Indoor Self-Localization Using Multiple Magnetic Sensors | Zendy

Isaku Nagai | Zendy; Jun Sakai | Zendy; Keigo Watanabe | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Indoor Self-Localization Using Multiple Magnetic Sensors

Author(s) -

Isaku Nagai,

Jun Sakai,

Keigo Watanabe

Publication year - 2019

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.2019.p0203

Subject(s) - particle filter , gyroscope , computer vision , computer science , trajectory , position (finance) , artificial intelligence , matching (statistics) , map matching , filter (signal processing) , simultaneous localization and mapping , path (computing) , global positioning system , robot , mobile robot , physics , mathematics , telecommunications , statistics , finance , quantum mechanics , astronomy , programming language , economics

This study proposes an indoor self-localization for the estimation of the position and posture of an instrument using multiple magnetic sensors. First, a magnetic map for the localization is efficiently created using multiple sensors and a local positioning device made from an optical sensor and a gyroscope. For the localization estimating trajectories, the measurement error of the local positioning is corrected by matching it with the magnetic map. Our instrument is composed of six magnetic sensors, and the description of the self-localization details is based on the framework of a particle filter. The experimental results show better indoor path trajectories compared with a raw trajectory without map matching. The accuracy of the instrument using various numbers of magnetic sensors for the estimation is also investigated.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research