Automated Calibration of RSS Fingerprinting Based Systems Using a Mobile Robot and Machine Learning.

ABSTRACT: This paper describes an automated method for the calibration of RSS-fingerprinting-based positioning systems. The method assumes using a robotic platform to gather fingerprints in the system environment and using them for training machine learning models. The obtained models are used for positioning purposes during the system operation. The presented calibration method covers all steps of the system calibration, from mapping the system environment using a GraphSLAM based algorithm to training models for radio map calibration. The study analyses four different models: fitting a log-distance path loss model, Gaussian Process Regression, Artificial Neural Network and Random Forest Regression. The proposed method was tested in a BLE-based indoor localisation system set up in a fully furnished

SUBMITTER: Kolakowski M 

PROVIDER: S-EPMC8473432 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature