Proceedings:
Knowledge Representation and Ontologies for Autonomous Systems
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Papers from the 2004 AAAI Spring Symposium
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Abstract:
One enabler for unmanned, autonomous system operation is mission awareness. Three components comprise mission awareness: knowledge of mission objectives, internal self-situational awareness, and external self-situational awareness. Mission objectives include both high level mission goals and any details operational requirements. Internal self-situational awareness entails 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 adversely affect system performance. An unmanned autonomous 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 actions necessary to accomplish the mission objectives. If the combination of the internal and external state will not permit the system to achieve its mission objectives, the autonomous control system must revise the mission plan and possibly notify supervisors and collaborators (human or machine). This paper describes an approach to the integration of information an autonomous health monitoring system with a vehicle’s autonomous controller. A behavior based, autonomous intelligent control system architecture developed for autonomous underwater vehicles is used to integrate both internal-self situational awareness, and autonomous control. The scalability of the architecture simplifies the addition of a hierarchical supervisor that can communicate with other collaborators to revise mission plans in the event of changes in the internal or external situation.
Spring
Papers from the 2004 AAAI Spring Symposium