An Indoor Mobile Localization Strategy for Robot in NLOS Environment | Zendy

Yan Wang | Zendy; Yuanwei Jing | Zendy; Zixi Jia | Zendy

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An Indoor Mobile Localization Strategy for Robot in NLOS Environment

Author(s) -

Yan Wang,

Yuanwei Jing,

Zixi Jia

Publication year - 2013

Publication title -

international journal of distributed sensor networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.324

H-Index - 53

eISSN - 1550-1477

pISSN - 1550-1329

DOI - 10.1155/2013/758749

Subject(s) - non line of sight propagation , computer science , identification (biology) , mobile robot , residual , robot , weighting , artificial intelligence , computer vision , real time computing , algorithm , wireless , telecommunications , medicine , botany , radiology , biology

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. © 2013 Yan Wang et al.

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