公开(公告)号：US10962371B2

公开(公告)日：2021-03-30

申请号：US16372788

申请日：2019-04-02

Applicant: GM Global Technology Operations LLC

Inventor： Lawrence A. Bush ,  Fan Bai ,  Pengfei Ren ,  Eric L. Raphael ,  Mohannad Murad ,  Mohammad Naserian

IPC: G01C21/16 ,  G01S19/49 ,  G01C21/32 ,  G06T7/70 ,  G01S17/86 ,  G01S17/93 ,  G01S17/931

Abstract: A method for vehicle tracking and localization includes receiving, by a controller, odometry data from a sensor of the first vehicle; geospatial data from a Global Positioning System (GPS) device of the first vehicle; inertial data from an inertial measurement unit (IMU) of the first vehicle; estimating an estimated-current location of the first vehicle and an estimated-current trajectory of the first vehicle using the odometry data from the sensor, the geospatial data from the GPS device, and the inertial data from the IMU of the first vehicle; inputting the inertial data into a Bayesian Network to determine a predicted location of the first vehicle and a predicted trajectory of the first vehicle, and updating the Bayesian Network using the estimated-current location and the estimated-current trajectory of the first vehicle using the odometry data and the geospatial data.

公开(公告)号：US20200318973A1

公开(公告)日：2020-10-08

申请号：US16372788

申请日：2019-04-02

Applicant: GM Global Technology Operations LLC

Inventor： Lawrence A. Bush ,  Fan Bai ,  Pengfei Ren ,  Eric L. Raphael ,  Mohannad Murad ,  Mohammad Naserian

IPC: G01C21/16 ,  G01S19/49 ,  G01C21/32 ,  G06T7/70 ,  G01S17/02 ,  G01S17/93

Abstract: A method for vehicle tracking and localization includes receiving, by a controller, odometry data from a sensor of the first vehicle; geospatial data from a Global Positioning System (GPS) device of the first vehicle; inertial data from an inertial measurement unit (IMU) of the first vehicle; estimating an estimated-current location of the first vehicle and an estimated-current trajectory of the first vehicle using the odometry data from the sensor, the geospatial data from the GPS device, and the inertial data from the IMU of the first vehicle; inputting the inertial data into a Bayesian Network to determine a predicted location of the first vehicle and a predicted trajectory of the first vehicle, and updating the Bayesian Network using the estimated-current location and the estimated-current trajectory of the first vehicle using the odometry data and the geospatial data.