Geomagnetic field-based localization with bicubic interpolation for mobile robots

This paper proposes a novel geomagnetic field-based SLAM (simultaneous localization and mapping) technique for application to mobile robots. SLAM is an essential technique for mobile robots such as robotic vacuum cleaners to perform their missions autonomously. For practical application to commercialized robotic vacuum cleaners, the SLAM techniques should be implemented with low-priced sensors and low-computational complexity. Most building structures produce distortions in the geomagnetic field and variation of the field over time occurs with extremely low frequency. The geomagnetic field is hence applicable to mobile robot localization. The proposed geomagnetic field SLAM uses only the geomagnetic field signals and odometry data to estimate the robot state and the geomagnetic field signal distribution with low computational cost. To estimate the signal strength of the geomagnetic field, bicubic interpolation, an extension of cubic interpolation for interpolating surfaces on a regular grid, is used. The proposed approach yields excellent results in simulations and experiments in various indoor environments.

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