Mission prioritization and work order arrangement for unmanned aerial vehicles and remotely-piloted vehicles

• US 10,043,397 B2
• Filed: 02/01/2016
• Issued: 08/07/2018
• Est. Priority Date: 02/01/2015
• Status: Active Grant

• Current Assignee: DTN, LLC (TBG AG)
• Original Assignee: Clear AG Incorporated
• Inventors: Salentiny, Dustin M., Mewes, John J.
• Primary Examiner(s): Black, Thomas G
• Assistant Examiner(s): Smith-Stewart, Demetra R
• Application Number:
  US15/012,510
• Publication Number:
  US 20160225263A1
• Time in Patent Office: 918 Days
• Field of Search: None
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64U 2201/10 autonomous, i.e. by navigating independently from ground or air stations, e.g. by using inertial navigation systems [INS]
• CPC Class Codes: B64U 2201/20 Remote controls
• CPC Class Codes: G05D 1/00 Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots drive control systems specially adapted for autonomous road vehicles B60W60/00
• CPC Class Codes: G05D 1/0061 for transition from automatic pilot to manual pilot and vice versa
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/003 Flight plan management
• CPC Class Codes: G08G 5/0034 Assembly of a flight plan
• CPC Class Codes: G08G 5/0039 Modification of a flight plan
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft
• CPC Class Codes: G08G 5/0091 for monitoring atmospheric conditions radar or analogous systems specially adapted for meteorological use G01S13/95; meteorology G01W

Abstract

A framework for combining a weather risk analysis with appropriate operational rules includes a data initialization component, a rules processing component, and one or more weather risk analysis and assessment tools to evaluate a flight condition. The framework applies current, historical, predicted and forecasted weather data to the one or more operational rules governing a mission, a payload, a flight plan, a craft type, and a location of the mission for aircraft such as an unmanned aerial vehicle or remotely-piloted vehicle, and generates advisories based on the evaluation of flight conditions such as a mission compliance status, instructions for operation of unmanned aircraft, and management advisories. The flight condition advisories include either a “fly” advisory or a “no-fly” advisory, and the framework may also provide a mission prioritization and optimization system.

Claims

1. A method, comprising:

ingesting, as input data, weather information, mission-specific flight parameters for unmanned aircraft, and operational rules for the unmanned aircraft, the weather information including at least one of current weather data, historical weather data, predicted weather data, and forecasted weather data for a specific geographic area, the mission-specific flight parameters defining flight plans for the unmanned aircraft in the specific geographic area and one or more work orders for the unmanned aircraft that include constraints and variables affecting satisfaction of the constraints, and the operational rules at least relating to mission performance;

analyzing the input data in a plurality of data processing modules within a computing environment in which the plurality of data processing modules are executed in conjunction with at least one processor, the data processing modules configured to perform a mission priority assessment for the unmanned aircraft relative to the weather information and the mission-specific flight parameters, by applying a constraint satisfaction analysis to

     1) determine a significance of each variable to the one or more work orders at least from computing one or more mission risk probabilities in a weather-based statistical analysis,

     2) assign weights to each constraint, based on the significance of each variable to the one or more work orders,

     3) adjust the weighted constraints by continually learning the significance of each variable from one or more factors affecting particular weather conditions in the weather-based statistical analysis for the performance of the one or more work orders, and

     4) prioritize flight plans for each work order based on the weighted constraints, and comparing the constraint satisfaction analysis with the operational rules to evaluate a flight condition of the unmanned aircraft for mission performance; and

generating, as output data, one or more of a mission compliance status confirming or denying compliance with the operational rules for the mission performance, and an operational instruction comprised of an arrangement of the work orders for the unmanned aircraft according to the prioritized flight plans.

2. The method of claim 1, wherein the constraints include a work order type, a suitability of weather conditions to a work order, and a time sensitivity of a work order, and wherein the variables affecting satisfaction of the constraints include travel time between geographical work order locations, changes in weather conditions over specified period of time for completion of a work order, and availability of one or more of unmanned aircraft, crews operating the unmanned aircraft, and the payload.

3. The method of claim 1, further comprising confirming a validity of a flight certificate of mission authorization, and delivering a signed authorization certificate to conduct the mission.

4. The method of claim 1, wherein the applying a constraint satisfaction analysis to determine a significance of each variable to the one or more work orders further comprises determining the weights of each constraint by automatically developing an artificial intelligence model to continually learn the significance of each variable to the one or more work orders.

5. The method of claim 1, wherein the applying a constraint satisfaction analysis to determine a significance of each variable to the one or more work orders further comprises determining the weights of each constraint from one or more human interactions that manually adjust the significance of each variable.

6. The method of claim 1, wherein the forecasted whether data includes near-term weather forecasts and extended-range weather forecasts.

7. The method of claim 1, wherein the flight condition is at least one of a pre-flight condition, an in-flight condition, and a post-flight condition.

8. The method of claim 1, wherein the arrangement of the work orders is a list of work orders for a plurality of unmanned aircraft.

9. The method of claim 1, wherein the operational instruction is at least one of a fly instruction, a takeoff prevention instruction, a payload instruction, and a recovery interference prevention instruction.

10. The method of claim 1, wherein the operational instruction is an adjustment of the flight plans by modifying one or more of the mission-specific flight parameters.

11. The method of claim 1, wherein one or more of the data processing modules are performed by a device embedded on board the unmanned aircraft.

