Motion capture system that combines sensors with different measurement ranges

• US 9,626,554 B2
• Filed: 09/16/2016
• Issued: 04/18/2017
• Est. Priority Date: 08/26/2010
• Status: Active Grant

• Current Assignee: Newlight Capital, LLC
• Original Assignee: Blast Motion Incorporated
• Inventors: Lohr, Scott, Bose, Bhaskar, Gupta, Piyush
• Primary Examiner(s): Beck, Leron
• Application Number:
  US15/268,501
• Publication Number:
  US 20170004358A1
• Time in Patent Office: 214 Days
• Field of Search: 348 77
• CPC Class Codes: A63B 2024/0025 Tracking the path or location of one or more users, e.g. players of a game
• CPC Class Codes: A63B 2220/34 Angular speed
• CPC Class Codes: A63B 2220/40 Acceleration
• CPC Class Codes: A63B 2220/44 Angular acceleration
• CPC Class Codes: A63B 2220/803 Motion sensors
• CPC Class Codes: A63B 2220/806 Video cameras
• CPC Class Codes: A63B 2225/20 with means for remote communication, e.g. internet or the like
• CPC Class Codes: A63B 24/0003 Analysing the course of a movement or motion sequences during an exercise or trainings sequence, e.g. swing for golf or tennis
• CPC Class Codes: A63B 24/0021 Tracking a path or terminating locations
• CPC Class Codes: A63B 24/0062 Monitoring athletic performances, e.g. for determining the work of a user on an exercise apparatus, the completed jogging or cycling distance
• CPC Class Codes: A63B 69/36 for golf
• CPC Class Codes: A63F 13/211 using inertial sensors, e.g. accelerometers or gyroscopes
• CPC Class Codes: A63F 13/212 using sensors worn by the player, e.g. for measuring heart beat or leg activity
• CPC Class Codes: A63F 13/65 automatically by game devices or servers from real world data, e.g. measurement in live racing competition
• CPC Class Codes: A63F 13/812 Ball games, e.g. soccer or baseball
• CPC Class Codes: G06F 2218/10 by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
• 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: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 10/0833 Tracking
• CPC Class Codes: G06Q 50/01 : Social networking
• CPC Class Codes: G06T 7/251 : involving models
• CPC Class Codes: G06V 40/23 : Recognition of whole body movements, e.g. for sport training
• CPC Class Codes: G16H 20/30 : relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
• CPC Class Codes: G16H 30/20 : for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: H04M 1/72412 : using two-way short-range wireless interfaces
• CPC Class Codes: H04M 2250/12 : including a sensor for measuring a physical value, e.g. temperature or motion telephones including GPS signal receivers H04M2250/10
• CPC Class Codes: H04N 7/181 : for receiving images from a plurality of remote sources
• CPC Class Codes: H04N 7/186 : Video door telephones
• CPC Class Codes: Y04S 10/50 : Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

Abstract

Motion capture system with a motion capture element that uses two or more sensors to measure a single physical quantity, for example to obtain both wide measurement range and high measurement precision. For example, a system may combine a low-range, high precision accelerometer having a range of −24 g to +24 g with a high-range accelerometer having a range of −400 g to +400 g. Data from the multiple sensors is transmitted to a computer that combines the individual sensor estimates into a single estimate for the physical quantity. Various methods may be used to combine individual estimates into a combined estimate, including for example weighting individual estimates by the inverse of the measurement variance of each sensor. Data may be extrapolated beyond the measurement range of a low-range sensor, using polynomial curves for example, and combined with data from a high-range sensor to form a combined estimate.

Claims

1. A motion capture system that combines sensors with different measurement ranges comprising

a motion capture element comprising

a memory;

a plurality of sensors comprising at least two sensors that each measure the same physical quantity, wherein said physical quantity is equal to or is a function of one or more of a position, an orientation, a velocity, an acceleration, an angular velocity, or an angular acceleration of said motion capture element;

a first communication interface;

a microprocessor coupled with said memory, said plurality of sensors, and said first communication interface, wherein said microprocessor is configured to

collect sensor data from said plurality of sensors, wherein said sensor data comprises a sensor value from each sensor of said plurality of sensors;

store said sensor data in said memory;

transmit said sensor data to a computer via said first communication interface;

