Systems and methods for determining a vehicle position

• US 10,788,830 B2
• Filed: 07/28/2017
• Issued: 09/29/2020
• Est. Priority Date: 07/28/2017
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Sharma, Arunandan
• Primary Examiner(s): Bekele, Mekonen T
• Application Number:
  US15/663,053
• Publication Number:
  US 20190033867A1
• Time in Patent Office: 1,159 Days
• CPC Class Codes: G01C 11/06 by comparison of two or more pictures of the same area
• CPC Class Codes: G01C 21/26 specially adapted for navigation in a road network
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G05D 1/0094 involving pointing a payload, e.g. camera, weapon, sensor, towards a fixed or moving target
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• 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
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 20/588 Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0137 for specific applications

Abstract

A method is described. The method includes obtaining a plurality of images. The method also includes detecting an object in the plurality of images. The method further includes determining a plurality of feature points on the object. The feature points have an established relationship to each other based on an object type. The method additionally includes determining a motion trajectory and a camera pose relative to a ground plane using the plurality of feature points.

Claims

1. A method, comprising:

obtaining a plurality of images;

detecting an object in the plurality of images, wherein the object comprises a traffic guidance object;

determining a plurality of feature points on the object, wherein the feature points have an established relationship to each other based on an object type;

determining an acceleration measurement; and

determining a motion trajectory and a camera pose relative to a ground plane using the plurality of feature points based on the acceleration measurement, wherein the motion trajectory and the camera pose determined using the plurality of feature points supplement a motion trajectory and a camera pose determined from inertial sensor measurements.

2. The method of claim 1, wherein the object includes a lane marker or a traffic sign.

3. The method of claim 1, wherein determining the plurality of feature points comprises determining three or more end corners of a detected lane marker.

4. The method of claim 1, wherein determining the plurality of feature points comprises determining three or more vertices of a detected traffic sign.

5. The method of claim 1, wherein determining the motion trajectory comprises determining scale information using the plurality of feature points.

6. The method of claim 1, wherein determining the motion trajectory and the camera pose comprises comparing a plurality of feature points determined from a first image to corresponding feature points determined from a second image.

7. The method of claim 1, further comprising:

combining measurements of the detected object with inertial sensor measurements; and

determining the motion trajectory based on the combined measurements.

8. The method of claim 1, further comprising:

combining satellite navigation receiver measurements with measurements of the detected object; and

determining a pose and position in a global frame based on the combined measurements.

9. The method of claim 8, further comprising:

combining vehicle sensor measurements from one or more vehicle sensors with the satellite navigation receiver measurements and measurements of the detected object; and

determining the pose and position in the global frame based on the combined measurements.

10. The method of claim 1, further comprising:

combining measurements of the detected object with speedometer measurements; and

determining the motion trajectory based on the combined measurements.

11. The method of claim 1, wherein the method is performed in a vehicle.

12. The method of claim 11, further comprising transmitting the camera pose to a mapping service.

13. The method of claim 1, wherein the method is performed by a server.

31. The method of claim 1, wherein measurements of the plurality of feature points on the object are used to compensate for scale drift of an inertial sensor in response to determining the acceleration measurement.

14. An electronic device, comprising:

a memory; and

a processor in communication with the memory, the processor configured to;

obtain a plurality of images;

detect an object in the plurality of images, wherein the object comprises a traffic guidance object;

determine a plurality of feature points on the object, wherein the feature points have an established relationship to each other based on an object type;

determine an acceleration measurement; and

determine a motion trajectory and a camera pose relative to a ground plane using the plurality of feature points based on the acceleration measurement, wherein the motion trajectory and the camera pose determined using the plurality of feature points supplement a motion trajectory and a camera pose determined from inertial sensor measurements.

15. The electronic device of claim 14, wherein the object includes a lane marker or a traffic sign.

16. The electronic device of claim 14, wherein the processor configured to determine the plurality of feature points comprises the processor configured to determine three or more end corners of a detected lane marker.

17. The electronic device of claim 14, wherein the processor configured to determine the plurality of feature points comprises the processor configured to determine three or more vertices of a detected traffic sign.

18. The electronic device of claim 14, wherein the processor configured to determine the plurality of feature points comprises the processor configured to determine scale information using the plurality of feature points.

19. The electronic device of claim 14, wherein the processor configured to determine the motion trajectory and the camera pose comprises the processor configured to compare a plurality of feature points determined from a first image to corresponding feature points determined from a second image.

20. A non-transitory computer readable medium storing computer executable code, comprising:

code for causing an electronic device to obtain a plurality of images;

code for causing the electronic device to detect an object in the plurality of images, wherein the object comprises a traffic guidance object;

code for causing the electronic device to determine a plurality of feature points on the object, wherein the feature points have an established relationship to each other based on an object type;

code for causing the electronic device to determine an acceleration measurement; and

code for causing the electronic device to determine a motion trajectory and a camera pose relative to a ground plane using the plurality of feature points based on the acceleration measurement, wherein the motion trajectory and the camera pose determined using the plurality of feature points supplement a motion trajectory and a camera pose determined from inertial sensor measurements.

21. The computer readable medium of claim 20, wherein the object includes a lane marker or a traffic sign.

22. The computer readable medium of claim 20, wherein the code for causing the electronic device to determine the plurality of feature points comprises code for causing the electronic device to determine three or more end corners of a detected lane marker.

23. The computer readable medium of claim 20, wherein the code for causing the electronic device to determine the plurality of feature points comprises code for causing the electronic device to determine three or more vertices of a detected traffic sign.

24. The computer readable medium of claim 20, wherein the code for causing the electronic device to determine the motion trajectory comprises code for causing the electronic device to determine scale information using the plurality of feature points.

25. The computer readable medium of claim 20, wherein code for causing the electronic device to determine the motion trajectory and the camera pose comprises code for causing the electronic device to compare a plurality of feature points determined from a first image to corresponding feature points determined from a second image.

26. An apparatus, comprising:

means for obtaining a plurality of images;

means for detecting an object in the plurality of images, wherein the object comprises a traffic guidance object;

means for determining a plurality of feature points on the object, wherein the feature points have an established relationship to each other based on an object type;

means for determining an acceleration measurement; and

means for determining a motion trajectory and a camera pose relative to a ground plane using the plurality of feature points based on the acceleration measurement, wherein the motion trajectory and the camera pose determined using the plurality of feature points supplement a motion trajectory and a camera pose determined from inertial sensor measurements.

27. The apparatus of claim 26, wherein the object includes a lane marker or a traffic sign.

28. The apparatus of claim 26, wherein the means for determining the plurality of feature points comprise means for determining three or more end corners of a detected lane marker.

29. The apparatus of claim 26, wherein the means for determining the plurality of feature points comprise means for determining three or more vertices of a detected traffic sign.

30. The apparatus of claim 26, wherein the means for determining the plurality of feature points comprise means for determining scale information using the plurality of feature points.