Reconfigurable autonomous device networks

• US 7,266,532 B2
• Filed: 06/03/2002
• Issued: 09/04/2007
• Est. Priority Date: 06/01/2001
• Status: Expired due to Fees

• Current Assignee: The General Hospital Corporation (Mass General Brigham, Inc.)
• Original Assignee: The General Hospital Corporation (Mass General Brigham, Inc.)
• Inventors: Jamieson, Ian MacQueen Drummond, Sutton, Jeffrey P.
• Primary Examiner(s): Hirl; Joseph P
• Application Number:
  US10/161,058
• Publication Number:
  US 20030005030A1
• Time in Patent Office: 1,919 Days
• Field of Search: 706/12, 706/14, 706/46
• US Class Current: 706/12
• CPC Class Codes: H04L 67/12 specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 69/329 in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 Network security protocols
• CPC Class Codes: H04W 40/00 Communication routing or communication path finding

Abstract

The present invention describes the use of autonomous devices, which can be arranged in networks, such as neural networks, to better identify, track, and acquire sources of signals present in an environment. The environment may be a physical environment, such as a battlefield, or a more abstract environment, such as a communication network. The devices may be mobile, in the form of vehicles with sensors, or may be information agents, and may also interact with one another, thus allowing for a great deal of flexibility in carrying out a task. In some cases, the devices may be in the form of autonomous vehicles which can collaboratively sense, identify, or classify a number of sources or targets concurrently. The autonomous devices may function as mobile agents or attractors in a network, such as a neural network. The devices may also be aggregated to form a network of networks and provide scalability to a system in which the autonomous devices are operating.

Claims

1. A system comprising:

first and second autonomous devices for collaboratively identifying objects in an environment, each autonomous device comprising;

a sensor unit adapted to sense information relating to an object;

a storage unit containing object template information corresponding to the object;

a computation unit adapted to process the sensed signals, wherein the computation unit comprises an algorithm to compute a degree of match between the sensed signals and the object template information;

a communication unit adapted to communicate information relating to operation of the autonomous device with other devices;

a control unit adapted to make a decision affecting a status of the autonomous device based at least on a result of the computation of the degree of match; and

a mobility unit, which receives instructions from the control unit, and is adapted to move the autonomous device from one location to another;

wherein the autonomous device is adapted to automatically move to increase the degree of match between the sensed signals and the object template information; and

wherein the computation unit is adapted to identify the object by determining that the degree of match has exceeded a predetermined threshold;

wherein the first autonomous device directly transmits information relating to the object to the second autonomous device, and the second autonomous device reconfigures itself in space, without human intervention, based at least in part on said transmitted information; and

wherein at least the first and second autonomous devices operatively collaborate to identify the objects in the environment.

2. The system of claim 1, further comprising a positioning unit adapted for determining the position of the device in the environment.

3. The system of claim 2, wherein the positioning unit comprises any one of:

a global positioning system (GPS), an inertial navigation system and a signal beacon guided system.

4. The system of claim 1, further comprising a learning unit which executes machine learning algorithms that improve an ability of the autonomous device to classify objects.

5. The system of claim 4, wherein the learning unit is adapted to execute new algorithms or use new data tat was not initially loaded into the learning unit.

6. The system of claim 1, wherein the autonomous device is a member of a network of autonomous devices which can communicate over a communication channel.

7. The system of claim 1, wherein the storage unit comprises a database containing pre-programmed object template information.

8. The device system of claim 7 wherein the storage unit is adapted to accept new information to modify the database.

9. The system of claim 1, wherein the autonomous device is a lead autonomous device and is adapted to coordinate the operation of at least one other device acting as a wing device tat assists the lead autonomous device in identifying an object.

10. The system of claim 1, wherein the autonomous device is coupled aver a communication channel to a central communication unit that centrally communicates with the autonomous device and other autonomous devices operating in the environment.

11. The system of claim 1, wherein the decision affecting the status of the autonomous device is a decision to transmit communication information to another autonomous device.

12. The system of claim 1, wherein the decision affecting the status of the autonomous device is a decision to move the autonomous device from one location to another.

13. The system of claim 1, wherein the decision affecting the status of the autonomous device is a decision to switch the autonomous device from one mode of operation to another.

