Determining Motion States

• US 20120309412A1
• Filed: 06/03/2011
• Published: 12/06/2012
• Est. Priority Date: 06/03/2011
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: MacGougan, Glenn Donald, Mayor, Robert, Huang, Ronald K.
• Granted Patent: US 8,892,390 B2
• Time in Patent Office: Days
• US Class Current: 455/456.1
• CPC Class Codes: G01P 15/00 Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
• CPC Class Codes: G01P 15/08 with conversion into electric or magnetic values
• CPC Class Codes: G06F 1/1694 the I/O peripheral being a single or a set of motion sensors for pointer control or gesture input obtained by sensing movements of the portable computer
• CPC Class Codes: G06F 3/0346 with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
• CPC Class Codes: G06F 3/038 Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry
• CPC Class Codes: H04W 64/006 with additional information processing, e.g. for direction or speed determination

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a motion state of a mobile device. Accelerometer data is received from accelerometer sensors onboard the mobile device, wherein the accelerometer data represents acceleration of the mobile device in three-dimensional space. An accelerometer signal vector representing at least a force due to gravity on the mobile device is determined. Two-dimensional accelerometer data orthogonal to the accelerometer signal vector is calculated. A motion state of the mobile device is determined based on the two-dimensional accelerometer data.

Claims

1. A method performed by a mobile device, the method comprising:

receiving accelerometer data from accelerometer sensors onboard the mobile device, wherein the accelerometer data represents acceleration of the mobile device in three-dimensional space;

determining an accelerometer signal vector representing at least a force due to gravity on the mobile device;

calculating two-dimensional accelerometer data orthogonal to the accelerometer signal vector; and

determining a motion state of the mobile device based on the two-dimensional accelerometer data.

2. The method of claim 1, wherein the accelerometer data is comprised of a time series vector of tri-axial accelerometer samples.

3. The method of claim 2, wherein determining an accelerometer signal vector includes:

dividing the time series vector of tri-axial accelerometer samples into a first and second part, each of the first and second parts including at least a threshold number of discrete sensor samples;

determining the accelerometer signal vector based on vector components of a gravity signal contained in the accelerometer samples of the first part; and

identifying an orthogonal plane corresponding to the accelerometer signal vector, the orthogonal plane orthogonal to the accelerometer signal vector.

4. The method of claim 3, wherein the accelerometer signal vector includes vector components of accelerometer sensor bias present on each axis of the tri-axial accelerometer samples.

5. The method of claim 3, wherein calculating two-dimensional accelerometer data includes:

computing a roll angle and a pitch angle required to rotate the accelerometer signal vector to substantially align with a vertical axis of the accelerometer samples; and

rotating vectors representing each of the accelerometer samples in the second part by the computed roll and pitch angles such that the accelerometer signal vector is substantially aligned with the vertical axis and the orthogonal plane is orthogonal to the vertical axis.

6. The method of claim 5, wherein determining the motion state of the mobile device includes:

identifying values of vector components of the rotated accelerometer samples in the orthogonal plane;

integrating the values of the vector components over a duration of the second part;

determining that the mobile device has at least a horizontal movement motion state if the integrated values exceed a horizontal motion threshold value;

identifying a variance in the vertical axis of the accelerometer samples; and

determining that the mobile device has at least a vertical movement motion state if the variance in the vertical axis exceeds a vertical motion threshold value.

7. The method of claim 1 further comprising using a speed of the mobile device calculated based on global navigation satellite system signals to verify the determined motion state of the mobile device.

8. The method of claim 1 further comprising assigning a confidence level associated with the determined motion state of the mobile device based on one or more previous determinations of motion state of the mobile device.

9. A computer program product tangibly embodied in a computer-readable storage medium, the computer program product including instructions that, when executed, perform the following operations:

receiving accelerometer data from accelerometer sensors onboard the mobile device, wherein the accelerometer data represents acceleration of the mobile device in three-dimensional space;

determining an accelerometer signal vector representing at least a force due to gravity on the mobile device;

calculating two-dimensional accelerometer data orthogonal to the accelerometer signal vector; and

determining a motion state of the mobile device based on the two-dimensional accelerometer data.

