Integrating self-health awareness in autonomous systems

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Abstract

One enabler for unmanned, autonomous system operation is mission awareness. Mission awareness is composed of three components: knowledge of mission objectives, internal self-situational awareness, and external self-situational awareness. Internal self-situational awareness implies knowledge of platform health and capability. External self-situational awareness encompasses knowledge of external resources (supplies, supervisors, or collaborators) as well as threats that can affect system performance. Finally, the system must be able to translate mission objectives into actions and assess the impact of its internal and external state on its ability to execute the mission. If the combination of the internal and external state will not permit the system to achieve its mission objectives, the autonomous control system for the platform must revise the mission plan or otherwise alter the mission execution strategy to remain within current system operational limits. A key aspect of the design and implementation of the health monitoring system and the autonomous control system is knowledge representation. The health monitoring system and the control system should have a common representation of the system capabilities and behaviors as well as the interactions between critical subsystems. Another key aspect is the representation of system health in a manner that can be used by the control system to compensate for subsystem degradation. This paper describes a generic architecture for the implementation of health monitoring within a complex system, the representation of system health information, and an approach for integrating health information with autonomous control. A behavior based, autonomous intelligent control system architecture developed for autonomous underwater vehicles is used to demonstrate the integration.

Original languageEnglish (US)
Pages (from-to)105-112
Number of pages8
JournalRobotics and Autonomous Systems
Volume49
Issue number1-2 SPEC. ISS.
DOIs
StatePublished - Nov 30 2004

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mathematics(all)
  • Computer Science Applications

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