Techniques for Accurate Pose Estimation

• US 20170032528A9
• Filed: 08/21/2015
• Published: 02/02/2017
• Est. Priority Date: 08/22/2014
• Status: Active Grant

• Current Assignee: Applied Research Associates Incorporated
• Original Assignee: Applied Research Associates Incorporated
• Inventors: Menozzi, Alberico
• Granted Patent: US 9,767,574 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/1656 with passive imaging devices, e.g. cameras
• CPC Class Codes: G02B 2027/0138 comprising image capture systems, e.g. camera
• CPC Class Codes: G02B 2027/0141 characterised by the informative content of the display
• CPC Class Codes: G02B 2027/0181 Adaptation to the pilot/driver
• CPC Class Codes: G02B 27/0093 with means for monitoring data relating to the user, e.g. head-tracking, eye-tracking
• CPC Class Codes: G02B 27/017 Head mounted
• CPC Class Codes: G06F 1/163 Wearable computers, e.g. on a belt
• CPC Class Codes: G06F 11/00 Error detection; Error correction; Monitoring error detection, correction or monitoring in information storage based on relative movement between record carrier and transducer G11B20/18; monitoring, i.e. supervising the progress of recording or reproducing G11B27/36; in static stores G11C29/00
• CPC Class Codes: G06F 3/01 Input arrangements or combined input and output arrangements for interaction between user and computer G06F3/16 takes precedence
• 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 3/04817 using icons graphical or visual programming using iconic symbols G06F8/34
• CPC Class Codes: G06T 11/00 2D [Two Dimensional] image generation
• CPC Class Codes: G06T 19/006 Mixed reality object pose determination, tracking or camera calibration for mixed reality G06T7/00
• CPC Class Codes: G06T 2200/24 involving graphical user interfaces [GUIs]
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 7/33 using feature-based methods

Abstract

The described technology regards an augmented reality system and method for estimating a position of a location of interest relative to the position and orientation of a display, including a retroactive update to a previously rendered estimate of the position of the orientation of the display stored in a rewind buffer. Systems of the described technology include including a plurality of sensors, a processing module or other computation means, and a database. Methods of the described technology use data from the sensor package useful to accurately render graphical user interface information on a display.

Claims

1. A pose estimation system for use with a display, the system comprising:

a. a plurality of sensors,

b. a database comprising geodetic coordinates of a location of interest, and

c. a processing module communicatively coupled with the database and the sensors, the processing module receiving over time data from the sensors comprising delayed data measurements, and data representing the spatial position and orientation of the display relative to the spatial position of the sensors, and applies an Extended Kalman Filter (EKF) to the received data to estimate the position and orientation of the display, and calculate a position of the location of interest relative to the position and orientation of the display, based on a retroactive update to a previously rendered estimates of the position of the orientation of the display stored in a rewind buffer.

2. The pose estimation system of claim 1, wherein the processing module estimates the position of the location of interest further using a forward buffer to store current and predicted estimates of the position and orientation of the display calculated by the processing module.

3. The pose estimation system of claim 1, wherein the database is remote from the sensors and the processing module.

4. The pose estimation system of claim 1, wherein the plurality of sensors comprise a camera, a 3-axis accelerometer, a 3-axis angular rate gyro, a 3-axis magnetometer, a barometric pressure sensor, and a GPS receiver.

5. The pose estimation system of claim 1, wherein the database further comprises digital terrain and elevation data, and the processing module ingests said data to aid in the estimation of altitude of the display position.

6. The pose estimation system of claim 1, wherein the plurality of sensors are mounted to a rigid reference assembly.

7. The pose estimation system of claim 1, further comprising a display, and wherein graphical user interface information comprising a graphical icon representing the location of interest is rendered on the display at the position estimated by the processing module.

8. The pose estimation system of claim 7, further comprising a radio configured to send and receive geo-spatial data relating to objects in the environment, wherein the processing module receives, stores and uses the geo-spatial data to render graphical user interface information on the display comprising a graphical icon representing some of the objects in the environment.

9. The pose estimation system of claim 1, wherein the processing module calculates absolute orientation and implements a baseline GPS/INS to estimate the position of the location of interest, and adjusts the GPS/INS values over time with the absolute orientation so calculated.

