IP Library Granted Patent US 10,102,758
Granted Patent B1
US 10,102,758 · App. 15/584,810 · Granted Oct 16, 2018

Method and apparatus for privacy-sensitive routing of an aerial drone

Inventors: Jerome Beaurepaire (Berlin, DE); Marko Tuukkanen (Schlenzer, DE)
Assignee: HERE Global B.V.
G08G5/0069B64C39/024G06Q10/08355G08G5/0039B64C2201/128G05D1/101
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Quick Facts
Patent No.
US 10,102,758
App. No.
15/584,810
Granted
Oct 16, 2018
Kind
B1
Abstract

An approach is provided for routing an aerial drone while preserving privacy. The approach involves processing model data depicting at least one structure to determine one or more privacy-sensitive features of the at least one structure. The approach also involves calculating line-of-sight data between a route of an aerial drone and the one or more privacy-sensitive features. The approach further involves configuring a routing of the aerial drone based on the line-of sight data when the aerial drone is traveling near the at least one structure.

Claims (51)

1. A method comprising:

processing model data depicting at least one structure to determine one or more privacy-sensitive features of the at least one structure;

calculating line-of-sight data between a route of an aerial drone and the one or more privacy-sensitive features, wherein the line-of-sight data is collected from one or more sensors; and

configuring a routing of the aerial drone based on the line-of sight data, wherein the routing of the aerial drone is near the at least one structure.

2. The method of claim 1 , wherein the one or more privacy-sensitive features include one or more windows, one or more openings, or a combination thereof of the at least one structure.

3. The method of claim 1 , wherein the routing of the aerial drone is configured so that a direct line-of-sight between the aerial drone and an interior location of the at least one structure through the one or more privacy-sensitive features is avoided or minimized.

4. The method of claim 1 , further comprising:

matching the model data against indoor mapping data of the at least one structure,

wherein the one or more privacy-sensitive features are further determined based on the matching.

5. The method of claim 1 , further comprising:

generating map data of the line-of-sight data with respect to the one or more privacy-sensitive features, the at least one structure, or a combination thereof,

wherein the map data includes a mapping of three-dimensional locations surrounding the at least one structure above a street level.

6. The method of claim 5 , further comprising:

calculating respective privacy scores for the one or more privacy-sensitive features based on the line-of-sight data, the model data, indoor mapping data, or a combination thereof,

wherein the map data further includes the respective privacy scores.

7. The method of claim 5 , wherein the routing is further based on the map data.

8. The method of claim 1 , wherein the line-of-sight data is based on a visual line of sight, a sensor-based line of sight, or a combination thereof.

9. The method of claim 1 , wherein the configuring of the routing of the aerial drone comprises:

generating a flight plan for the aerial drone to make a delivery to at least one location at or near the at least one structure, wherein the flight plan is based on the line-of-sight data; and

initiating an execution of the flight plan by the aerial drone to make the delivery.

10. The method claim 1 , wherein the flight plan for the aerial drone specifies an approach angle, a height of the aerial drone, a distance of the aerial drone from the one or more privacy-sensitive features, a location where the aerial drone is to rise, a location where the aerial drone is to descend, or a combination thereof.

11. The method of claim 1 , further comprising:

deactivating at least one sensor of the aerial drone when a line of sight of the at least one sensor is calculated to include an interior of the at least one structure through the one or more privacy-sensitive features.

12. The method of claim 1 , further comprising:

transmitting a signal from the aerial drone to at least one receiver of the at least one structure when a line of sight of the one or more sensors is calculated to expose an interior of the at least one structure through the one or more privacy-sensitive features,

wherein the signal indicates to the at least one structure to take one or more automated privacy-preserving measures.

13. 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 perform at least the following:

process model data depicting at least one structure to determine one or more privacy-sensitive features of the at least one structure;

calculate line-of-sight data between a route of an aerial drone and the one or more privacy-sensitive features, wherein the line-of-sight data is collected from one or more sensors; and

configure a routing of the aerial drone based on the line-of sight data, wherein the routing of the aerial drone is near the at least one structure.

14. The apparatus of claim 13 , wherein the routing of the aerial drone is configured so that a direct line-of-sight between the aerial drone and an interior location of the at least one structure through the one or more privacy-sensitive features is avoided or minimized.

15. The apparatus of claim 13 , wherein the apparatus is further caused to:

match the model data against indoor mapping data of the at least one structure,

wherein the one or more privacy-sensitive features are further determined based on the matching.

16. The apparatus of claim 13 , wherein the apparatus is further caused to:

generate map data of the line-of-sight data with respect to the one or more privacy-sensitive features, the at least one structure, or a combination thereof,

wherein the map data includes a mapping of three-dimensional locations surrounding the at least one structure above a street level.

17. A non-transitory computer-readable storage medium, carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform:

processing model data depicting at least one structure to determine one or more privacy-sensitive features of the at least one structure;

calculating line-of-sight data between a route of an aerial drone and the one or more privacy-sensitive features, wherein the line-of-sight data is collected from one or more sensors; and

configuring a routing of the aerial drone based on the line-of sight data, wherein the routing of the aerial drone is near the at least one structure.

18. The non-transitory computer-readable storage medium of claim 17 , wherein the routing of the aerial drone is configured so that a direct line-of-sight between the aerial drone and an interior location of the at least one structure through the one or more privacy-sensitive features is avoided or minimized.

19. The non-transitory computer-readable storage medium of claim 17 , wherein the apparatus is further caused to perform:

matching the model data against indoor mapping data of the at least one structure,

wherein the one or more privacy-sensitive features are further determined based on the matching.

20. The non-transitory computer-readable storage medium of claim 17 , wherein the apparatus is further caused to perform:

generating map data of the line-of-sight data with respect to the one or more privacy-sensitive features, the at least one structure, or a combination thereof,

wherein the map data includes a mapping of three-dimensional locations surrounding the at least one structure above a street level.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 3, 2017
From: TUUKKANEN, MARKO; BEAUREPAIRE, JEROME
To: HERE GLOBAL B.V.
Reel/Frame 042227/0806 →
Cited By (2)
US 12,367,781 US 12,682,767