WiFi SLAM algorithms: an experimental comparison

被引：11

作者：

Herranz, F. ^{[1
]}

Llamazares, A. ^{[1
]}

Molinos, E. ^{[1
]}

Ocana, M. ^{[1
]}

Sotelo, M. A. ^{[2
]}

机构：

[1] Univ Alcala de Henares, Polytech Sch, Dept Elect, Univ Campus, Madrid 28871, Spain

[2] Univ Alcala de Henares, Polytech Sch, Dept Comp Engn, Univ Campus, Madrid 28871, Spain

来源：

ROBOTICA | 2016年 / 34卷 / 04期

关键词：

WiFi; SLAM; SAM; Indoor;

D O I：

10.1017/S0263574714001908

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

Localization and mapping in indoor environments, such as airports and hospitals, are key tasks for almost every robotic platform. Some researchers suggest the use of Range-Only (RO) sensors based on WiFi (Wireless Fidelity) technology with SLAM (Simultaneous Localization And Mapping) techniques to solve both problems. The current state of the art in RO SLAM is mainly focused on the filtering approach, while the study of smoothing approaches with RO sensors is quite incomplete. This paper presents a comparison between filtering algorithms, such as EKF and FastSLAM, and a smoothing algorithm, the SAM (Smoothing And Mapping). Experimental results are obtained in indoor environments using WiFi sensors. The results demonstrate the feasibility of the smoothing approach using WiFi sensors in an indoor environment.

引用

页码：837 / 858

页数：22

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