10. The pose estimation system of claim 1, wherein the position of the location of interest is the vector r_ds^d, calculated using the formula:

r_ds^d=(C_n^eC_bⁿC_d^b)^T[r_es^e−

(r_ep^e+C_n^eC_bⁿr_pd^b)]

wherein r_pd ^b is the position of the origin of the display coordinate system d with respect to the point of origin of the body coordinate system p, expressed in body system coordinates b;

r_es^e is the position vector of the location of interest s in the environment with respect to the origin of the earth centered, earth fixed coordinate system e, expressed in e coordinates, derived from the geodetic coordinates of the location of interest in the database; and

r_ep^e is the position of location p with respect to the origin of e, expressed in e coordinates.

11. The pose estimation system of claim 1, wherein each delayed data measurement is stored in the rewind buffer and processed using a separate sequential update.

12. The pose estimation system of claim 1, wherein the plurality of sensors comprises a 3-axis magnetometer, and wherein the processing module calculates and compares the norm of data from the 3-axis magnetometer to the Earth'"'"'s field strength to detect the presence or absence of magnetic disturbances and, if detected, rejects data from the magnetometer corresponding to the times of detected magnetic disturbances.

13. A method for providing an estimate of position for a location of interest relative to a display, the method comprising the steps of:

a. receiving sensor data from a plurality of sensors comprising delayed data measurements and data representing the spatial position and orientation of a display,

b. applying an Extended Kalman Filter (EKF) to the received data and geodetic coordinates of a location of interest, to estimate a position of the location of interest relative to the position and orientation of the display, based on a retroactive update to a previously rendered position estimate stored in a rewind buffer.

14. The method of claim 13, wherein the step of applying an Extended Kalman Filter (EKF) further comprises the step of using a forward buffer to store current and predicted position and orientation estimates of the display.

15. The method of claim 13, wherein the sensor data received comprises time-stamped sensor values comprising camera imagery, accelerometer measurements, rate-gyro measurements, magnetometer measurements, barometric pressure sensor measurements, GPS receiver position measurements, and GPS receiver velocity measurements.

16. The method of claim 13, wherein the position of the location of interest is the vector r_ds^d, calculated using the formula:

r_ds^d=(C_n^eC_bⁿC_d^b)^T[r_es^e−

(r_ep^e+C_n^eC_bⁿr_pd^b)]

wherein r_pd^b is the position of the origin of the display coordinate system d with respect to the point of origin of the body coordinate system p, expressed in body system coordinates b;

r_es^e is the position vector of the location of interest s in the environment with respect to the origin of the earth centered, earth fixed coordinate system e, expressed in e coordinates, derived from the geodetic coordinates of the location of interest in the database; and

r_ep^e is the position of location p with respect to the origin of e, expressed in e coordinates.

17. A pose estimation system for use with a display, the system comprising

a. means for receiving sensor data from a plurality of sensors comprising delayed data measurements and data representing the spatial position of a display,

b. means for applying an Extended Kalman Filter (EKF) to the received data and geodetic coordinates of a location of interest, to estimate a position and orientation of the display, based on a retroactive update to a previously rendered position estimate stored in a rewind buffer, and calculate the position of a location of interest relative to the position and orientation of the display.

18. The pose estimation system of claim 17, wherein the means for applying the Extended Kalman Filter (EKF) further comprises the step of using a forward buffer to store current and predicted position and orientation estimates of the display.

19. The pose estimation system of claim 17, wherein the sensor data received comprises time-stamped sensor values comprising camera imagery, accelerometer measurements, rate-gyro measurements, magnetometer measurements, barometric pressure sensor measurements, GPS receiver position measurements, and GPS receiver velocity measurements.

20. The pose estimation system of claim 17, wherein the position of the location of interest is the vector r_ds^d, calculated using the formula:

r_ds^d=(C_n^eC_bⁿC_d^b)^T[r_es^e−

(r_ep^e+C_n^eC_bⁿr_pd^b)]

wherein r_pd^b is the position of the origin of the display coordinate system d with respect to the point of origin of the body coordinate system p, expressed in body system coordinates b;

r_es^e is the position vector of the location of interest s in the environment with respect to the origin of the earth centered, earth fixed coordinate system e, expressed in e coordinates, derived from the geodetic coordinates of the location of interest in the database; and

r_ep^e is the position of location p with respect to the origin of e, expressed in e coordinates.