Game console and gaming object with motion prediction modeling and methods for use therewith

• US 9,943,760 B2
• Filed: 11/08/2016
• Issued: 04/17/2018
• Est. Priority Date: 06/22/2007
• Status: Active Grant

• Current Assignee: Avago Technologies International Sales Pte Limited (Broadcom, Inc.)
• Original Assignee: Avago Technologies General IP PTE Limited (Broadcom, Inc.)
• Inventors: Rofougaran, Ahmadreza (Reza), Rofougaran, Maryam, Seshadri, Nambirajan, Ibrahim, Brima B., Walley, John, Karaoguz, Jeyhan
• Primary Examiner(s): Shah, Milap
• Assistant Examiner(s): PINHEIRO, JASON PAUL
• Application Number:
  US15/346,254
• Publication Number:
  US 20170232345A1
• Time in Patent Office: 525 Days
• 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 13/213 comprising photodetecting means, e.g. cameras, photodiodes or infrared cells A63F13/219, A63F13/655 take precedence
• CPC Class Codes: A63F 13/235 using a wireless connection, e.g. infrared or piconet
• CPC Class Codes: A63F 13/57 Simulating properties, behaviour or motion of objects in the game world, e.g. computing tyre load in a car race game A63F13/56 takes precedence
• CPC Class Codes: A63F 13/573 using trajectories of game objects, e.g. of a golf ball according to the point of impact
• CPC Class Codes: A63F 13/825 Fostering virtual characters
• CPC Class Codes: A63F 2300/1012 involving biosensors worn by the player, e.g. for measuring heart beat, limb activity
• CPC Class Codes: A63F 2300/1031 using a wireless connection, e.g. Bluetooth, infrared connections
• CPC Class Codes: A63F 2300/5553 user representation in the game field, e.g. avatar
• CPC Class Codes: G01S 13/003 Bistatic radar systems; Multistatic radar systems
• CPC Class Codes: G01S 13/426 Scanning radar, e.g. 3D radar G01S13/66 takes precedence
• CPC Class Codes: G01S 13/723 by using numerical data
• CPC Class Codes: G01S 13/878 Combination of several spaced transmitters or receivers of known location for determining the position of a transponder or a reflector G01S13/874 takes precedence
• CPC Class Codes: G01S 7/412 based on a comparison between measured values and known or stored values
• CPC Class Codes: G06F 3/011 Arrangements for interaction with the human body, e.g. for user immersion in virtual reality blind teaching G09B21/00
• CPC Class Codes: G06F 3/012 Head tracking input arrangements
• 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 3/045 using resistive elements, e.g. a single continuous surface or two parallel surfaces put in contact

Abstract

A game console includes a receiver that receives motion data in response to motion of a gaming object. A trajectory generation module generates trajectory data based on the motion data and based on a motion prediction model. A processor executes a gaming application based on the trajectory data to generate display data.

Claims

1. A game device comprising:

trajectory generation circuitry configured to generate trajectory data based on motion data of a gaming object and based on a motion prediction model that determines a type of motion based on a game selection signal that indicates selection of one of a plurality of games, wherein the motion prediction model further determines a family of trajectories corresponding to the type of motion, and wherein the motion prediction model selects one trajectory of the family of trajectories that fits the motion data; and

a processor, coupled to the trajectory generation circuitry, configured to execute a gaming application based on the game selection signal and the trajectory data to generate display data.

2. The game device of claim 1 wherein the motion prediction model represents a biomechanical trajectory of a user of the gaming device in accordance with a game.

3. The game device of claim 2 further comprising:

model generation circuitry, coupled to the trajectory generation circuitry, configured to generate the motion prediction model based on a game selection signal that indicates the game.

4. The game device of claim 1

wherein the trajectory generation circuitry generates the trajectory data by interpolating the motion data based on the motion prediction model.

5. The game device of claim 1 wherein the motion data include a plurality of model parameters of the motion prediction model.

6. The game device of claim 5 wherein the motion prediction model includes a polynomial trajectory and the plurality of model parameters include a plurality of polynomial coefficients.

7. The game device of claim 1

wherein the motion data include differential motion data and wherein the trajectory generation circuitry generates a current position based on a prior position and further based on the differential motion data.

8. A mobile communication device comprising:

a motion sensor configured to generate motion signals in response to motion of the mobile communication device;

motion data generation circuitry configured to generate motion data based on the motion signal of a gaming object and based on a motion prediction model that determines a type of motion based on a game selection signal that indicates selection of one of a plurality of games, wherein the motion prediction model further determines a family of trajectories corresponding to the type of motion, and wherein the motion prediction model selects one trajectory of the family of trajectories that fits the motion data; and

a transmitter, coupled to the motion data generation circuitry, that sends the motion data to a game device.

9. The mobile communication device of claim 8 wherein the motion sensor includes at least one of:

an accelerometer, an RFID tag and an on-chip gyrator.

10. The mobile communication device of claim 8 wherein the motion prediction model represents a biomechanical trajectory of a user of the mobile communication device in accordance with a game.

11. The mobile communication device of claim 8 further comprising a wireless transceiver for communicating voice signals and data with a wireless network.

12. The mobile communication device of claim 8 further comprising:

a model generation module, coupled to the motion data generation module, that selects a data rate for the motion data based on the game selection signal.

13. The mobile communication device of claim 8 wherein the motion data include a plurality of model parameters of the motion prediction model.

14. The mobile communication device of claim 13 wherein the motion prediction model includes a polynomial trajectory and the plurality of model parameters include a plurality of polynomial coefficients.

15. The mobile communication device of claim 8 wherein the motion data include differential motion data.

16. A method comprising:

generating motion data in response to motion of a gaming object;

generating, via trajectory generation circuitry, trajectory data based on the motion data of the gaming object and based on a motion prediction model that determines a type of motion based on a game selection signal that indicates selection of one of a plurality of games, wherein the motion prediction model further determines a family of trajectories that correspond to that type of motion corresponding to the type of motion, and wherein the motion prediction model selects one trajectory of the family of trajectories that fits the motion data; and

executing, via a processor, a gaming application based on the game selection signal and the trajectory data to generate display data.

17. The method of claim 16 wherein the motion prediction model represents a biomechanical trajectory of a user of the gaming object in accordance with a game.

18. The method of claim 16 wherein the trajectory data is generated by interpolating the motion data based on the motion prediction model.

19. The method of claim 16 wherein the motion data includes a plurality of model parameters of the motion prediction model.

20. The method of claim 19 wherein the motion prediction model includes a polynomial trajectory and the plurality of model parameters include a plurality of polynomial coefficients.