Air space maps

Patent metadata

Field	Value
Publication number	US-9953540-B2
Application number	US-201514741039-A
Country	US
Kind code	B2
Filing date	Jun 16, 2015
Priority date	Jun 16, 2015
Publication date	Apr 24, 2018
Grant date	Apr 24, 2018

Abstract

Drone space is defined according to a building model and a buffer space. At least one three-dimensional geometry is identified from the building model. The buffer space is calculated from the three-dimensional geometry. Coordinates for a drone air space are defined based on the buffer space. At least one path segment may be identified based on the coordinates for the drone air space, and the coordinates for drone air space are stored in a map database in association with the at least one path segment.

First claim

We claim:

1. A method comprising:
identifying at least one three-dimensional geometry from a building model based on data collected by at least one sensor;
identifying a functional classification for a road type for at least one path segment;
calculating, by a processor, a buffer space from the at least one three-dimensional geometry according to the functional classification for the road type for at least one path segment;
defining, by the processor, coordinates for a drone air space based on the buffer space;
identifying at least one path segment for ground travel corresponding to the coordinates for the drone air space; and
storing the coordinates for drone air space in association with at least one path segment for ground travel in a map database.

2. The method of claim 1 , wherein the buffer space is defined based on a buffer distance from buildings in the building model.

3. The method of claim 2 , further comprising:
identifying a geographic region based on the at least one path segment; and
selecting the buffer space according to geographic region.

4. The method of claim 2 , further comprising:
identifying a temporal characteristic; and
selecting the buffer space according to temporal characteristic.

5. The method of claim 2 , further comprising:
receiving a drone identification value;
determining a degree of error for a drone based on the drone identification value; and
selecting the buffer space according to the degree of error for the drone.

6. The method of claim 5 , wherein the degree of error is a function of one or more of a positioning system error, an inertial measurement system error, or a latency time.

7. The method of claim 1 , wherein the drone air space is defined by an altitude limit in addition to the buffer space.

8. The method of claim 1 , further comprising:
defining a drone space attribute for the at least one path segment, wherein the drone space attribute includes a width based on the buffer space.

9. The method of claim 1 , further comprising:
defining a ramp in the drone space based on the at least one path segment.

10. The method of claim 1 , further comprising:
receiving a request for routing from a drone; and
calculating a route through the drone space based on the at least one path segment.

11. The method of claim 10 , wherein the at least one path segment includes a drone space attribute.

12. An apparatus comprising:
at least one processor; and
at least one memory including computer program code for one or more programs; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform:
detecting a position of a drone vehicle;
sending a routing request for the drone vehicle and the position of the drone vehicle; and
receiving a navigation command based on the routing request, wherein the navigation command is based on road attribute data from a geographic database, the road attribute data including at least one geographic attribute stored in association with a road segment and at least one drone space attribute stored in association with the road segment, the at least one drone space attribute defined by at least one three-dimensional geometry from a building model and a buffer space generated from the building model, wherein the buffer space is based on a functional classification of the road segment.

13. The apparatus of claim 12 , wherein the buffer space is defined based on a buffer distance from buildings in the building model, and the buffer space is a function of a geographic region, the functional classification of the at least one path segment, a temporal characteristic, or a drone identification value.

14. An apparatus comprising:
at least one processor; and
at least one memory including computer program code for one or more programs; the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform:
identifying at least one three-dimensional geometry from a building model based on data collected by at least one sensor;
calculating a buffer space from the at least one three-dimensional geometry;
identifying at least one ground path segment based on the coordinates for the drone air space;
defining coordinates for a drone air space based on the buffer space, wherein the buffer space is based on a functional classification for the at least one ground path segment; and
storing a path segment data record including at least one geographic attribute for at least one ground path segment and including the coordinates for drone air space.

15. The apparatus of claim 14 , wherein the buffer space is defined based on a buffer distance from buildings in the building model, and the buffer distance is variable as a function of a geographic region, the functional classification of the at least one path segment, or a temporal characteristic.

16. The apparatus of claim 14 , wherein the buffer space is defined based on a buffer distance from buildings in the building model, and the buffer distance is variable as a function of a drone identification value.

17. The apparatus of claim 16 , wherein the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform:
determining a degree of error for a drone based on the drone identification value; and
selecting the buffer space according to the degree of error for the drone, wherein the degree of error is a function of one or more of a positioning system error, an inertial measurement system error, or a latency time.

Assignees

• Here Global Bv

Inventors

• Macfarlane Jane
• Adachi Jeffrey
• Dannenbring Aaron

Classifications

• B64U2101/30

  for imaging, photography or videography · CPC title

• G08G5/0034

  Physics · mapped topic

• G01C21/20

  Instruments for performing navigational calculations (G01C21/24, G01C21/26 take precedence) · CPC title

• G05D1/101

  specially adapted for aircraft · CPC title

• B64C2201/123

  Operations & Transport · mapped topic