Indoor Robot Localization Using Magnetometer Data
Lokalizace robotu za pomoci magnetometru
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České vysoké učení technické v Praze
Czech Technical University in Prague
Czech Technical University in Prague
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Magnetické pole v železobetonových budovách je často nehomogenní a lze ho využít k lokalizaci. Měření magnetometrem spolu s předem známou magnetickou mapou může zlepšit přesnost odometrie. Tato bakalářská práce se zabývá lokalizací pozemního mobilního robotu ve vnitřním prostředí za pomoci magnetometru. V první části ukážeme, jak je možné zaznamenat nehomogenitu magnetického pole uvnitř budov. Naměření datasetu a jeho konverze na magnetickou mapu jsou klíčové pro možnou lokalizaci. Ve druhé části navrhneme a implementujeme lokalizaci v magnetickém poli jakožto optimalizační úlohu. Tato lokalizace využije již zmíněné magnetické mapy k úpravě odometrie.
The magnetic field in reinforced concrete buildings is often inhomogeneous and can be used for localization. Magnetometer measurements along with a previously known magnetic map can improve the odometry accuracy. This bachelor thesis deals with the localization of the ground mobile robot in the indoor environment using a magnetometer. In the first part, we demonstrate how it is possible to record the inhomogeneity of the magnetic field inside buildings. Measuring the dataset and converting it into a magnetic map is necessary for possible localization. In the second part, we design and implement localization in a magnetic field as an optimization problem. This localization uses the already mentioned magnetic maps to adjust the odometry.
The magnetic field in reinforced concrete buildings is often inhomogeneous and can be used for localization. Magnetometer measurements along with a previously known magnetic map can improve the odometry accuracy. This bachelor thesis deals with the localization of the ground mobile robot in the indoor environment using a magnetometer. In the first part, we demonstrate how it is possible to record the inhomogeneity of the magnetic field inside buildings. Measuring the dataset and converting it into a magnetic map is necessary for possible localization. In the second part, we design and implement localization in a magnetic field as an optimization problem. This localization uses the already mentioned magnetic maps to adjust the odometry.