10. The computer program product of claim 9, wherein the accelerometer data is comprised of a time series vector of tri-axial accelerometer samples.

11. The computer program product of claim 10, wherein determining an accelerometer signal vector includes:

dividing the time series vector of tri-axial accelerometer samples into a first and second part, each of the first and second parts including at least a threshold number of discrete sensor samples;

determining the accelerometer signal vector based on vector components of a gravity signal contained in the accelerometer samples of the first part; and

identifying an orthogonal plane corresponding to the accelerometer signal vector, the orthogonal plane orthogonal to the accelerometer signal vector.

12. The computer program product of claim 11, wherein calculating two-dimensional accelerometer data includes:

computing a roll angle and a pitch angle required to rotate the accelerometer signal vector to substantially align with a vertical axis of the accelerometer samples; and

rotating vectors representing each of the accelerometer samples in the second part by the computed roll and pitch angles such that the accelerometer signal vector is substantially aligned with the vertical axis and the orthogonal plane is orthogonal to the vertical axis.

13. The computer program product of claim 12, wherein determining the motion state of the mobile device includes:

identifying values of vector components of the rotated accelerometer samples in the orthogonal plane;

integrating the values of the vector components over a duration of the second part;

determining that the mobile device has at least a horizontal movement motion state if the integrated values exceed a horizontal motion threshold value;

identifying a variance in the vertical axis of the accelerometer samples; and

determining that the mobile device has at least a vertical movement motion state if the variance in the vertical axis exceeds a vertical motion threshold value.

14. The computer program product of claim 9 further comprising using a speed of the mobile device calculated based on global navigation satellite system signals to verify the determined motion state of the mobile device.

15. The computer program product of claim 9 further comprising assigning a confidence level associated with the determined motion state of the mobile device based on one or more previous determinations of motion state of the mobile device.

16. A mobile device comprising:

accelerometer sensors operable to receive accelerometer data, wherein the accelerometer data represents acceleration of the mobile device in three-dimensional space;

a motion detector module operable to determine an accelerometer signal vector representing at least a force due to gravity on the mobile device, calculate two-dimensional accelerometer data orthogonal to the accelerometer signal vector, and determine a motion state of the mobile device based on the two-dimensional accelerometer data.

17. The mobile device of claim 16, wherein the accelerometer data is comprised of a time series vector of tri-axial accelerometer samples.

18. The mobile device of claim 16, wherein determining an accelerometer signal vector includes:

dividing the time series vector of tri-axial accelerometer samples into a first and second part, each of the first and second parts including at least a threshold number of discrete sensor samples;

determining the accelerometer signal vector based on vector components of a gravity signal contained in the accelerometer samples of the first part; and

identifying an orthogonal plane corresponding to the accelerometer signal vector, the orthogonal plane orthogonal to the accelerometer signal vector.

19. The mobile device of claim 18, calculating two-dimensional accelerometer data includes:

computing a roll angle and a pitch angle required to rotate the accelerometer signal vector to substantially align with a vertical axis of the accelerometer samples; and

rotating vectors representing each of the accelerometer samples in the second part by the computed roll and pitch angles such that the accelerometer signal vector is substantially aligned with the vertical axis and the orthogonal plane is orthogonal to the vertical axis.

20. The mobile device of claim 19, wherein determining the motion state of the mobile device includes:

identifying values of vector components of the rotated accelerometer samples in the orthogonal plane;

integrating the values of the vector components over a duration of the second part;

determining that the mobile device has at least a horizontal movement motion state if the integrated values exceed a horizontal motion threshold value;

identifying a variance in the vertical axis of the accelerometer samples; and

determining that the mobile device has at least a vertical movement motion state if the variance in the vertical axis exceeds a vertical motion threshold value.