14. A method for identifying objects in an environment, comprising:

providing at least first and second mobile autonomous devices for operation in the environment the first and second autonomous devices respectively comprising first and second databases and first and second sensors;

providing object template data, corresponding to the objects, in the first and second databases;

sensing signals from a first object using the first sensor;

using the first autonomous device, evaluating a degree of match between an object template and the sensed signals, wherein the first autonomous device automatically moves to increase the degree of match between the sensed signals and the object template and identifies the object by determining that the degree of match has exceeded a predetermined threshold;

directly transmitting information relating to the object from the first autonomous device to the second autonomous device; and

reconfiguring the second autonomous device in space, without human intervention, based at least in part on said transmitted information.

15. The method of claim 14, wherein the action comprises switching the autonomous device from one mode of operation to another.

16. The method of claim 14, further comprising communicating information between the at least one autonomous device to a second autonomous device, the information being for collaborative identification of the object.

17. The method of claim 16, wherein the at least one autonomous device and the second device operate in a communication network.

18. A system for identifying at least one object in an environment, comprising:

a first autonomous device which detects at least a first signal from the object;

a second autonomous device which detects at least a second signal from the abject; and

a communication network which connects the first and second autonomous devices and directly passes information between said first and second autonomous devices;

wherein each of said first and second autonomous devices each comprises a control module, a sensor module, and a communications module;

wherein the first autonomous device is adapted to evaluate a first match between the first signal and a first reference object template and transmit a result of said evaluation directly to the second autonomous device over the communication network;

wherein the second autonomous device is adapted to reconfigure itself in space, without human intervention, based at least in part on the result of said evaluation; and

wherein said first and second matches arc indicative of an identity of the at least one object in the environment.

19. The system of claim 18, further comprising an external controller that coordinates communication between the first and second autonomous devices.

20. The system of claim 18, wherein the first and second autonomous devices are elements in a first network of devices, and wherein the system further comprises a second network of devices, similar to the first network of devices and in communication with the first network.

21. A system comprising:

a network comprising first and second autonomous devices for collaboratively identifying objects in an environment, each autonomous device comprising;

a sensor unit adapted to sense information relating to an object;

a storage unit containing object template information corresponding to the object;

a computation unit adapted to process the sensed signals, wherein the computation unit comprises an algorithm to compute a degree of match between the sensed signals and the object template information;

a communication unit adapted to communicate information relating to operation of the autonomous device with other devices; and

a control unit adapted to make a decision affecting a status of the autonomous device based at least on a result of the computation of the degree of match;

wherein the first and second autonomous devices respectively comprise first and second sensors adapted to sense a condition relating to the performance of the network and wherein the first and second autonomous devices are respectively adapted to carry first and second information pertaining to the condition; and

wherein the first autonomous device is adapted to receive the second information pertaining to the condition and update the first information pertaining to the condition based on the second information; and

wherein the first autonomous devices is adapted to reconfigure itself in space, without human intervention, based at least in part on the second information.

22. The system of claim 21, wherein the system further comprises first and second nodes, and wherein said first autonomous device is adapted to move information from the first node to the second node by moving from the first node to the second node while carrying the first information within the autonomous device.

23. The system of claim 21, wherein the system further comprises first and second nodes, and wherein said first autonomous device is adapted to move information from the first node to the second node by transmitting an information packet containing the first information to said second node.

24. The system of claim 21, wherein said condition corresponds to a communication signal travel time.

25. The system of claim 21, wherein each autonomous device carries a representation of the condition across the network in its entirety.

26. A method for determining an optimum configuration of agents operating in an environment, the method comprising:

sensing, using a first agent in the environment, a first environmental signal;

forming a first representation of the first environmental signal;

sensing, using a second agent in the environment, a second environmental signal;

forming a second representation of the second environmental signal;

directly exchanging, between the first and second agents, the respective first and second representations;

within the first or second agent, computing a performance metric corresponding to a first configuration of the first and second agents, the performance metric corresponding to an overlap between an environmental signal and a stored target template; and

reconfiguring the first and second agents, based on the performance metric and without human intervention, to arrive at a new configuration of the first and second agents.

27. The method of claim 26, further comprising making a decision to include a third agent in the new configuration.

28. The method of claim 26, wherein the first and second agents are autonomous devices.

29. The method of claim 28, wherein the autonomous devices are mobile autonomous vehicles.

30. The method of claim 29, wherein the mobile autonomous vehicles are any of:

airborne vehicles, land vehicles and waterborne vehicles.

31. The method of claim 26, wherein the acts of the method are carried out as a simulation running on a machine executing programmed instructions.

32. The method of claim 26, wherein determination of the optimum configuration provides information regarding scalability of the system as the number and type of agents is varied.