Specialized contextual drones for virtual fences

• US 10,820,574 B2
• Filed: 07/29/2016
• Issued: 11/03/2020
• Est. Priority Date: 07/29/2016
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Gordon, Michael S., Kozloski, James Robert, Kundu, Ashish, Pickover, Clifford A.
• Primary Examiner(s): Smith, Isaac G
• Application Number:
  US15/223,351
• Publication Number:
  US 20180027772A1
• Time in Patent Office: 1,558 Days
• Field of Search: 701 3, 701 25, 701 26
• CPC Class Codes: A01K 1/0029 Crowding gates or barriers
• CPC Class Codes: A01K 15/023 Anti-evasion devices
• CPC Class Codes: A01K 29/005 Monitoring or measuring activity, e.g. detecting heat or mating
• CPC Class Codes: A01K 57/00 Appliances for providing, preventing or catching swarms; Drone-catching devices
• CPC Class Codes: B63G 8/001 Underwater vessels adapted for special purposes, e.g. unmanned underwater vessels; Equipment specially adapted therefor, e.g. docking stations self-propelled or direction controlled diving chambers with mechanical link to a base B63C11/42
• CPC Class Codes: B64C 39/024 of the remote controlled vehicle type, i.e. RPV
• CPC Class Codes: B64U 10/14 with four distinct rotor axes, e.g. quadcopters
• CPC Class Codes: B64U 2101/00 UAVs specially adapted for particular uses or applications
• CPC Class Codes: B64U 2101/31 for surveillance
• CPC Class Codes: G05D 1/104 involving a plurality of aircrafts, e.g. formation flying traffic control systems for aircraft G08G5/00

Abstract

Techniques for drone device control are provided. In one example, a computer-implemented method comprises establishing, by a plurality of drone devices respectively operatively coupled to processors and coordinating with one other, a defined region of a defined coordinate space of a geographic area, wherein the defined region is associated with an animal. The computer-implemented method also comprises monitoring, by the plurality of drone devices, a physical relationship between the animal and the defined region. The computer-implemented method can also comprise, in response to identifying that the physical relationship between the animal and the defined region fails to meet a criterion, performing, by the plurality of drone devices, a pattern of operations selected to alter the physical relationship between the animal and the defined region to satisfy the criterion.

Claims

1. A computer-implemented method, comprising:

analyzing, by a plurality of drone devices respectively operatively coupled to processors, a physical environment of a geographic area in which one or more animals are located to generate respective environment information about the physical environment, wherein the analysis is performed using respective instruments of drone devices of the plurality of drone devices;

selecting, by a drone device of the plurality of drone devices based on the respective environment information received by the drone device from other drone devices of the plurality of drone devices via a communication network, a defined region, of a defined coordinate space of the geographic area, that surrounds the one or more animals, where the defined region is selected to mitigate at least one risk of the physical environment to the one or more animals, wherein the selecting comprises;

determining a water feature of the physical environment based on the respective environment information,

determining a capability of the one or more animals with respect to the one or more animals interacting with the water feature in relation to the at least one risk to the one or more animals, and

including a portion of the water feature in the defined region that is selected based on the determined capability of the one or more animals in relation to the portion of the water feature;

communicating, by the drone device via the communication network, data indicating the defined region to the other drone device;

maintaining, by the plurality of drone devices based on the data indicating the defined region, a virtual fence around the defined region; and

monitoring, by the plurality of drone devices, respective physical relationships between the one or more animals and the defined region.

2. The computer-implemented method of claim 1, further comprising:

in response to identifying that the physical relationship between an animal of the one or more animals and the defined region fails to meet a criterion, performing, by the plurality of drone devices, a pattern of operations selected to alter the physical relationship between the animal and the defined region to satisfy the criterion.

3. The computer-implemented method of claim 2, wherein the pattern of operations comprises a movement pattern of the plurality of drone devices.

4. The computer-implemented method of claim 2, wherein the pattern of operations comprises a visual indication presented by a drone of the plurality of drone devices.

5. The computer-implemented method of claim 2, wherein the pattern of operations comprises an audio indication presented by a drone device of the plurality of drone devices.

6. The computer-implemented method of claim 2, wherein the pattern of operations comprises a physical stimulation presented by a drone device of the plurality of drone devices.

