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Embedded command and control infrastructures for Intelligent Autonomous Systems

Embedded command and control infrastructures for Intelligent Autonomous Systems
Embedded command and control infrastructures for Intelligent Autonomous Systems
The issue of Command and Control (C2) is generally associated with the management infrastructure of large scale systems for warfare, public utilities and public transportation, and is concerned with ensuring that the distributed human elements of command and control can be fully integrated into a coherent, total system. Intelligent Autonomous Systems (IASs) are a class of complex systems that perform tasks autonomously in uncertain, dynamic environments, the management of which can be viewed from the perspective of embedded command and control systems. This thesis establishes a vision for the modular construction of intelligent autonomous embedded C2 systems, which defines a complex integration problem characterised by distributed intelligence, world knowledge and control, concurrent processing on heterogeneous platforms, and real-time performance requirements. It concludes that by adopting an appropriate systems infrastructure model, based on Object Technology, it is possible to view the construction of embedded C2 systems as the integration of a temporally assembled collection of reusable components. To support this metaphor it is necessary to construct a common reference model, or standards framework, for the representation and specification of modular C2 systems. This framework must support the coherent long term development and evolution in system capability, ensuring that systems are extensible, robust and perform correctly. In this research, which draws together the themes of other published research in object oriented systems and robotics, classical AI models for intelligent systems architectures are used to specify the overall system structure, with open systems technologies supporting the interoperation of elements within the architecture. All elements of this system are modelled in terms of objects, with well defined, implementation independent interfaces. This approach enables the system to be specified in terms of an object model, and the development process to be framed in terms of object technology, defining a new approach to IAS development. The implementation of an On-board Command and Control System for an Autonomous Underwater Vehicle is used to validate these concepts. The further application of emergent industrial standards in distributed object oriented systems means that this kind of component-based integration is scaleable, providing a near-term solution to generic command and control problems, including Computer Integrated Manufacturing and large scale autonomous systems, where individual autonomous systems, such as robots, form elements of a complete, total intelligent system, for application to areas such as fully automated factories and cooperating intelligent autonomous vehicles for construction sites.
University of Southampton
Fraser, R.J.C.
eb2c6781-5c5e-40ce-a720-cb448ee3071b
Fraser, R.J.C.
eb2c6781-5c5e-40ce-a720-cb448ee3071b
Harris, C.
c4fd3763-7b3f-4db1-9ca3-5501080f797a

Fraser, R.J.C. (1994) Embedded command and control infrastructures for Intelligent Autonomous Systems. University of Southampton, : University of Southampton, Doctoral Thesis.

Record type: Thesis (Doctoral)

Abstract

The issue of Command and Control (C2) is generally associated with the management infrastructure of large scale systems for warfare, public utilities and public transportation, and is concerned with ensuring that the distributed human elements of command and control can be fully integrated into a coherent, total system. Intelligent Autonomous Systems (IASs) are a class of complex systems that perform tasks autonomously in uncertain, dynamic environments, the management of which can be viewed from the perspective of embedded command and control systems. This thesis establishes a vision for the modular construction of intelligent autonomous embedded C2 systems, which defines a complex integration problem characterised by distributed intelligence, world knowledge and control, concurrent processing on heterogeneous platforms, and real-time performance requirements. It concludes that by adopting an appropriate systems infrastructure model, based on Object Technology, it is possible to view the construction of embedded C2 systems as the integration of a temporally assembled collection of reusable components. To support this metaphor it is necessary to construct a common reference model, or standards framework, for the representation and specification of modular C2 systems. This framework must support the coherent long term development and evolution in system capability, ensuring that systems are extensible, robust and perform correctly. In this research, which draws together the themes of other published research in object oriented systems and robotics, classical AI models for intelligent systems architectures are used to specify the overall system structure, with open systems technologies supporting the interoperation of elements within the architecture. All elements of this system are modelled in terms of objects, with well defined, implementation independent interfaces. This approach enables the system to be specified in terms of an object model, and the development process to be framed in terms of object technology, defining a new approach to IAS development. The implementation of an On-board Command and Control System for an Autonomous Underwater Vehicle is used to validate these concepts. The further application of emergent industrial standards in distributed object oriented systems means that this kind of component-based integration is scaleable, providing a near-term solution to generic command and control problems, including Computer Integrated Manufacturing and large scale autonomous systems, where individual autonomous systems, such as robots, form elements of a complete, total intelligent system, for application to areas such as fully automated factories and cooperating intelligent autonomous vehicles for construction sites.

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More information

Published date: 1994
Additional Information: Address: Faculty of Engineering and Applied Science
Organisations: University of Southampton, Southampton Wireless Group

Identifiers

Local EPrints ID: 250158
URI: http://eprints.soton.ac.uk/id/eprint/250158
PURE UUID: c2aa1189-d5fa-4181-afb4-061a7b94a28e

Catalogue record

Date deposited: 04 May 1999
Last modified: 10 Dec 2021 20:07

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Contributors

Author: R.J.C. Fraser
Thesis advisor: C. Harris

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