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Measurement System for the Simulation of Indoor Magnetic Disturbances using a Robotic Arm

Massimo Stefanoni, Richárd Pesti, Ákos Odry, Peter Šarčević

Year
2023
Citations
6

Abstract

Magnetometer-based localization is a challenging task both in indoor and outdoor applications since their reliability depends on the environmental characteristics. The obtained geomagnetic field enables the estimation of both orientation and position if proper calibration and data fusion with inertial measurement units (IMUs), GPS and radio modules are executed. However, the distortions by hard and soft iron effects of both metallic objects and building structures requires additional data processing steps to obtain usable measurement data. This paper addresses the applicability of magnetometers for indoor mobile robot localization purposes. A measurement method is elaborated, which obtains the metallic objects-related disturbance characteristics with the help of both a robotic arm-based setup, which simulates the movement of the mobile robot, and data acquisition steps for the calculation of induced effects of disturbing objects. The experimental setup is applied to investigate four scenarios, namely, measurements with one simpler disturbing object either on the right or left side of the robot, with simpler disturbing objects on both sides, and with one complex object on one side of the robot. To extract the effect of the objects, the measurements collected with no additional object are subtracted from the measurements in the case of each scenario. The obtained measurement results clearly validate that incorporating the measurements of the undisturbed scenario enables the obtainment of the effect of disturbing objects. These results form the basis for the development of intelligent fusion algorithms of magneto-inertial sensors for mobile robot localization tasks.

Keywords

Sensor fusionComputer scienceRobotComputer visionMobile robotArtificial intelligenceGlobal Positioning SystemRobotic armOrientation (vector space)Object (grammar)

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