Utilizing 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 routing an autonomous drone using GNSS data by using a worst-case of risk analyses for planning, the method including:
obtaining from a risk analysis server a worst-case risk analysis, covering a selected period, responsive to a requested area, wherein the worst-case risk analysis identifies cuboids in an area through which a drone can fly throughout the selected period with GNSS coverage that meets a coverage threshold that is specified as adequate for autonomous flight guidance;
identifying, by a first routing algorithm, a route through the cuboids identified as having the adequate GNSS coverage, from a starting location to a destination.
2 . The method of claim 1 , further including routing the autonomous drone over the identified route.
3 . The method of claim 1 , wherein the configurably adequate GNSS coverage is defined by a target precision percentage.
4 . The method of claim 1 , wherein adequate GNSS coverage is met when the precision of GNSS coverage satisfies requirements of a Federal Aviation Administration (FAA).
5 . A method of routing an autonomous drone using GNSS data by using a worst-case and then a best-case pair of risk analyses for planning, the method including:
obtaining from a risk analysis server a worst-case risk analysis responsive to a requested area that identifies first cuboids in the requested area through which a drone can fly throughout at least the requested area with configurably adequate GNSS coverage for autonomous flight guidance;
attempting but failing to identify, by a first routing algorithm, a route through the first cuboids identified as having the adequate GNSS coverage, from a starting location to a destination,
obtaining a best-case risk analysis responsive to the requested area that identifies second cuboids in the requested area through which the drone can fly at some times with the configurably adequate GNSS coverage for autonomous flight guidance;
identifying, by a second routing algorithm, a time-dependent route between the starting location and the destination.
6 . The method of claim 5 , further including routing a vehicle over the time-dependent route from the starting location to destination.
7 . The method of claim 5 , further including
obtaining supplemental time-dependent forecast data that:
includes the start location and the destination of the autonomous vehicle, and
predicts adequacy of GNSS coverage at intervals over time for third cuboids along at least one route from the start location to the destination; and
routing the drone using supplemental time-dependent forecast data.
8 . A non-transitory computer readable medium impressed with computer program instructions that, when executed on hardware, cause the hardware to carry out actions of routing an autonomous drone using GNSS data by using a worst-case of risk analyses for planning, the actions including:
obtaining from a risk analysis server a worst-case risk analysis, covering a selected period, responsive to a requested area, wherein the worst-case risk analysis identifies cuboids in an area through which a drone can fly throughout the selected period with GNSS coverage that meets a coverage threshold that is specified as adequate for autonomous flight guidance;
identifying, by a first routing algorithm, a route through the cuboids identified as having the adequate GNSS coverage, from a starting location to a destination.
9 . The computer readable medium of claim 8 , further including actions routing the autonomous drone over the identified route.
10 . The computer readable medium of claim 8 , wherein the configurably adequate GNSS coverage is defined by a target precision percentage.
11 . The computer readable medium of claim 8 , wherein adequate GNSS coverage is met when the precision of GNSS coverage satisfies requirements of a Federal Aviation Administration (FAA).
12 . A system including hardware coupled to memory, the memory including the non-transitory computer readable medium impressed with computer program instructions of claim 8 .
13 . The system of claim 12 , further including actions routing the autonomous drone over the identified route.
14 . The system of claim 12 , wherein adequate GNSS coverage is met when the precision of GNSS coverage satisfies requirements of a Federal Aviation Administration (FAA).
15 . A non-transitory computer readable medium impressed with computer program instructions that, when executed on hardware, cause the hardware to carry out actions of routing an autonomous drone using GNSS data by using a worst-case and then a best-case pair of risk analyses for planning, the actions including:
obtaining from a risk analysis server a worst-case risk analysis responsive to a requested area that identifies first cuboids in an area through which a drone can fly throughout at least the requested area with configurably adequate GNSS coverage for autonomous flight guidance;
attempting but failing to identify, by a first routing algorithm, a route through the first cuboids identified as having the adequate GNSS coverage, from a starting location to a destination,
obtaining a best-case risk analysis responsive to the requested area that identifies second cuboids in the requested area through which the drone can fly at some times with the configurably adequate GNSS coverage for autonomous flight guidance;
identifying, by a second routing algorithm, a time-dependent route between the starting location and the destination.
16 . The computer readable medium of claim 15 , further including actions routing a vehicle over the time-dependent route from the starting location to destination.
17 . The computer readable medium of claim 16 , further including actions
obtaining supplemental time-dependent forecast data that:
includes the start location and the destination of the autonomous vehicle, and
predicts adequacy of GNSS coverage at intervals over time for third cuboids along at least one route from the start location to the destination; and
routing the drone using supplemental time-dependent forecast data.
18 . 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 routing an autonomous drone using GNSS data by using a worst-case and then a best-case pair of risk analyses for planning, the actions including:
obtaining from a risk analysis server a worst-case risk analysis responsive to a requested area that identifies first cuboids in an area through which a drone can fly throughout at least the requested area with configurably adequate GNSS coverage for autonomous flight guidance;
attempting but failing to identify, by a first routing algorithm, a route through the first cuboids identified as having the adequate GNSS coverage, from a starting location to a destination,
obtaining a best-case risk analysis responsive to the requested area that identifies second cuboids in the requested area through which the drone can fly at some times with the configurably adequate GNSS coverage for autonomous flight guidance;
identifying, by a second routing algorithm, a time-dependent route between the starting location and the destination.
19 . The system of claim 18 , further including actions
obtaining supplemental time-dependent forecast data that:
includes the start location and the destination of the autonomous vehicle, and
predicts adequacy of GNSS coverage at intervals over time for third cuboids along at least one route from the start location to the destination; and
routing the drone using supplemental time-dependent forecast data.