Drone carrier

• US 10,013,886 B2
• Filed: 03/08/2016
• Issued: 07/03/2018
• Est. Priority Date: 03/08/2016
• Status: Active Grant

• Current Assignee: NEC Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Blomberg, Jeanette L., Butler, Eric K., Chandra, Anca A., Chowdhary, Pawan R., Griffin, Thomas D., Jadav, Divyesh, Jiang, Shun, Lee, Sunhwan, Moore, Robert J., Strong, Jr., Hovey R., Tan, Chung-hao
• Primary Examiner(s): Chen, Shelley
• Application Number:
  US15/064,550
• Publication Number:
  US 20170263131A1
• Time in Patent Office: 847 Days
• Field of Search: None
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64U 70/87 using inflatable cushions
• CPC Class Codes: G05B 19/0426 Programming the control sequence
• CPC Class Codes: G05B 2219/23328 Modification program
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/0026 located on the ground
• 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 5/0043 Traffic management of multiple aircrafts from the ground G08G5/003 takes precedence; data processing specially designed for resource management, e.g. scheduling or allocating time, human or machine resources G06Q10/06
• CPC Class Codes: G08G 5/0056 in an emergency situation, e.g. hijacking
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft
• CPC Class Codes: G08G 5/0082 for monitoring traffic from a ground station radar or analogous systems specially adapted for traffic control G01S13/91

Abstract

Embodiments of the present invention provide a method comprising receiving a task set comprising multiple tasks, receiving operational information identifying one or more operating characteristics of multiple drones, and obtaining an initial heuristic ordering of the multiple tasks based on the operational information and the climate information. Each task has a corresponding task location. The method further comprises scheduling the multiple tasks to obtain a final ordering of the multiple tasks. The final ordering represents an order in which the multiple tasks are scheduled, and the final ordering may be different from the initial heuristic ordering.

Claims

1. A method, comprising:

receiving a task set comprising multiple tasks, wherein each task has a corresponding task location;

receiving operational information identifying one or more operating characteristics of multiple drones;

obtaining an initial heuristic ordering of the multiple tasks based on the operational information and climate information; and

scheduling the multiple tasks to obtain a final ordering of the multiple tasks, wherein the final ordering represents an order in which the multiple tasks are scheduled, and the final ordering may be different from the initial heuristic ordering.

2. The method of claim 1, further comprising:

for each task, receiving the climate information identifying estimated wind conditions within proximity of a corresponding task location for the task.

3. The method of claim 2, wherein:

the initial heuristic ordering is based on a recursive polygonal spiral course for a drone receiver carrying the multiple drones; and

for each task, the drone receiver is scheduled to approach a corresponding task location for the task to within a distance, the distance being computed based on one or more operating characteristics of a drone of the multiple drones that will be scheduled to perform the task and estimated wind conditions within proximity of the task.

4. The method of claim 3, wherein the distance is also computed based on a limiting unpowered falling velocity of the drone that will perform the task, such that the drone receiver is capable of catching the drone if the drone encounters a power failure during a horizontal move, wherein the horizontal move is performed at a pre-specified elevation above an elevation of the drone receiver.

5. The method of claim 4, wherein the drone receiver catches a drone that encounters a power failure.

6. The method of claim 5, wherein the drone receiver comprises one or more mechanical shock absorbers to facilitate catching a drone that encounters a power failure.

7. The method of claim 1, wherein:

the initial heuristic ordering is computed by applying a heuristic, approximate solution to the planar traveling salesman problem; and

the final ordering is a modification of the initial heuristic ordering based on scheduling the multiple tasks when they become feasible, even if out of order.

8. The method of claim 1, further comprising:

setting a heading toward a task location corresponding to a first task of the initial heuristic ordering.

9. The method of claim 1, further comprising:

scheduling the launch of a drone of the multiple drones to perform a task when the drone is within a feasible distance of the task location independent of any initial heuristic ordering.

10. The method of claim 9, further comprising:

scheduling, when the carrier is within the feasible distance of a task location corresponding to the first task of the initial heuristic ordering, the launch of a drone of the multiple drones to perform the first task, scheduling continuing on the same heading, and, if necessary, scheduling waiting for the return of the drone, and scheduling subsequent re-setting of the heading towards another task location corresponding to another task of the initial heuristic ordering that has not already been scheduled for visit.

11. The method of claim 1, further comprising:

managing a group flight plan request for a group of drones utilizing shared locks for 4D cells for the group, and computing feasibility of the request utilizing a heuristic solution that is based on maximum distance to a location specified in a task.

12. A system comprising a computer processor, a computer-readable hardware storage medium, and program code embodied with the computer-readable hardware storage medium for execution by the computer processor to implement a method comprising:

receiving a task set comprising multiple tasks, wherein each task has a corresponding task location;

receiving operational information identifying one or more operating characteristics of multiple drones;

obtaining an initial heuristic ordering of the multiple tasks based on the operational information and climate information; and

scheduling the multiple tasks to obtain a final ordering of the multiple tasks, wherein the final ordering represents an order in which the multiple tasks are scheduled, and the final ordering may be different from the initial heuristic ordering.

13. The system of claim 12, the method further comprising:

for each task, receiving the climate information identifying estimated wind conditions within proximity of a corresponding task location for the task.

14. The system of claim 13, wherein:

the initial heuristic ordering is based on a recursive polygonal spiral course for a drone receiver carrying the multiple drones; and

for each task, the drone receiver is scheduled to approach a corresponding task location for the task to within a distance, the distance being computed based on one or more operating characteristics of a drone of the multiple drones that will be scheduled to perform the task and estimated wind conditions within proximity of the task.

15. The system of claim 12, wherein the distance is also computed based on a limiting unpowered falling velocity of the drone that will perform the task, such that the drone receiver is capable of catching the drone if the drone encounters a power failure during a horizontal move, wherein the horizontal move is performed at a pre-specified elevation above an elevation of the drone receiver.

16. The system of claim 15, wherein the drone receiver catches a drone that encounters a power failure.

17. The system of claim 12, wherein the drone receiver comprises one or more mechanical shock absorbers to facilitate catching a drone that encounters a power failure.

18. The system of claim 12, wherein:

the initial heuristic ordering is computed by applying a heuristic, approximate solution to the planar traveling salesman problem; and

the final ordering is a modification of the initial heuristic ordering based on scheduling the multiple tasks when they become feasible, even if out of order.

19. The system of claim 12, the method further comprising:

setting a heading toward a task location corresponding to a first task of the initial heuristic ordering.

20. A computer program product comprising a computer-readable hardware storage device having program code embodied therewith, the program code being executable by a computer to implement a method comprising:

receiving a task set comprising multiple tasks, wherein each task has a corresponding task location;

receiving operational information identifying one or more operating characteristics of multiple drones;

obtaining an initial heuristic ordering of the multiple tasks based on the operational information and climate information; and

scheduling the multiple tasks to obtain a final ordering of the multiple tasks, wherein the final ordering represents an order in which the multiple tasks are scheduled, and the final ordering may be different from the initial heuristic ordering.