Generating and distributing GNSS risk analysis data for facilitating safe routing of autonomous drones
Disclosed is route planning using a worst-case risk analysis and, if needed, a best-case risk analysis of GNSS coverage. The worst-case risk analysis identifies cuboids or 2d regions through which a vehicle can be routed with assurance that adequate GNSS coverage will be available regardless of the time of day that the vehicle travels. The best-case risk analysis identifies cuboids or 2d regions through which there is adequate coverage at some times during the day. In case path finding using the worst-case risk analysis fails, a best-case risk analysis can be requested and used to find alternate potential path(s). Time dependent forecast data that covers regions along the alternate potential path(s) can be requested and used to route vehicles, including autonomous drones, from starting points to destinations. This includes generation, distribution and use of risk analysis data, implemented as methods, systems and articles of manufacture.
1. A method of generating and distributing GNSS data for facilitating safe routing of autonomous drones, the method including:
obtaining three to fifty days of historical GNSS satellite path data, at least two of which are non-consecutive days, for a region of calculation;
generating, using the historical GNSS satellite path data, a worst-case risk analysis for the region of calculation that reveals cuboids in the region of interest through which a drone can fly through with configurably adequate GNSS coverage for autonomous flight irrespective of the time of flight, including:
sampling, over a range of hours of historical GNSS satellite path data, using a three-dimension model of the region of calculation, including ray casting from the cuboids to the historical paths of the GNSS satellites using the three-dimensional model to determine precision of GNSS coverage for cuboids; and
for each cuboid in the region of calculation, determining the lowest precision of GNSS coverage during the consecutive span of hours;
receiving and responding to a request for the worst-case risk analysis for a region of interest within the region of calculation by distributing the worst-case risk analysis for the region of interest.
2. The method of claim 1 , further including indicating in the worst-case analysis the cuboids for which adequate GNSS coverage is not dependent on time-of-day.
3. The method of 1, wherein configurably adequate is met when the precision of GNSS coverage satisfies requirements of a Federal Aviation Administration (FAA).
4. The method of claim 1 , wherein the historical GNSS satellite path data includes three to ten non-consecutive days.
5. The method of claim 1 , wherein the non-consecutive days are separated by 5 to 20 days.
6. The method of claim 1 , wherein the sampling is conducted on an interval between once per half-second and once per 90 seconds.
7. The method of claim 1 , wherein the range of hours of historical GNSS satellite path data is between 12 to 24 hours.
8. The method of claim 1 , further including:
wherein the worst-case risk analysis includes inadequate coverage zones; and
wherein the generating further includes padding worst zones with a buffer zone that extends outward from the inadequate coverage zones up to 10 meters.
9. The method of claim 8 , wherein the buffer zone extends outward up to 5 meters.
10. The method of claim 8 , further including:
generating, using the historical satellite data, a best-case risk analysis for the region of calculation that reveals cuboids in which, for at least a period of time in the historical GNSS satellite path data, a time-sensitive route is available; and
receiving a request for the best-case analysis for the region of interest and responding by distributing the best-case risk analysis.
11. The method of claim 10 , further including:
requesting and receiving a forecast for at least the requested range of time covering at least the likely route; and
finding in the forecast at least one time during which the drone can fly from the starting location to the destination through the cuboids that have the configurably adequate GNSS coverage for a period within the range of time.
12. A non-transitory computer readable medium impressed with computer program instructions that, when executed on hardware, cause the hardware to carry out actions of generating and distributing GNSS data for facilitating safe routing of autonomous drones, the actions including:
obtaining three to fifty days of historical GNSS satellite path data, at least two of which are non-consecutive days, for a region of calculation;
generating, using the historical GNSS satellite path data, a worst-case risk analysis for the region of calculation that reveals cuboids in the region of interest through which a drone can fly through with configurably adequate GNSS coverage for autonomous flight irrespective of the time of flight, including:
sampling, over a range of hours of historical GNSS satellite path data, using a three-dimension model of the region of calculation, including ray casting from the cuboids to the historical paths of the GNSS satellites using the three-dimensional model to determine precision of GNSS coverage for cuboids; and
for each cuboid in the region of calculation, determining the lowest precision of GNSS coverage during the consecutive span of hours;
receiving and responding to a request for the worst-case risk analysis for a region of interest within the region of calculation by distributing the worst-case risk analysis for the region of interest.
13. The computer readable medium of 12 , wherein configurably adequate is met when the precision of GNSS coverage satisfies requirements of a Federal Aviation Administration (FAA).
14. The computer readable medium of claim 12 , wherein the historical GNSS satellite path data includes three to ten non-consecutive days.
15. The computer readable medium of claim 12 , wherein the non-consecutive days are separated by 5 to 20 days.
16. The computer readable medium of claim 12 , further including:
wherein the worst-case risk analysis includes inadequate coverage zones; and
wherein the generating further includes padding worst zones with a buffer zone that extends outward from the inadequate coverage zones up to 10 meters.
17. The computer readable medium of claim 16 , wherein the buffer zone extends outward up to 5 meters.
18. The computer readable medium of claim 16 , further including:
generating, using the historical satellite data, a best-case risk analysis for the region of calculation that reveals cuboids in which, for at least a period of time in the historical GNSS satellite path data, a time-sensitive route is available; and
receiving a request for the best-case analysis for a second requested range of time and the region of interest and responding by distributing the best-case risk analysis.
19. The computer readable medium of claim 18 , further including:
requesting and receiving a forecast for at least the requested range of time covering at least the likely route; and
finding in the forecast at least one time during which the drone can fly from the starting location to the destination through the cuboids that have the configurably adequate GNSS coverage for a period within the range of time.
20. A system including hardware and a non-transitory computer readable medium impressed with computer program instructions that, when executed on the hardware, cause the hardware to carry out actions of generating and distributing GNSS data for facilitating safe routing of autonomous drones, the actions including:
obtaining three to fifty days of historical GNSS satellite path data, at least two of which are non-consecutive days, for a region of calculation;
generating, using the historical GNSS satellite path data, a worst-case risk analysis for the region of calculation that reveals cuboids in the region of interest through which a drone can fly through with configurably adequate GNSS coverage for autonomous flight irrespective of the time of flight, including:
sampling, over a range of hours of historical GNSS satellite path data, using a three-dimension model of the region of calculation, including ray casting from the cuboids to the historical paths of the GNSS satellites using the three-dimensional model to determine precision of GNSS coverage for cuboids; and
for each cuboid in the region of calculation, determining the lowest precision of GNSS coverage during the consecutive span of hours;
receiving and responding to a request for the worst-case risk analysis for a region of interest within the region of calculation by distributing the worst-case risk analysis for the region of interest.
21. The computer readable medium of claim 20 , further including:
wherein the worst-case risk analysis includes inadequate coverage zones; and
wherein the generating further includes padding worst zones with a buffer zone that extends outward from the inadequate coverage zones up to 10 meters.
22. The computer readable medium of claim 21 , wherein the buffer zone extends outward up to 5 meters.
23. The computer readable medium of claim 21 , further including:
generating, using the historical satellite data, a best-case risk analysis for the region of calculation that reveals cuboids in which, for at least a period of time in the historical GNSS satellite path data, a time-sensitive route is available; and
receiving a request for the best-case analysis for a second requested range of time and the region of interest and responding by distributing the best-case risk analysis.
24. The computer readable medium of claim 23 , further including:
requesting and receiving a forecast for at least the requested range of time covering at least the likely route; and
finding in the forecast at least one time during which the drone can fly from the starting location to the destination through the cuboids that have the configurably adequate GNSS coverage for a period within the range of time.