Electronic device for estimating relative position and pose and operating method of the same
US-2024004024-A1 · Jan 4, 2024 · US
US10274318B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-10274318-B1 |
| Application number | US-201414502174-A |
| Country | US |
| Kind code | B1 |
| Filing date | Sep 30, 2014 |
| Priority date | Sep 30, 2014 |
| Publication date | Apr 30, 2019 |
| Grant date | Apr 30, 2019 |
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A system for determining and correcting a calculated orientation of a computing device based on data from an accelerometer and a gyroscope. The system utilizes a modified Kalman filter that updates covariance to reduce decay over time based on a residual of the filter. Gyroscope bias is tracked and offset based on the updated covariance and the residual. The residual is based on an observational orientation determined from an angle between a measured acceleration vector and an expected acceleration vector, rotating a predicted frame based on the angle.
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What is claimed is: 1. A computing device comprising: at least one processor; a gyroscope; an accelerometer; and at least one memory including instructions that, when executed by the at least one processor, cause the device to: determine a linear approximation of a measured rotation of the device based on first data from the gyroscope; determine a predicted covariance based on the linear approximation and a previous covariance; determine a measurement residual quantifying a discrepancy between a predicted orientation of the computing device based on the first data and a frame rotation that rotates the predicted orientation based on second data from the accelerometer; determine a covariance of a Kalman filter based on the predicted covariance, the measurement residual, and a gain of the Kalman filter; and determine an estimate of an orientation of the computing device relative to an Earth reference frame based at least in part on the covariance of the Kalman filter. 2. The computing device of claim 1 , wherein the at least one memory further includes instructions that, when executed by the at least one processor, further cause the device to: determine a bias offset for the gyroscope based on the covariance and the measurement residual, wherein the linear approximation on a next determination of the estimate of the orientation is based on a combination of the first data from the gyroscope and the bias offset. 3. The computing device of claim 1 , wherein the at least one memory further includes instructions that, when executed by the at least one processor, further cause the device to: determine the gain of the Kalman filter in accordance with: K t = R - 1 trace ( P ~ t | t - 1 / R ) * R - 1 * P ~ t | t - 1 * R - 1 wherein K t is the gain, {tilde over (P)} t|t-1 is the predicted covariance, and R is a first diagonal four-by-four matrix with diagonal values corresponding to a variance of the accelerometer. 4. The computing device of claim 3 , wherein the at least one memory further includes instructions that, when executed by the at least one processor, further cause the device to: initialize the predicted covariance {tilde over (P)} t|t-1 on a first determination of the estimate of the orientation to a second diagonal four-by-four matrix with diagonal values “m,” wherein 0<m<0.02. 5. The computing device of claim 1 , wherein the instructions determine the linear approximation in accordance with: A = ( I + 1 2 [ 0 - ω x - ω y - ω z ω x 0 ω z - ω y ω y - ω z 0 ω x ω z
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