Nine-axis quaternion sensor fusion using modified kalman filter

US10274318B1 · US · B1

Patent metadata
FieldValue
Publication numberUS-10274318-B1
Application numberUS-201414502174-A
CountryUS
Kind codeB1
Filing dateSep 30, 2014
Priority dateSep 30, 2014
Publication dateApr 30, 2019
Grant dateApr 30, 2019

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

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.

First claim

Opening claim text (preview).

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

Assignees

Inventors

Classifications

  • G01C19/02Primary

    Rotary gyroscopes · CPC title

  • involving use of the magnetic field of the earth · CPC title

  • in two or more dimensions · CPC title

  • Gesture based interaction, e.g. based on a set of recognized hand gestures (interaction based on gestures traced on a digitiser G06F3/04883) · CPC title

  • G06F3/0346Primary

    with detection of the device orientation or free movement in a three-dimensional [3D] space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors · CPC title

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US10274318B1 cover?
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 observationa…
Who is the assignee on this patent?
Amazon Tech Inc
What technology area does this patent fall under?
Primary CPC classification G01C19/02. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Apr 30 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (B1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).