Pose estimation

• US 9,482,536 B2
• Filed: 01/31/2013
• Issued: 11/01/2016
• Est. Priority Date: 05/31/2012
• Status: Active Grant

• Current Assignee: CSX Transportation Incorporated (CSX Corporation), International Electronic Machines Corp.
• Original Assignee: CSX Transportation Incorporated (CSX Corporation), International Electronic Machines Corp.
• Inventors: Mian, Zahid F., vonAchen, William G.
• Primary Examiner(s): Holwerda, Stephen
• Application Number:
  US13/756,255
• Publication Number:
  US 20130325334A1
• Time in Patent Office: 1,370 Days
• Field of Search: 700/245, 700/250, 700/253, 700/254, 700/258, 700/259, 700/262, 700/263
• US Class Current: 1/1
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G05D 1/027 comprising intertial navigation means, e.g. azimuth detector inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165
• CPC Class Codes: G05D 1/0278 using satellite positioning signals, e.g. GPS

Abstract

A solution for estimating the pose of a platform, such as a vehicle, is provided. Data from a plurality of types of sensing devices located on the platform can be used to independently calculate a plurality of preliminary estimates corresponding to the pose. A plurality of estimates corresponding to the pose can be generated using the preliminary estimates and at least one covariance matrix. One or more entries in the covariance matrix are adjusted based on an uncertainty for the corresponding preliminary estimate. The uncertainty can vary based on time, distance, and/or velocity of the platform.

Claims

1. A method comprising:

a computer system periodically calculating a plurality of estimates corresponding to a pose of a platform, wherein the periodically calculating includes;

for each of a plurality of types of sensor data, independently calculating at least one of a plurality of preliminary estimates based on the sensor data corresponding to the type of sensor data;

adjusting a covariance matrix including covariance data for each of the plurality of types of sensor data based on an uncertainty for at least one of the plurality of preliminary estimates, wherein the uncertainty varies based on at least one of;

time, distance, or velocity of the platform; and

generating the plurality of estimates using the plurality of preliminary estimates and the covariance matrix, wherein the covariance matrix is applied to each of the plurality of estimates to adjust an emphasis each of the plurality of preliminary estimates has on the corresponding estimate.

2. The method of claim 1, wherein the plurality of types of sensor data include:

global positioning system measurement data;

inertial data; and

wheel odometry data.

3. The method of claim 1, wherein the adjusting includes dynamically adjusting at least one entry of the covariance matrix based on at least one of:

an amount of time the platform has been moving, a distance the platform has moved without stopping, or an amount of time since external location information has been received.

4. The method of claim 3, wherein the at least one entry corresponds to wheel odometry data for the platform, and wherein the computer system increases the uncertainty corresponding to the wheel odometry data based on an amount of time the platform has been moving.

5. The method of claim 1, wherein the adjusting includes the computer system reinitializing at least one entry of the covariance matrix in response to the platform being stationary.

6. The method of claim 1, wherein the generating includes applying one of a plurality of process noise covariance matrixes to the plurality of preliminary estimates to generate the plurality of estimates, wherein each of the process noise covariance matrixes corresponds to an uncertainty due to at least one attribute of the platform.

7. The method of claim 6, further comprising the computer system selecting a stationary process noise covariance matrix when the platform is stationary and selecting a moving process noise covariance matrix when the platform is moving.

8. The method of claim 7, wherein the adjusting includes the computer system dynamically adjusting at least one entry of the moving process noise covariance matrix based on a velocity of the platform.

9. The method of claim 1, wherein the platform is a vehicle, the method further comprising the computer system managing navigation of the vehicle using the plurality of estimates corresponding to the pose.

10. A computer system comprising:

a set of computing devices configured to perform a method comprising periodically calculating a plurality of estimates corresponding to a pose of a platform, wherein the periodically calculating includes;

for each of a plurality of types of sensor data, independently calculating at least one of a plurality of preliminary estimates based on the sensor data corresponding to the type of sensor data;

adjusting a covariance matrix including covariance data for each of the plurality of types of sensor data based on an uncertainty for at least one of the plurality of preliminary estimates, wherein the uncertainty varies based on at least one of;

time, distance, or velocity of the platform; and

generating the plurality of estimates using the plurality of preliminary estimates and the covariance matrix, wherein the covariance matrix is applied to each of the plurality of estimates to adjust an emphasis each of the plurality of preliminary estimates has on the corresponding estimate.

11. The computer system of claim 10, wherein the plurality of types of sensor data include:

global positioning system measurement data;

inertial data; and

wheel odometry data.

12. The computer system of claim 10, wherein the adjusting includes dynamically adjusting at least one entry of the covariance matrix based on at least one of:

an amount of time the platform has been moving, a distance the platform has moved without stopping, or an amount of time since external location information has been received.

13. The computer system of claim 12, wherein the at least one entry corresponds to wheel odometry data for the platform, and wherein the computer system increases the uncertainty corresponding to the wheel odometry data based on an amount of time the platform has been moving.

14. The computer system of claim 12, wherein the adjusting includes reinitializing at least one entry of the covariance matrix in response to the platform being stationary.

15. The computer system of claim 10, wherein the generating includes applying one of a plurality of process noise covariance matrixes to the plurality of preliminary estimates to generate the plurality of estimates, wherein each of the process noise covariance matrixes corresponds to an uncertainty due to at least one attribute of the platform.

16. The computer system of claim 15, the method further comprising selecting a stationary process noise covariance matrix when the platform is stationary and selecting a moving process noise covariance matrix when the platform is moving.

17. The computer system of claim 10, wherein the platform is a vehicle, the method further comprising managing navigation of the vehicle using the plurality of estimates corresponding to the pose.

18. A vehicle comprising:

a navigation system including a set of computing devices configured to perform a method comprising;

periodically calculating a plurality of estimates corresponding to a pose of the vehicle, wherein the periodically calculating includes;

for each of a plurality of types of sensor data, independently calculating at least one of a plurality of preliminary estimates based on the sensor data corresponding to the type of sensor data;

adjusting a covariance matrix including covariance data for each of the plurality of types of sensor data based on an uncertainty for at least one of the plurality of preliminary estimates, wherein the uncertainty varies based on at least one of;

time, distance, or velocity of the platform; and

generating the plurality of estimates using the plurality of preliminary estimates and the covariance matrix, wherein the covariance matrix is applied to each of the plurality of estimates to adjust an emphasis each of the plurality of preliminary estimates has on the corresponding estimate; and

managing navigation of the vehicle using the plurality of estimates corresponding to the pose.

19. The vehicle of claim 18, wherein the adjusting includes dynamically adjusting at least one entry of the covariance matrix based on at least one of:

an amount of time the vehicle has been moving, a distance the vehicle has moved without stopping, or an amount of time since external location information has been received.

20. The vehicle of claim 18, the method further comprising selecting a stationary process noise covariance matrix when the vehicle is stationary and selecting a moving process noise covariance matrix when the vehicle is moving.