Irregular Feature Mapping

• US 20170153111A1
• Filed: 08/16/2016
• Published: 06/01/2017
• Est. Priority Date: 06/12/2012
• Status: Active Grant

• Current Assignee: TRX Systems, Inc.
• Original Assignee: TRX Systems, Inc.
• Inventors: Bandyopadhyay, Amrit, Beisel, Brian, Funk, Benjamin, Teolis, Carole, Giles, Christopher, Karvounis, John
• Granted Patent: US 9,778,044 B2
• Time in Patent Office: Days
• CPC Class Codes: G01C 21/12 executed aboard the object being navigated; Dead reckoning
• CPC Class Codes: G01C 21/1652 with ranging devices, e.g. LIDAR or RADAR
• CPC Class Codes: G01C 21/1654 with electromagnetic compass
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01S 5/013 Identifying areas in a building
• CPC Class Codes: G01S 5/0264 at least one of the systems being a non-radio wave positioning system
• CPC Class Codes: H04W 64/00 Locating users or terminals or network equipment for network management purposes, e.g. mobility management

Abstract

Disclosed herein are methods and systems for mapping irregular features. In an embodiment, a computer-implemented method may include obtaining tracking data that has dead reckoning tracking data for a tracked subject along a path and performing shape correction on the tracking data to provide a first estimate of the path.

Claims

1. A computer-implemented method for reducing errors in inertial tracking data, the method being implemented by a computer that includes a physical processor, the method comprising:

obtaining, as input, a building outline for a complex building having a plurality of outline segments that include an arc segment;

determining probable grid directions based on the building outline for each location among a plurality of locations within the building outline, the probable grid directions for at least one location among the plurality of locations being nonparallel with the arc segment;

obtaining, as input, tracking data for a mobile device along a tracking path comprising a plurality of tracking points, the tracking data including sensor data associated with the mobile device; and

correcting a heading of at least a portion of the tracking path using the determined probable grid directions.

2. The method of claim 1, wherein determining probable grid directions includes partitioning the arc segment at a plurality of vertices to create a sequence of straight line segments.

3. The method of claim 1, wherein determining probable grid directions includes spawning lines from a plurality of interior points within the building outline in all headings, and identifying outline segments among the plurality of outline segments that intersect the spawned lines without obstruction.

4. The method of claim 1, wherein determining probable grid directions includes spawning lines from a plurality of interior points within the building outline in all headings, and determining, for each spawned line, a distance to the building outline.

5. The method of claim 4, wherein the determined distance for each spawned line is weighted according to a length of one outline segment among the plurality of outline segments that the spawned line intersects without obstruction.

6. The method of claim 1, wherein determining probable grid directions includes spawning lines from a plurality of interior points within the building outline in all headings, and combining weighted values of all spawned lines for each interior point among the plurality of interior points to create a histogram of probable grid directions for that interior point.

7. The method of claim 6, further comprising:

eliminating probable grid directions from the histogram of probable grid directions using a predetermined threshold.

8. The method of claim 1, wherein the sensor data is obtained from at least one of an inertial sensor, and optical flow sensor, or a Doppler velocimeter.

9. A computing system for localizing a mobile device traversing a structure, the computing system comprising:

a processor; and

a memory communicatively coupled to the processor, the memory bearing instructions that, when executed on the processor, cause the computing system to at least;

obtain, as input, a building outline for a complex building having a plurality of outline segments that include at least two outline segments forming a non-orthogonal angle at a vertex;

determine probable grid directions based on the building outline for each location among a plurality of locations within the building outline, the probable grid directions for at least one location among the plurality of locations being nonparallel to one of the at least two outline segments forming the non-orthogonal angle at the vertex;

obtain, as input, tracking data for a mobile device along a tracking path comprising a plurality of tracking points, the tracking data including sensor data associated with the mobile device; and

divide the building outline into a plurality of building partitions based on the determined probable grid directions.

10. The system of claim 9, wherein the memory also bearing instructions that, when executed on the processor, further cause the computing system to at least:

determine a location of the mobile device based on a comparison of the tracking data and one or more sensor signatures associated with one building partition among the plurality of building partitions.

11. The system of claim 9, wherein the obtained tracking data further includes previously-acquired sensor data stored in persistent memory.

12. The system of claim 9, wherein the memory also bearing instructions that, when executed on the processor, further cause the computing system to at least:

correct a heading of at least a portion of the tracking path using the plurality of building partitions.

13. The system of claim 9, wherein the building outline is obtained from a Geographic Information Systems (GIS) map.

14. The system of claim 9, wherein the memory also bearing instructions that, when executed on the processor, further cause the computing system to at least:

correct a heading of at least a portion of the tracking path using the determined probable grid directions.

15. A computer-implemented method for reducing errors in inertial tracking data, the method being implemented by a computer that includes a physical processor, the method comprising:

obtaining, as input, a building outline for a complex building having a plurality of outline segments;

determining probable grid directions based on the building outline for each location among a plurality of locations within the building outline, the probable grid directions for at least one location among the plurality of locations being nonparallel with at least one outline segment among the plurality of outline segments;

obtaining, as input, tracking data for a mobile device along a tracking path comprising a plurality of tracking points, the tracking data including sensor data associated with the mobile device; and

dividing the building outline into a plurality of building partitions based on the determined probable grid directions.

16. The method of claim 15, further comprising:

correcting a heading of at least a portion of the tracking path using the determined probable grid directions.

17. The method of claim 15, wherein each building partition among the plurality of building partitions is associated with an expected hallway orientation or angle.

18. The method of claim 15, further comprising:

correcting a heading of at least a portion of the tracking path using the determined probable grid directions.

19. The method of claim 15, further comprising:

determining one or more sensor signatures for at least one building partition among the plurality of building partitions based on tracking data obtained while the mobile device was present in the at least one building partition.

20. The method of claim 19, wherein the one or more sensor signatures include a magnetic sensor data profile.