INDOOR STRUCTURE INFERENCE USING POINTS OF INTEREST

• US 20130342565A1
• Filed: 06/21/2012
• Published: 12/26/2013
• Est. Priority Date: 06/21/2012
• Status: Active Grant

• Current Assignee: Qualcomm, Inc.
• Original Assignee: Qualcomm, Inc.
• Inventors: Sridhara, Vinay, Chao, Hui, Das, Saumitra Mohan, Gupta, Rajarshi
• Granted Patent: US 9,395,189 B2
• Time in Patent Office: Days
• US Class Current: 345/629
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01C 21/3811 Point data, e.g. Point of Interest [POI]
• CPC Class Codes: G01C 21/383 Indoor data
• CPC Class Codes: G01C 21/3867 Geometry of map features, e.g. shape points, polygons or for simplified maps
• CPC Class Codes: G01S 5/0236 Assistance data, e.g. base station almanac
• CPC Class Codes: G01S 5/02524 Creating or updating the radio-map

Abstract

In one implementation, a method may comprise: obtaining a digital map of an indoor region that identifies boundaries between subsections within the indoor region; and approximating locations of walls separating rooms within at least one of the subsections based, at least in part, on locations of feature labels provided in the digital map.

Claims

1. A method comprising:

obtaining from a memory a digital map of an indoor region that identifies boundaries between subsections within said indoor region; and

approximating locations of walls separating rooms within at least one of said subsections based, at least in part, on locations of feature labels provided in said digital map.

2. The method of claim 1, wherein said feature labels identify points of interest.

3. The method of claim 1, wherein said feature labels comprise names of stores.

4. The method of claim 3, further comprising:

approximating said locations of said feature labels based, at least in part, on a quantity of said stores.

5. The method of claim 3, further comprising:

modifying said locations of said feature labels based, at least in part, on said names of stores.

6. The method of claim 1, wherein said approximating said locations of walls further comprises superimposing polygons over said at least one of said subsections.

7. The method of claim 6, wherein said polygons comprise Voronoi cells.

8. The method of claim 7, wherein said Voronoi cells are generated based, at least in part, on said locations of said feature labels.

9. The method of claim 1, further comprising:

determining routeability for at least a portion of said indoor region based, at least in part, on said approximated locations of walls.

10. The method of claim 1, further comprising:

computing values of a radio heatmap database based, at least in part, on locations of transmitters and said approximation of locations of walls.

11. The method of claim 10, wherein said radio heatmap database comprises received signal strength indicator (RSSI) values.

12. The method of claim 1, wherein at least one of said subsections within said indoor region comprises an anchor store of a shopping mall, the method further comprising:

determining a size of said anchor store based, at least in part, on a lookup table; and

constraining said approximating locations of walls based, at least in part, on said determined size.

13. An apparatus comprising:

means for obtaining a digital map of an indoor region that identifies boundaries between subsections within said indoor region; and

means for approximating locations of walls separating rooms within at least one of said subsections based, at least in part, on locations of feature labels provided in said digital map.

14. The apparatus of claim 13, wherein said feature labels identify points of interest.

15. The apparatus of claim 13, wherein said feature labels comprise names of stores.

16. The apparatus of claim 15, further comprising:

means for approximating said locations of said feature labels based, at least in part, on a quantity of said stores.

17. The apparatus of claim 15, further comprising:

means for modifying said locations of said feature labels based, at least in part, on said names of stores.

18. The apparatus of claim 13, wherein said means for approximating said locations of walls further comprises means for superimposing polygons over said at least one of said subsections.

19. The apparatus of claim 18, wherein said polygons comprise Voronoi cells.

20. The apparatus of claim 19, wherein said Voronoi cells are generated based, at least in part, on said locations of said feature labels.

21. The apparatus of claim 13, further comprising:

means for determining routeability for at least a portion of said indoor region based, at least in part, on said approximated locations of walls.

22. The apparatus of claim 13, further comprising:

means for computing values of a radio heatmap database based, at least in part, on locations of transmitters and said approximation of locations of walls.