12. A flight prioritization system for unmanned aircraft, comprising:

a data ingest and initialization component configured to retrieve, store, and arrange weather information comprised of at least one of current weather data, historical weather data, predicted weather data, and forecasted weather data for a specific geographic area, mission-specific flight parameters defining flight plans for the unmanned aircraft in the specific geographic area, and one or more work orders for the unmanned aircraft that include constraints and variables affecting satisfaction of the constraints, and operational rules governing mission performance;

a mission analytics component configured to perform a mission priority assessment for the unmanned aircraft relative to the weather information and the mission-specific flight parameters, by applying a constraint satisfaction analysis to

     1) determine a significance of each variable to the one or more work orders at least from computing one or more mission risk probabilities in a weather-based statistical analysis,

     2) assign weights to each constraint, based on the significance of each variable to the one or more work orders,

     3) adjust the weighted constraints by continually learning the significance of each variable from one or more factors affecting particular weather conditions in the weather-based statistical analysis for the performance of the one or more work orders, and

     4) prioritize flight plans for each work order based on the weighted constraints, and comparing the constraint satisfaction analysis with the operational rules to evaluate a flight condition of the unmanned aircraft for mission performance; and

one or more components configured to generate output data that includes a mission compliance status confirming or denying compliance with the operational rules and an operational instruction comprised of an arrangement of the work orders for the unmanned aircraft according to the prioritized flight plans.

13. The system of claim 12, wherein the data ingest and initialization component, the mission analytics components, and the one or more components configured to generate output data are performed by a device embedded on the unmanned aircraft.

14. The system of claim 12, wherein the arrangement of the work orders is a list of work orders for a plurality of unmanned aircraft.

15. The system of claim 12, wherein the operational instruction is at least one of a fly instruction, a takeoff prevention instruction, a payload instruction, and a recovery interference prevention instruction.

16. The system of claim 12, further comprising a flight control component configured to restrict ground control of the unmanned aircraft in response to an operational instruction.

17. The system of claim 12, further comprising a flight certification module configured to confirm a flight certificate validity and deliver a signed authorization certificate for the unmanned aircraft to perform the mission.

18. The system of claim 12, wherein the forecasted whether data includes near-term weather forecasts and extended-range weather forecasts.

19. The system of claim 12, wherein the flight condition is at least one of a pre-flight condition, an in-flight condition, and a post-flight condition.

20. The system of claim 12, wherein the constraints include a work order type, a suitability of weather conditions to a work order, and a time sensitivity of a work order, and wherein the variables affecting satisfaction of the constraints include travel time between geographical work order locations, changes in weather conditions over specified period of time for completion of a work order, and availability of one or more of unmanned aircraft, crews operating the unmanned aircraft, and the payload.

21. The system of claim 12, wherein the mission analytics component is further configured to determine a significance of each variable to the one or more work orders further comprises by automatically developing an artificial intelligence model to continually learn the significance of each variable to the one or more work orders.

22. The system of claim 12, wherein the mission analytics component is further configured to determine a significance of each variable to the one or more work orders further comprises from one or more human interactions that manually adjust the significance of each variable.

23. A method of ordering mission priority for unmanned aircraft, comprising:

retrieving and initializing a plurality of inputs, the plurality of inputs including weather information comprised of least one of current weather data, historical weather data, predicted weather data, and forecasted weather data for a specific geographic area, and including mission-specific flight parameters defining flight plans for the unmanned aircraft in the specific geographic area and one or more work orders for the unmanned aircraft that include constraints and variables affecting satisfaction of the constraints;

retrieving one or more appropriate operational rules for performing missions by the unmanned aircraft based on the plurality of inputs;

prioritizing flight plans for each work order, by applying a constraint satisfaction analysis using the weather information and the mission-specific flight parameters to assign weights for each constraint to the one or more work orders based on a significance of each variable to the one or more work orders, the weights determined by automatically developing an artificial intelligence model to continually learn the significance of each variable to the one or more work orders and adjust the weights assigned to each constraint based on the learned significance of each variable and on one or more particular weather conditions impacting the weather-based statistical analysis for the performance of the one or more work orders in the specific geographic area, and compare the constrain satisfaction analysis with the operational rules in a mission priority assessment; and

issuing a flight advisory representing the mission priority assessment to at least one of an operator of the unmanned aircraft and to a device embedded on the unmanned aircraft.

24. The method of claim 23, wherein the advisory either confirms or denies compliance with the one or more operational rules for the mission.

25. The method of claim 23, wherein the advisory is an operational instruction for the unmanned aircraft, the operational instruction comprising at least one of a fly instruction, a takeoff prevention instruction, a payload instruction, and a recovery interference prevention instruction.

26. The method of claim 23, wherein the advisory is an operational instruction comprising an arrangement of the work orders for a plurality of the unmanned aircraft.

27. The method of claim 23, further comprising confirming a validity of a flight certificate of mission authorization, and delivering a signed authorization certificate to conduct the mission.

28. The method of claim 23, wherein the forecasted whether data includes near-term weather forecasts and extended-range weather forecasts.

29. The method of claim 23, wherein the constraints include a work order type, a suitability of weather conditions to a work order, and a time sensitivity of a work order, and wherein the variables affecting satisfaction of the constraints include travel time between geographical work order locations, changes in weather conditions over specified period of time for completion of a work order, and availability of one or more of unmanned aircraft, crews operating the unmanned aircraft, and the payload.

30. The method of claim 23, wherein the weights are further determined from one or more human interactions that manually adjust the significance of each variable.