Personality sharing among drone swarm

• US 10,324,466 B2
• Filed: 01/27/2017
• Issued: 06/18/2019
• Est. Priority Date: 01/27/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Erickson, Thomas D., Fleming, Kala K., Pickover, Clifford A., Weldemariam, Komminist
• Primary Examiner(s): Cass, Jean Paul
• Application Number:
  US15/417,644
• Publication Number:
  US 20180217593A1
• Time in Patent Office: 872 Days
• Field of Search: 701 4
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• 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: G06N 3/008 based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. based on robots replicating pets or humans in their appearance or behaviour
• CPC Class Codes: G08G 5/0008 with other aircraft
• CPC Class Codes: G08G 5/0013 with a ground station
• CPC Class Codes: G08G 5/006 in accordance with predefined flight zones, e.g. to avoid prohibited zones
• CPC Class Codes: G08G 5/0069 specially adapted for an unmanned aircraft
• CPC Class Codes: G08G 5/0086 for monitoring terrain radar or analogous systems specially adapted for terrain avoidance G01S13/935

Abstract

A drone identifies situational context (based on signals from at least one sensor) and selects an action in response to the situational context, based on a personality of the drone. The drone then communicates its personality to other drones within a swarm of drones, the drone being a member of the swarm of drones.

Claims

1. A computer-implemented method comprising:

identifying, by a first drone, a situational context based on signals from at least one sensor;

selecting, by the first drone, an action based on an algorithm of the first drone that defines behaviors in response to the situational context, including movement, noise level, speed and responsivity to spoken language; and

communicating, by the first drone, the algorithm of the first drone to at least a second drone within a swarm of drones, the first drone being a member of the swarm of drones.

2. The method of claim 1 wherein the first drone communicates the algorithm to the at least second drone in response to a magnitude of a risk vector exceeding a threshold value.

3. The method of claim 1 further comprising receiving an algorithm of another drone in the swarm of drones, by the first drone, wherein the situational context includes the algorithm of the another drone in the swarm of drones.

4. The method of claim 1 wherein the situational context includes an identity of a recipient of drone actions.

5. The method of claim 1 further comprising:

receiving an algorithm of another drone in the swarm of drones, by the first drone, wherein the situational context includes the algorithm of the another drone in the swarm of drones; and

modifying, by the first drone, the algorithm of the first drone in response to the situational context.

6. The method of claim 5, further comprising providing a system, wherein the system comprises distinct software modules, each of the distinct software modules being embodied on a computer-readable storage medium, and wherein the distinct software modules comprise a situation awareness module, a personality manager module, and an amelioration action coordinator module;

wherein;

identifying situational context is facilitated by the situation awareness module executing on at least one hardware processor;

selecting an action is facilitated by the amelioration action coordinator module executing on the at least one hardware processor; and

modifying the algorithm of the first drone is facilitated by the personality manager module.

7. The method of claim 1 further comprising communicating, by the first drone, the algorithm of the first drone according to a learned pattern of propagation.

8. The method of claim 1 further comprising communicating, by the first drone, the algorithm of the first drone according to a learned rate of propagation.

9. The method of claim 1 wherein the algorithm of the first drone is configured for at least one of crop scouting or location security.

10. A computer program product for controlling a drone in a swarm of drones, the computer program product comprising a computer readable storage medium that embodies program instructions executable by a drone to cause the drone to:

identify situational context based on signals from at least one sensor;

select an action, based on an algorithm of the drone that defines behaviors in response to the situational context, including movement, noise level, speed, and responsivity to spoken language; and

communicate the algorithm of the drone to at least a second drone in the swarm.

11. The product of claim 10 wherein the program instructions are further executable to cause the drone to modify its algorithm.

12. The product of claim 11 wherein the program instructions are further executable to cause the drone to modify its algorithm in response to the situational context including an algorithm of another drone in the swarm.

13. The product of claim 10 wherein the situational context includes an identity of a recipient of drone actions.

14. The product of claim 10 wherein the program instructions are further executable to cause the drone to communicate its algorithm at a rate selected based on the situational context.

15. A drone apparatus comprising:

at least one sensor;

a memory;

a communications module; and

at least one processor, coupled in communication with the memory, the sensor, and the communications module, and operative to;

identify situational context based on signals from the at least one sensor;

select an action to take, based on an algorithm, facilitated in the processor, that defines behaviors in response to the situational context including movement, noise level, speed, and responsivity to spoken language; and

communicate the algorithm to another processor via the communications module.

16. The apparatus of claim 15 wherein the at least one processor is further operative to communicate the algorithm at a rate selected based on the situational context.

17. The apparatus of claim 15 wherein the situational context includes an algorithm of another drone in the swarm of drones.

18. The apparatus of claim 15 wherein the situational context includes an identity of a recipient of drone actions.

19. The apparatus of claim 15 wherein the processor is further operative to modify the algorithm in response to the situational context.

20. The apparatus of claim 19, further comprising a plurality of distinct software modules, each of the distinct software modules being embodied on a computer-readable storage medium, and wherein the distinct software modules comprise a situation awareness module, a personality manager module, and an amelioration action coordinator module;

wherein;

said at least one processor is operative to identify the situational context by executing said situation awareness module;

said at least one processor is operative to select the action by executing said amelioration action coordinator module; and

said at least one processor is operative to modify the algorithm by executing said personality manager module.