Augmented reality alignment system and method

Abstract

Various embodiments of an augmented reality alignment system and method are disclosed. An exemplary alignment system and method therefor may correct for image misalignment, distortion, and image deflection of graphic images that are projected within an operator's field of view. The alignment system may be configured to consider a number of dynamic and static error factor inputs in real time such that when a graphic image is projected, the graphic image is substantially aligned with the real-world target it is intended to overlay and the graphic image is displayed substantially free of distortion.

1 . An augmented reality alignment method, comprising the steps of:
 receiving a target position input;   receiving at least one first dynamic error factor input, said first dynamic error factor input including at least one of a curved mirror position input, an eye position input, a kinematics input, an orientation input, and a latency input;   determining a pixel position based on said target position input and at least one of said first dynamic error factor inputs;   generating a graphic output based on said pixel position;   receiving at least one second dynamic error factor input after generating said graphic output to correct said graphic output for distortion; and   receiving at least one static error factor input to correct said graphic output for distortion.   
     
     
         2 . The augmented reality alignment method of  claim 1 , wherein said first dynamic error factor input is the same type of error factor input as said second dynamic error factor input. 
     
     
         3 . The augmented reality alignment method of  claim 1 , wherein at least one of said static error factor inputs includes at least one of a windshield surface variation input, a mounting variation input, and a display unit optical variation input. 
     
     
         4 . The augmented reality alignment method of  claim 1 , wherein determining a pixel position based on said target position input and at least one of said first dynamic error factor inputs comprises the steps of:
 identifying a virtual display plane based on at least one of said first dynamic error factor inputs;   providing a target position based on said target position input;   providing an eye position based on said eye position input;   drawing a vector between said target position and said eye position; and   calculating an intersection point at a location where said vector intersects said virtual display plane, said intersection point having a corresponding pixel position.   
     
     
         5 . The augmented reality alignment method of  claim 4 , wherein a curved mirror position input is at least one of said first dynamic error factor inputs. 
     
     
         6 . The augmented reality alignment method of  claim 1 , wherein receiving at least one second dynamic error factor input to correct said graphic output for distortion comprises the steps of:
 providing at least one said second dynamic error factor input, including at least an eye position input;   determining a first driver eye position in which a driver's eyes are located based on said eye position input;   providing calibration data for at least one driver eye position of an eye box in which said driver's eyes are located;   providing predictive data for said at least one driver eye position;   combining said calibration data with said predictive data to calculate a distortion delta; and   shifting pixels of said graphic output to be projected at said first driver eye position by said distortion delta.   
     
     
         7 . The augmented reality alignment method of  claim 1 , wherein projecting said graphic output results in an image substantially aligned with said target with a position error of below about 0.5 degrees and substantially distortion free. 
     
     
         8 . The augmented reality alignment method of  claim 1 , wherein said second dynamic error factor inputs received to correct said graphic output for distortion include an eye position input and a latency input. 
     
     
         9 . An augmented reality alignment system, comprising:
 a processing unit, said processing unit having a memory, said memory including instructions executable by said processing unit, said instructions including instructions for:   receiving a target position input;   receiving at least one first dynamic error factor input, said first dynamic error factor input including at least one of a curved mirror position input, an eye position input, a kinematics input, an orientation input, and a latency input;   determining a pixel position, wherein determining said pixel position comprises:
 identifying a virtual display plane based on at least one of said first dynamic error factor inputs; 
 providing a target position based on said target position input; 
 providing an eye position based on said eye position input; 
 drawing a vector between said target position and said eye position; and 
 calculating an intersection point at a location where said vector intersects said virtual display plane, said intersection point having a corresponding pixel position; 
   generating a graphic output based on said pixel position;   receiving at least one second dynamic error factor input after generating said graphic output to correct said graphic output for distortion;   receiving at least one static error factor input to correct said graphic output for distortion.   
     
     
         10 . The augmented reality alignment system of  claim 9 , wherein said second dynamic error factor inputs received to correct said graphic output for distortion include an eye position input, a kinematics input, and a latency input. 
     
     
         11 . The augmented reality alignment system of  claim 9 , wherein said eye position is an actual position of a driver's eyes. 
     
     
         12 . The augmented reality alignment system of  claim 9 , wherein said eye position is an assumed eye position. 
     
     
         13 . The augmented reality alignment system of  claim 9 , wherein an orientation input is at least one of said first dynamic error factor inputs. 
     
     
         14 . The augmented reality alignment system of  claim 9 , wherein receiving at least one second dynamic error factor input to correct said graphic output for distortion; comprises:
 providing at least one said second dynamic error factor input, including at least an eye position input;   determining a first driver eye position in which a driver's eyes are located based on said eye position input;   providing calibration data for at least one driver eye position of an eye box in which said driver's eyes are located;   providing predictive data for said at least one driver eye position;   combining said calibration data with said predictive data to calculate a distortion delta; and   shifting pixels of said graphic output to be projected at said first driver eye position by said distortion delta.   
     
     
         15 . An augmented reality alignment system, comprising:
 a processing unit, said processing unit having a memory, said memory including instructions executable by said processing unit, said instructions including instructions for:   receiving a target position input;   receiving at least one first dynamic error factor input, said first dynamic error factor input including at least one of a curved mirror position input, an eye position input, a kinematics input, an orientation input, and a latency input;   determining a pixel position based on said target position input and at least one of said first dynamic error factor inputs;   generating a graphic output based on said pixel position;   receiving at least one second dynamic error factor input after generating said graphic output to correct said graphic output for distortion; and   receiving at least one static error factor input to correct said graphic output for distortion.   
     
     
         16 . The augmented reality alignment system of  claim 15 , wherein a curved mirror position input is at least one of said first dynamic error factor inputs. 
     
     
         17 . The augmented reality alignment system of  claim 15 , wherein said second dynamic error factor inputs include a kinematics input and a latency input. 
     
     
         18 . The augmented reality alignment system of  claim 15 , wherein said memory includes instructions for receiving at least one second dynamic error factor input to correct said graphic output for distortion, said instructions configured to execute the correction by:
 providing at least one said second dynamic error factor input, including at least an eye position input;   determining a first driver eye position in which a driver's eyes are located based on said eye position input;   providing calibration data for at least one driver eye position of an eye box in which said driver's eyes are located;   providing predictive data for said at least one driver eye position;   combining said calibration data with said predictive data to calculate a distortion delta; and   shifting pixels of said graphic output to be projected at said first driver eye position by said distortion delta.   
     
     
         19 . The augmented reality alignment system of  claim 15 , wherein determining a pixel position based on said target position input and at least one of said first dynamic error factor inputs comprises the steps of:
 identifying a virtual display plane based on at least one of said first dynamic error factor inputs;   providing a target position based on said target position input;   providing an eye position based on said eye position input;   drawing a vector between said target position and said eye position; and   calculating an intersection point at a location where said vector intersects said virtual display plane, said intersection point having a corresponding pixel position.   
     
     
         20 . The augmented reality alignment system of  claim 19 , wherein prior to drawing said vector between said target position and said eye position, said target position is adjusted to reflect a predicted target position.