[1]秦国威,孙新柱,陈孟元.基于WIFI指纹定位的仿生SLAM研究[J].智能系统学报,2018,13(3):407-413.[doi:10.11992/tis.201705020]
QIN Guowei,SUN Xinzhu,CHEN Mengyuan.Bio-inspired SLAM fingerprint location based on WIFI[J].CAAI Transactions on Intelligent Systems,2018,13(3):407-413.[doi:10.11992/tis.201705020]
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QIN Guowei,SUN Xinzhu,CHEN Mengyuan.Bio-inspired SLAM fingerprint location based on WIFI[J].CAAI Transactions on Intelligent Systems,2018,13(3):407-413.[doi:10.11992/tis.201705020]
基于WIFI指纹定位的仿生SLAM研究
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
13
期数:
2018年第3期
页码:
407-413
栏目:
学术论文—智能系统
出版日期:
2018-05-05
- Title:
- Bio-inspired SLAM fingerprint location based on WIFI
- Keywords:
- wireless signal network; rodent model; position fingerprinting; simultaneous localization and mapping; template matching; experience drawing; accuracy rate; accuracy precision
- 分类号:
- TP242.6;TN92
- 摘要:
- 针对复杂室内环境下移动机器人的定位问题，基于RatSLAM模型的定位方法，由于室内环境的复杂性及易变性，定位精度及准确性很难得到保证。本文基于此提出RatSLAM和WIFI相结合的策略，利用基于WIFI信号强度的指纹识别方法，离线阶段建立位置指纹数据库，在线定位阶段采用位置指纹定位算法完成认知点的匹配，从局部场景中获取更加精确的经历制图。实验分析表明：两种算法的结合使得移动机器人的定位精确度更高，提高了系统的鲁棒性，使系统具备了良好的定位性能。
- Abstract:
- From the viewpoint of localization of mobile robots in complex indoor environments, it is difficult to guarantee the localization accuracy of the RatSLAM model owing to the complexity and variability of indoor environments. In this paper, the authors propose a strategy of combining RatSLAM and WIFI by utilizing the fingerprint recognition method based on WIFI signal strength. To this end, a position fingerprint database is established in the offline stage, and the position fingerprint localization algorithm is used to match the cognitive points in the online positioning stage to obtain more accurate experience mapping of a local scene. The experimental results show that the combination of the two algorithms can increase the positioning accuracy of a mobile robot and improve system robustness, thereby providing good positioning performance.
- 参考文献/References:
-
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备注/Memo
收稿日期:2017-05-16。
基金项目:安徽省高校优秀青年人才支持计划项目（gxyqZD2018050）.
作者简介:秦国威,男,1994年生,硕士研究生,主要研究方向为机器视觉和仿生导航算法;孙新柱,男,1974年生,副教授,主要研究方向为运动控制系统分析与设计、智能机器人运动控制。主持多项省级自然科学研究项目,获安徽省教学成果二等奖1项、安徽省科技进步三等奖1项。发表学术论文20余篇;陈孟元,男,1984年生,副教授,主要研究方向为移动机器人地图构建及同步定位。主持安徽省高等学校自然科学研究项目10余项,授权国家发明专利4项。发表学术论文30余篇。
通讯作者:孙新柱.E-mail:xzsun@ahpu.edu.cn.
更新日期/Last Update:
2018-06-25