System and Method for Determining Motion

• US 20130138413A1
• Filed: 11/24/2012
• Published: 05/30/2013
• Est. Priority Date: 11/24/2011
• Status: Abandoned Application

• Current Assignee: Auckland UniServices Limited (Auckland University)
• Original Assignee: Auckland UniServices Limited (Auckland University)
• Inventors: Finch, Mark Christopher, Lintern, Thomas Oliver, Nielsen, Poul, Taberner, Andrew James
• Application Number:
  US13/684,506
• Publication Number:
  US 20130138413A1
• Time in Patent Office: Days
• US Class Current: 703/6
• CPC Class Codes: A63B 2024/0015 Comparing movements or motion sequences with computerised simulations of movements or motion sequences, e.g. for generating an ideal template as reference to be achieved by the user
• CPC Class Codes: A63B 24/0006 Computerised comparison for qualitative assessment of motion sequences or the course of a movement
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

A method of generating model motion data representing the predicted motion of a physical system based on sensed motion data from one or more motion sensors within the physical system. The method generates a stream of model motion data representing the predicted motion of the physical system based on a dynamic motion model of the physical system based on initial estimates of system parameters. The method then optimizes the system parameters of the dynamic motion model based on processing of the streams of model motion data and sensed motion data from one or more motion sensors within the physical system.

Claims

1. A method of generating model motion data representing the predicted motion of a physical system based on sensed motion data from one or more motion sensors within the physical system, comprising:

generating a stream of model motion data representing the predicted motion of the physical system based on a dynamic motion model of the physical system which comprises initial estimates of system parameters;

receiving a stream of sensed motion data representing the measured motion within the physical system as sensed by the one or more motion sensors within the physical system;

optimizing the system parameters of the dynamic motion model based on processing of the streams of model motion data and sensed motion data; and

outputting the model motion data from the dynamic motion model based on the optimized system parameters.

2. A method according to claim 1 wherein the dynamic motion model of the physical system comprises a physical system model defined by equations of motion corresponding to the physical system.

3. A method according to claim 1 wherein generating model motion data comprises solving the equations of motion of the physical system model to generate one or more time-dependent model motion data variables.

4. A method according to claim 3 wherein the model motion data variables represent any position and/or orientation parameter relating to the motion within the physical system.

5. A method according to claim 1 wherein the physical system comprises one or more motion sensors located or mounted on moving features within the physical system and which are configured to sense or measure motion of those moving features within the physical system to generate sensed motion data.

6. A method according to claim 5 wherein each motion sensor comprises:

an accelerometer configured to sense acceleration and generate sensed motion data variables representing acceleration within the physical system;

a magnetometer configured to sense magnetic field strength and generate sensed motion data variables representing magnetic field strength within the physical system; and

a gyroscope configured to sense angular velocity and generate sensed motion data variables representing angular velocity within the physical system.

7. A method according to claim 1 wherein the dynamic motion model of the physical system further comprises a motion sensor relationship model that is configured to model the relationship between the model motion data from the physical system model and the sensed motion data from the one or more motion sensors.

8. A method according to claim 1 wherein optimizing the system parameters of the dynamic motion model comprises applying an objective function to the stream of model motion data and sensed motion data to generate optimized system parameters.

9. A method according to claim 8 wherein optimizing the system parameters comprises continuously or periodically optimizing the system parameters based on the continuous streams of model motion data and sensed motion data.

10. A motion assessment system for generating model motion data representing the predicted motion within a physical system, comprising:

a dynamic motion model sub-system that is configured to generate a stream of model motion data representing the predicted motion of the physical system based on a dynamic motion model of the physical system, the dynamic motion model being configured by model configuration data defining the dynamic motion model of the physical system being assessed and initial estimates of model system parameters;

one or more motion sensors within the physical system that are configured to measure motion within the physical system and generate a stream of sensed motion data representing the measured motion; and

an optimization sub-system configured to receive and process the streams of model motion data and sensed motion data so as to optimize the model system parameters of the dynamic motion model to improve the accuracy of the model motion data.

11. A motion assessment system according to claim 10 wherein the physical system comprises one or more motion sensors located or mounted on moving features within the physical system and which are configured to sense or measure motion of those moving features within the physical system to generate sensed motion data.

12. A motion assessment system according to claim 11 wherein the sensed motion data represents one or more sensed motion data variables representing motion within the physical system.

13. A motion assessment system according to claim 11 wherein each motion sensor comprises:

an accelerometer configured to sense acceleration and generate sensed motion data variables representing acceleration within the physical system;

a magnetometer configured to sense magnetic field strength and generate sensed motion data variables representing magnetic field strength within the physical system; and

a gyroscope configured to sense angular velocity and generate sensed motion data variables representing angular velocity within the physical system.

14. A motion assessment system according to claim 11 wherein each motion sensor comprises a global positioning system (GPS) sensor or module that is configured to sense position and/or linear velocity and generate sensed motion data variables representing the position and/or linear velocity within the physical system.

15. A motion assessment system according to claim 11 wherein each motion sensor is an accelerometer sensor, magnetometer sensor, gyroscope sensor, or GPS sensor, either alone or in any combination, and each sensor is configured to measure along 1, 2, or 3 axes, and where the axes are typically orthogonal to each other.

16. A motion assessment system according to claim 11 wherein the model configuration data defines a dynamic motion model comprising:

a physical system model that is configured to generate the model motion data representing the predicted motion of the physical system; and

a motion sensor relationship model that is configured to define the relationship between the model motion data of the physical system model and the sensed motion data from the motion sensor(s).

17. A motion assessment system according to claim 10 wherein the optimization sub-system is configured to apply an objective function to the model motion data and sensed motion data and generate optimized model system parameters that reduce any error between the motion as represented by the model motion data and sensed motion data.

18. A motion modeling device for modeling the motion of a physical system, comprising:

an input interface configured to receive a stream of sensed motion data from one or more motion sensors within the physical system that are configured to sense motion within the physical system;

a signal processor configured to generate a stream of model motion data representing the predicted motion within the physical system based on a dynamic motion model of the physical system, the dynamic motion model being configured by stored model configuration data defining the dynamic motion model of the physical system and stored initial estimates of system parameters within the dynamic motion model, the signal processor being configured to update the system parameters of the dynamic motion model with optimized system parameters generated based on processing of the streams of model motion data and sensed motion data;

memory configured to store system data used and processed by the signal processor; and

an output interface configured to output the model motion data.

19. A motion modeling device according to claim 18 wherein the signal processor is configured to continuously or periodically update the system parameters of the dynamic motion model with optimized system parameters.

20. A motion modeling device according to claim 18 wherein the signal processor is configured to apply an objective function to the streams of model motion data and sensed motion data and generate the optimized system parameters that reduce any error between the motion as represented by the model motion data and sensed motion data.