期刊文献+

基于机器人的室内指纹地图更新

Robot-based Indoor Fingerprint Map Update Method
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摘要 为满足大室内空间高精度指纹定位的需求,需采集大量的室内指纹地图数据,但传统室内指纹采集方法人工作业反复,费时费力;同时指纹地图还需频繁更新以保证更好的现势性从而得到更高的定位精度,更增加了在大室内空间中实现高精度指纹定位的难度。针对室内定位中的指纹地图采集提出了一种基于机器人的扫描采集更新方法。该方法不仅能大量节省人力成本,而且能高效地得到更丰富、更准确的指纹点信息以组成高质量的指纹地图,从而提高室内指纹定位的精度。 In order to meet the needs of high-precision fingerprint localization in large indoor space, we need to collect a large number of indoor fingerprint map data. But the classic collecting method of fingerprint map has a large consume in human resources and time. On the other hand, map should be updated with high frequency to get high-precision fingerprint localization. So it brings out the difficult for high-precision fingerprint localization in large indoor space. This paper proposed a new update method of fingerprint map based on robot. This method can not only save a lot of manpower, but conduct more efficiently to get fingerprint map with high quality. Compared with the classic fingerprint map collecting method, the method can get more high-precision fingerprint localization.
出处 《地理空间信息》 2018年第3期17-19,22,共4页 Geospatial Information
基金 国家重点研发计划资助项目(2016YFB0502202)
关键词 室内定位 移动机器人 指纹 更新 indoor location mobile robot fingerprint update
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  • 1亚瑟-阿尔法,蔡阁强,陈岳,劳里-卡瑟波特,陈绪,张天魁.Indoor Location Sensing Systems Based on Radio Channel Fingerprinting[J].China Communications,2011,8(8):1-12. 被引量:1
  • 2史伟光.基于射频识别技术的室内定位算法研究[D].天津:天津大学,2011. 被引量:6
  • 3Wu K S,Xiao J,Yi Y W,et al.CSIbased indoor localization[J].IEEE Transactions on Parallel and Distributed Systems,2013,24(7):1300-1309. 被引量:1
  • 4Niu J W,Lu B H,Cheng L,et al.ZiLoc:energy efficient WiFi fingerprintbased localization with lowpower radio[C]//Wireless Communications and Networking Conference (WCNC).Shanghai,2013:4558-4563. 被引量:1
  • 5Bahl P,Padmanabhan V N.RADAR:an inbuilding RFbased user location and tracking system[C]//International Conference on Computer Communications.Tel Aviv,2000,775-784. 被引量:1
  • 6Duvallet F,Tew A D.WiFi position estimation in industrial environments using Gaussian processes[C]//Intelligent Robots and Systems.Nice,2008:2216-2221. 被引量:1
  • 7Yim J,Jeong S,Gwon K,et al.Improvement of Kalman filters for WLAN based indoor tracking[J].Expert Systems with Applications,2009,37(6):426-433. 被引量:1
  • 8Gezici S.A survey on wireless position estimation[J].Wireless Personal Communications,2008,44(3):263-282. 被引量:1
  • 9Bergroth L,Hakonen H,Raita T.A survey of longest common subsequence algorithms[C]//String Processing and Information Retrieval.Curuna,2000:39-48. 被引量:1
  • 10Parvinnia E,Taheri M,Ziarati K.An improved longest common subsequence algorithm for reducing memory complexity in global alignment of DNA sequences[C]//Biomedical Engineering and Informatics.Sanya,2008:57-61. 被引量:1

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