Systems and methods for using a sliding window of global positioning epochs in visual-inertial odometry
First Claim
1. A method for visual inertial odometry (VIO)-aided global positioning, comprising:
- updating an extended Kalman filter (EKF) state comprising a current pose of an electronic device and a sliding window of multiple prior poses using measurements up to a current epoch, wherein the sliding window of multiple prior poses comprises poses of the electronic device at a number of most recent global positioning system (GPS) time epochs, wherein the updating comprises updating an EKF covariance matrix for the prior poses and the current pose in the EKF state;
determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose;
determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix;
using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs; and
controlling a vehicle based on the fused pseudorange measurements.
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Abstract
A method for visual inertial odometry (VIO)-aided global positioning is described. The method includes updating an extended Kalman filter (EKF) state including a current pose and a sliding window of multiple prior poses. The sliding window includes poses at a number of most recent global positioning system (GPS) time epochs. Updating the EKF includes updating an EKF covariance matrix for the prior poses and the current pose in the EKF state. The method also includes determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose. The method further includes determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix. The method additionally includes using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs.
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Citations
28 Claims
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1. A method for visual inertial odometry (VIO)-aided global positioning, comprising:
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updating an extended Kalman filter (EKF) state comprising a current pose of an electronic device and a sliding window of multiple prior poses using measurements up to a current epoch, wherein the sliding window of multiple prior poses comprises poses of the electronic device at a number of most recent global positioning system (GPS) time epochs, wherein the updating comprises updating an EKF covariance matrix for the prior poses and the current pose in the EKF state; determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose; determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix; using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs; and controlling a vehicle based on the fused pseudorange measurements. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. An electronic device for visual inertial odometry (VIO)-aided global positioning, comprising:
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a memory; a processor coupled to the memory, wherein the processor is configured to; update an extended Kalman filter (EKF) state comprising a current pose of the electronic device and a sliding window of multiple prior poses using measurements up to a current epoch, wherein the sliding window of multiple prior poses comprises poses of the electronic device at a number of most recent global positioning system (GPS) time epochs, wherein the updating comprises updating an EKF covariance matrix for the prior poses and the current pose in the EKF state; determine, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose; determine an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix; use the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs; and control a vehicle based on the fused pseudorange measurements. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A non-transitory tangible computer-readable medium storing computer executable code, comprising:
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code for causing an electronic device to update an extended Kalman filter (EKF) state comprising a current pose of the electronic device and a sliding window of multiple prior poses using measurements up to a current epoch, wherein the sliding window of multiple prior poses comprises poses of the electronic device at a number of most recent global positioning system (GPS) time epochs, wherein the updating comprises updating an EKF covariance matrix for the prior poses and the current pose in the EKF state; code for causing the electronic device to determine, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose; code for causing the electronic device to determine an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix; code for causing the electronic device to use the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs; and code for causing the electronic device to control a vehicle based on the fused pseudorange measurements. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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22. An apparatus, comprising:
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means for updating an extended Kalman filter (EKF) state comprising a current pose of the apparatus and a sliding window of multiple prior poses using measurements up to a current epoch, wherein the sliding window of multiple prior poses comprises poses of the apparatus at a number of most recent global positioning system (GPS) time epochs, wherein the updating comprises updating an EKF covariance matrix for the prior poses and the current pose in the EKF state; means for determining, at a GPS epoch, a relative displacement between each of the updated prior poses and the current pose; means for determining an error covariance of each of the relative displacements based on cross-covariances between each of the updated prior poses and the current pose in the EKF covariance matrix; means for using the relative displacements and the error covariances to fuse pseudorange measurements taken over multiple epochs; and means for controlling a vehicle based on the fused pseudorange measurements. - View Dependent Claims (23, 24, 25, 26, 27, 28)
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Specification