23. The apparatus of claim 22, wherein said radio heatmap database comprises received signal strength indicator (RSSI) values.

24. The apparatus of claim 13, wherein at least one of said subsections within said indoor region comprises an anchor store of a shopping mall, the apparatus further comprising:

means for determining a size of said anchor store based, at least in part, on a lookup table; and

means for constraining said approximating locations of walls based, at least in part, on said determined size.

25. An apparatus comprising:

a receiver to receive wireless signals; and

one or more processing units to;

approximate locations of walls separating rooms within at least one of multiple subsections based, at least in part, on locations of feature labels provided in a digital map received through said receiver, wherein said digital map comprises a map of an indoor region that identifies boundaries between said subsections within said indoor region.

26. The apparatus of claim 25, wherein said feature labels identify points of interest.

27. The apparatus of claim 25, wherein said feature labels comprise names of stores.

28. The apparatus of claim 27, further comprising one or more processing units to:

approximate said locations of said feature labels based, at least in part, on a quantity of said stores.

29. The apparatus of claim 27, further comprising one or more processing units to:

modify said locations of said feature labels based, at least in part, on said names of stores.

30. The apparatus of claim 25, wherein said approximating said locations of walls further comprises superimposing polygons over said at least one of said subsections.

31. The apparatus of claim 30, wherein said polygons comprise Voronoi cells.

32. The apparatus of claim 31, wherein said Voronoi cells are generated based, at least in part, on said locations of said feature labels.

33. The apparatus of claim 25, further comprising one or more processing units to:

determine routeability for at least a portion of said indoor region based, at least in part, on said approximated locations of walls.

34. The apparatus of claim 25, further comprising one or more processing units to:

compute values of a radio heatmap database based, at least in part, on locations of transmitters and said approximation of locations of walls.

35. The apparatus of claim 34, wherein said radio heatmap database comprises received signal strength indicator (RSSI) values.

36. The apparatus of claim 25, wherein at least one of said subsections within said indoor region comprises an anchor store of a shopping mall, the apparatus further comprising one or more processing units to:

determine a size of said anchor store based, at least in part, on a lookup table; and

constrain said approximating locations of walls based, at least in part, on said determined size.

37. An article comprising:

a non-transitory storage medium comprising machine-readable instructions stored thereon that are executable by a special purpose computing device to;

evaluate a digital map of an indoor region to identify boundaries between subsections within said indoor region; and

approximate locations of walls separating rooms within at least one of said subsections based, at least in part, on locations of feature labels provided in said digital map.

38. The article of claim 37, wherein said feature labels identify points of interest.

39. The article of claim 37, wherein said feature labels comprise names of stores.

40. The article of claim 39, further comprising machine-readable instructions stored thereon that are executable by said special purpose computing device to:

approximate said locations of said feature labels based, at least in part, on a quantity of said stores.

41. The article of claim 39, further comprising machine-readable instructions stored thereon that are executable by said special purpose computing device to:

modify said locations of said feature labels based, at least in part, on said names of stores.

42. The article of claim 37, wherein said approximating said locations of walls further comprises superimposing polygons over said at least one of said subsections.

43. The article of claim 42, wherein said polygons comprise Voronoi cells.

44. The article of claim 43, wherein said Voronoi cells are generated based, at least in part, on said locations of said feature labels.

45. The article of claim 37, further comprising machine-readable instructions stored thereon that are executable by said special purpose computing device to:

determine routeability for at least a portion of said indoor region based, at least in part, on said approximated locations of walls.

46. The article of claim 37, further comprising machine-readable instructions stored thereon that are executable by said special purpose computing device to:

compute values of a radio heatmap database based, at least in part, on locations of transmitters and said approximation of locations of walls.

47. The article of claim 46, wherein said radio heatmap database comprises received signal strength indicator (RSSI) values.

48. The article of claim 37, wherein at least one of said subsections within said indoor region comprises an anchor store of a shopping mall, the article further comprising machine-readable instructions stored thereon that are executable by said special purpose computing device to:

determine a size of said anchor store based, at least in part, on a lookup table; and

constrain said approximating locations of walls based, at least in part, on said determined size.