Systems and methods for deep learning-based pedestrian dead reckoning for exteroceptive sensor-enabled devices
Abstract:
Systems are provided for estimating 6DOF positioning of a computing device while in a pedestrian dead reckoning mode. The systems obtain a set of inertial tracking data from the set of one or more inertial tracking components while the system is in a pedestrian dead reckoning mode. Then, the systems obtain an estimated 3DOF velocity of the system based inertial tracking data, using a predictive model trained on a set of observed exteroceptive sensor data and observed inertial tracking data. The systems also obtain estimated 6DOF positioning of the systems based on the estimated 3DOF velocity.
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