7. The computer-implemented method of claim 2, wherein the monitoring is performed using the respective instruments of the drone devices.

8. The computer-implemented method of claim 2, wherein the monitoring comprises identifying a defined condition predicted to cause the physical relationship between the animal and the defined region fail to satisfy the criterion.

9. The computer-implemented method of claim 8, wherein the defined condition comprises the identification of a predator animal, and the performing the pattern of operations comprises performing an action to drive the predator animal to a defined distance away from the defined coordinate space.

10. The computer-implemented method of claim 2, wherein the pattern of operations is selected according to a learning algorithm that learns a behavior of the animal relative to the defined region.

11. The computer-implemented method of claim 2, wherein the pattern of operations is selected according to a learning algorithm that learns effectiveness of an operation performed by a drone device of the plurality of drone devices relative to alteration of the physical relationship between the animal and the defined region.

12. The computer-implemented method of claim 1, further comprising modifying, by the at least one drone of the plurality of drone devices, the defined region based on a defined condition in the physical environment detected by at least one drone of the plurality of drone devices.

13. A computer program product for managing one or more virtual boundaries of a defined region, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a drone device to cause the drone device to:

analyze, using at least one instrument of the drone device, a physical environment of a geographic area in which one or more animals are located to generate environment information about the physical environment;

receive, via at least one communication link from at least one other drone device, respective other environment information about the physical environment generated by the at least one other drone device;

select, based on the environment information and the respective other environment information, a defined region, of a coordinate space of the geographic area, that surrounds the one or more animals, wherein the defined region is selected to mitigate at least one risk of the physical environment to the one or more animals, wherein the selection of the defined region comprises;

determine a water feature of the physical environment based on the environment information and the respective environment information,

determine a capability of the one or more animals with respect to the one or more animals interacting with the water feature in relation to the at least one risk to the one or more animals, and

include a portion of the water feature in the define region that is chosen based on the determined capability of the one or more animals in relation to the portion of the water feature;

monitor, with the at least one other drone device, one or more virtual boundaries of the defined region;

determine a violation associated with the one or more virtual boundaries of the defined region based on the monitoring;

determine one or more actions to perform by the drone device and the at least one other drone device to continue to monitor the one or more virtual boundaries of the defined region and mitigate the violation associated with the one or more virtual boundaries of the defined region; and

perform, via communication of data indicating the one or more actions using the at least one communication link with the at least one other drone device, the one or more actions.

14. The computer program product of claim 13, wherein the violation comprises an animal of the one or more animals being located outside of the defined region and a status associated with the animal indicating that the animal is to be maintained inside the defined region.

15. The computer program product of claim 14, wherein the one or more actions comprises using one or more instruments of the drone device to produce one or more stimuli to drive the animal back into the defined region.

16. The computer program product of claim 13, wherein the violation comprises of the one or more animals being animal being located inside of the defined region and a status associated with the animal indicating that the animal is to be maintained outside of the defined region.

17. The computer program product of claim 16, wherein the one or more actions comprises using one or more instruments of the drone device to produce one or more stimuli to drive the animal out of the defined region.

18. A drone device, comprising:

a memory that stores computer executable components; and

a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise;

a boundary component that;

analyzes, using at least one instrument of the drone device, a physical environment of a geographic area in which one or more animals are located to generate environment information about the physical environment;

selects, based on the environment information, a defined region, of a coordinate space of the geographic area, that surrounds the one or more animals, wherein the defined region is selected to mitigate at least one risk of the physical environment to the one or more animals, wherein the selection of the defined region comprises;

determine a water feature of the physical environment based on the environment information and the respective environment information,

determine a capability of the one or more animals with respect to the one or more animals interacting with the water feature in relation to the at least one risk to the one or more animals, and

include a portion of the water feature in the define region that is chosen based on the determined capability of the one or more animals in relation to the portion of the water feature;

a monitoring component that determines, based on information related to maintaining the defined region exchanged with at least one other drone device, whether a violation associated with a virtual boundary of the defined region has occurred; and

a violation response component that determines an action to be performed by the drone device to mitigate the violation.

19. The drone device of claim 18, wherein the violation response component also implements the action to be performed by the drone device.

20. The drone device of claim 18, wherein the violation response component also learns additional information associated with effectiveness of actions performed to mitigate violations of the virtual boundary of the defined region.