Invention Grant
- Patent Title: Systems and methods for deep learning-based pedestrian dead reckoning for exteroceptive sensor-enabled devices
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Application No.: US16797798Application Date: 2020-02-21
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Publication No.: US11435185B2Publication Date: 2022-09-06
- Inventor: Evan Gregory Levine , Raymond Kirk Price
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Workman Nydegger
- Main IPC: G01C21/16
- IPC: G01C21/16 ; G06F3/0346 ; G01S5/02 ; G01S5/14 ; G02B27/01 ; G06N7/00 ; G06T19/00 ; H04W4/02

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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