System and method for an open autonomy kernel (oak)

• US 7,574,497 B2
• Filed: 05/30/2002
• Issued: 08/11/2009
• Est. Priority Date: 06/01/2001
• Status: Active Grant

• Current Assignee: Johns Hopkins University
• Original Assignee: Johns Hopkins University
• Inventors: Scheidt, David H., Vick, Shon D., Alger, David L., McCubbin, Christopher B., Watson, David P.
• Primary Examiner(s): Vaughn, Jr; William C
• Assistant Examiner(s): PEREZ, CARLOS R
• Application Number:
  US10/344,876
• Publication Number:
  US 20030182354A1
• Time in Patent Office: 2,630 Days
• Field of Search: 709220-227
• US Class Current: 709/223
• CPC Class Codes: G06F 8/24 Object-oriented
• CPC Class Codes: G06F 8/313 Logic programming, e.g. PROLOG programming language
• CPC Class Codes: G06N 5/00 Computing arrangements using knowledge-based models

Abstract

The Open Autonomy Kernel (OAK) addresses critical infrastructure requirements for next generation autonomous and semi-autonomous systems (24), including performance tracking, anomaly detection, diagnosis, fault recovery, and plant “safing”. OAK combines technologies in automated planning and scheduling, control agent-based systems (22), and model based reasoning to form a portable software architecture (26), knowledge-base, and open Application Programming Interface (API) to enable integrated auxiliary subsystem autonomy.

Claims

1. A system including a processor and a memory for controlling a connection-based system in which a plurality of independently executing control agents are distributed across an agent communication framework, each control agent being associated with a subsystem of the connection-based system wherein each control agent is responsive to other control agents such that connection-based system goals and connection-based system states can be propagated throughout the distributed network of control agents and acted upon to autonomously control the connection-based system, said system comprising:

in the subsystem, hardware components that are subject to component failures;

an agent communication framework that serves as a communication network for the plurality of control agents, wherein

each control agent is comprised of;

an agent communication broker that provides a communication interface between a control agent and the agent communication framework;

a model based reasoning engine (MBRE) communicable with the agent communication broker, the MBRE being based on failure sensitive component models of the hardware components that include

(i) physical properties based models on the hardware components, and

(ii) failure states of the hardware components,

wherein the MBRE estimates a component failure based subsystem state based on data gathered from the hardware components and knowledge of the past commands issued to said hardware components; and

a planner communicable with the agent communication broker and the model based reasoning engine that generates a reconfiguration plan for the implementation of a specific goal based on input including the specific goal and the subsystem state, and

wherein each control agent propagates commands for achieving the specific goal that are issued to associated hardware components.

2. The system of claim 1 wherein at least one control agent is communicable with an external actor that provides a system level goal to initiate connection-based system-wide control.

3. The system of claim 2 wherein a control agent is communicable with at least one hardware component within the control agent'"'"'s subsystem via a control mediator that provides an interface between the control agent and the hardware'"'"'s device controller.

4. The system of claim 3 wherein said control agent is further comprised of:

an executive manager communicable with the agent communication broker that routes incoming and outgoing messages for the control agent;

an ACL manager communicable with the executive manager for translating incoming messages into message objects, wherein message objects include a query object having data pertaining to subsystem status queries, a fact object having data pertaining to subsystem state updates, a goal object having data pertaining to the goal of a control agent, and a subscription object having data pertaining to another control agent that is interested in the status of the present control agent;

a model-based reasoning engine manager communicable with the executive manager, said model-based reasoning engine manager for storing the current state of a subsystem model; and

communicating query, fact, and goal objects between the model-based reasoning engine and executive manager;

a plan implementation manager communicable with the executive manager for implementing a plan generated by the planner;

a subscription manager communicable with the executive manager for maintaining a list of other control agents authorized to receive messages from the present control agent handling requests from other control agents and generating fact message objects pertaining to subsystem state changes to said other control agents.

5. The system of claim 4 wherein said control agent is further comprised of a reactive manager communicable with the executive manager for monitoring and comparing the current control agent'"'"'s state against a set of emergency states and a persistent goal to determine whether the current control agent'"'"'s model has entered an abnormal or hazardous state, wherein when the reactive manager determines that a control agent'"'"'s model has entered an abnormal or hazardous state, said reactive manager generates a new pre-emptive goal for the control agent to implement in order to prevent damage to the connection-based system.