An Indoor Mobile Localization Strategy for Robot in NLOS Environment
Joint Authors
Jia, Zixi
Jing, Yuanwei
Wang, Yan
Source
International Journal of Distributed Sensor Networks
Issue
Vol. 2013, Issue - (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-01-14
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Telecommunications Engineering
Information Technology and Computer Science
Abstract EN
This paper deals with the problem of localization of mobile robot in indoor environment with mixed line-of-sight/nonline-of-sight (LOS/NLOS) conditions.
To reduce the NLOS errors, a prior knowledge-based correction strategy (PKCS) is proposed to locate the robot.
This strategy consists of two steps: NLOS identification and mitigation.
We propose an NLOS identification method by applying the statistical theory.
Then we correct the NLOS errors by subtracting the expected NLOS errors.
Finally, the residual weighting algorithm is employed to estimate the location of the robot.
Simulation results show that the proposed strategy significantly improves the accuracy of localization in mixed LOS/NLOS indoor environment.
American Psychological Association (APA)
Wang, Yan& Jing, Yuanwei& Jia, Zixi. 2013. An Indoor Mobile Localization Strategy for Robot in NLOS Environment. International Journal of Distributed Sensor Networks،Vol. 2013, no. -, pp.1-8.
https://search.emarefa.net/detail/BIM-496466
Modern Language Association (MLA)
Wang, Yan…[et al.]. An Indoor Mobile Localization Strategy for Robot in NLOS Environment. International Journal of Distributed Sensor Networks Vol. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-496466
American Medical Association (AMA)
Wang, Yan& Jing, Yuanwei& Jia, Zixi. An Indoor Mobile Localization Strategy for Robot in NLOS Environment. International Journal of Distributed Sensor Networks. 2013. Vol. 2013, no. -, pp.1-8.
https://search.emarefa.net/detail/BIM-496466
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-496466