An Indoor Mobile Localization Strategy for Robot in NLOS Environment

Author:

Wang Yan1,Jing Yuanwei1,Jia Zixi1

Affiliation:

1. The School of Information Science and Engineering, Northeastern University, Shenyang 110819, China

Abstract

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.

Funder

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Computer Networks and Communications,General Engineering

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