wherein

each sensor of said at least two sensors has a measurement range comprising a closed interval between a lower measurable value and an upper measurable value, said measurement range having an interior comprising a set of measurable values that are strictly greater than said lower measurable value and strictly less than said upper measurable value;

said measurement range associated with each sensor of said at least two sensors differs from the measurement range associated with at least one other sensor of said at least two sensors;

wherein said computer is configured to

receive said sensor data;

calculate an individual sensor estimate of said physical quantity from said sensor value associated with each sensor of said at least two sensors;

combine the individual sensor estimate across said at least two sensors to form a combined estimate of said physical quantity;

analyze a motion of said motion capture element based on said sensor data and on said combined estimate of said physical quantity.

2. The system of claim 1 wherein

said plurality of sensors comprises at least one rate gyroscope;

said at least two sensors that each measure the same physical quantity comprise a plurality of accelerometers.

3. The system of claim 2 wherein

a first accelerometer in said plurality of accelerometers has an upper measurable value of 24 g or lower.

4. The system of claim 3 wherein

a second accelerometer in said plurality of accelerometers has an upper measurable value of 100 g or higher.

5. The system of claim 2 wherein

a first accelerometer in said plurality of accelerometers has an upper measurable value of 16 g or lower.

6. The system of claim 5 wherein

a second accelerometer in said plurality of accelerometers has an upper measurable value of 400 g or higher.

7. The system of claim 1 wherein said combine the individual sensor estimate across said at least two sensors comprises

determine whether the sensor value associated with each sensor of said at least two sensors is in said interior of said measurement range associated with said each sensor;

when only one sensor value is in said interior of said measurement range, set said combined estimate of said physical quantity to said only one sensor value.

8. The system of claim 7 wherein said combine the individual sensor estimate across said at least two sensors further comprises

when multiple sensor values are in said interior of said measurement range for the associated sensor, set said combined estimate of said physical quantity to a sensor value associated with a sensor that has a finest measurement resolution.

9. The system of claim 7 wherein

each sensor of said at least two sensors has an associated measurement variance;

said combine the individual sensor estimate across said at least two sensors further comprises

when multiple sensor values are in said interior of said measurement range for the associated sensor, set said combined estimate of said physical quantity to a weighted average of said multiple sensor values, with weights inversely proportional to said measurement variance for the associated sensor.

10. The system of claim 9 wherein

said each sensor of said at least two sensors has an associated measurement resolution that represents a difference between successive measurement values of said each sensor;

said measurement variance is proportional to a square of said measurement resolution.

11. The system of claim 1 wherein one or both of said computer and said microprocessor are further configured to

track said sensor data over time;

analyze said sensor data over time to determine whether one or more sensors of said at least two sensors are out of calibration;

send a calibration required signal when said one or more sensors of said at least two sensors are out of calibration.

12. The system of claim 11 wherein said analyze said sensor data over time comprises perform a paired t-test on sensor data samples, wherein

each sensor data sample of said sensor data samples comprises

a first sensor value associated with a first sensor of said at least two sensors, wherein said first sensor value is in said interior of said measurement range of said first sensor;

a second sensor value associated with a second sensor of said at least two sensors, wherein said second sensor value is in said interior of said measurement range of said second sensor;

wherein said first sensor value and said second sensor value were measured at substantially the same time.

13. The system of claim 1 wherein said individual sensor estimate for a sensor of said at least two sensors is calculated as

said sensor value when said sensor value is in said interior of said measurement range of said sensor;

an extrapolated value based on extrapolation of one or more previous or subsequent sensor values in said interior of said measurement range when said sensor value is equal to said lower measurable value for said sensor or is equal to said upper measurable value for said sensor.

14. The system of claim 13 wherein said extrapolation fits a polynomial curve to said one or more previous or subsequent sensor values.

15. The system of claim 13 wherein said combine the individual sensor estimate across said at least two sensors comprises

set said combined estimate of said physical quantity to a weighted average of said multiple sensor values, wherein each individual sensor estimate has an associated weight;

when said individual sensor estimate is said extrapolated value, set said associated weight for said extrapolated value to a decreasing function of a distance between said extrapolated value and said measurement range of said sensor.

16. The system of claim 15 wherein said associated weight for said extrapolated value is zero when said distance between said extrapolated value and said measurement range of said sensor exceeds a threshold.