 地图构建
Keywords:
smart car; SLAM; ROS; map construction
分类号:
TP39
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 05. 016
摘要:
对于目前常用的定位系统( 例如GPS),在存在遮挡条件或者在室内执行任务时,往往会出现定位不准,无法识别区域位置等问题,这使得机器人在移动过程中无法正确地进行判断,很可能无法移动至目的地。针对移动机器人在未知环境下的定位不准,无法识别区域位置等问题,设计了一个 ROS 系统的激光 SLAM 视觉智能勘察小车, 通过结合激光SLAM 与深度摄像头,提升小车的数据采集能力,并结合 ROS 系统的图形化模拟环境,对智能小车的位置进行估计并构建地图,实现了小车的自主定位和导航。经测试,在室内或遮蔽环境下相比采用传统雷达 SLAM 或视觉 SLAM 具有更高的定位精度,并且反应快,可以进行实时地图构建,解决了在遮挡条件或者在室内执行任务时出现的问题,使得机器人在地图构建之后能够准确进行判断前往目的地。
Abstract:
For the commonly used positioning system,such as GPS, in the presence of occlusion conditions or when performing tasks indoors,there are often problems such as inaccurate positioning and inability to identify the position of the area,which makes the robot unable to correctly judge during the movement and probably unable to move to the destination. Aiming at the problem that the mobile robot is not positioned in the unknown environment and cannot identify the location of the area,a laser SLAM visual intelligent survey vehicle of ROS system is designed. By combining the laser SLAM and the depth camera,the data acquisition capability of the car is improved,and by combining with the graphical simulation environment of the ROS system,the location of the smart car is estimated and the map is constructed,so as to realize the autonomous positioning and navigation of the car. Compared with traditional radar SLAM or visual SLAM in indoor or shelter environment,it has higher positioning accuracy and faster response,and can be used for real-time map construction,which solves the problems in occlusion conditions or indoor tasks. So that the robot can accurately judge the destination after the map is built.

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更新日期/Last Update: 2020-05-10