Intelligent self-situational awareness for increased autonomy, reduced operational risk, and improved capability

Karl M. Reichard, Jeff Banks, Eddie C. Crow, Lora Weiss

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Intelligent self-situational awareness refers to the ability of a system to autonomously assess its health and condition and to interpret the impact of its current and future health and condition on current mission objectives. Intelligent self-situational awareness represents a fusion of system health monitoring and intelligent autonomous control and is an extension of embedded diagnostics and prognostics, integrated system health management, and condition based maintenance that incorporates not only the ability to perceive current health and condition, but to assess the impact of the current health and condition within the context of the current mission requirements and resources. Department of Defense investment in system health management has been driven largely by a desire to reduce manning and control operational and sustainment costs associated with maintenance and logistics over the life cycle of systems. Studies conducted by the Applied Research Laboratory have shown payback times of 3-4 years for the investment in system health management for major platforms with significant cost savings and 4-5% improvements in operational availability.1 In order to implement integrated system health management in unmanned systems, the health monitoring capability must be integrated with the autonomous control system to avoid the bandwidth requirements and communication delays associated with sending health and performance-related sensor data back to a human operator. The capability of intelligent self-situational awareness can reduce the cognitive load on humans in manned and collaborative human-robotic missions, reduce the work load for ground support personnel, provides increased ability to respond to unanticipated faults and system degradation, and aid in mission planning and implementation. The benefits associated with the use of traditional embedded diagnostics and prognostics will still apply in space exploration missions: reduced loss of system availability due to unplanned system outages, reduced operational and sustainment costs, reduced logistics footprint and increased availability. Intelligent self-situational awareness helps meet all of these requirements, while also reducing the need for human interaction or response and is more conducive to integration with unmanned systems. This paper will investigate the cost and benefits of integrated system health management and autonomous control in autonomous and robotic exploration drawing on experiences in Department of Defense applications. An example is provided of integrated control and health management in a collaborative mission involving two unmanned underwater vehicles.

Original languageEnglish (US)
Title of host publicationA Collection of Technical Papers - 1st Space Ecploration Conference
Subtitle of host publicationContinuing the Voyage of Discovery
PublisherAmerican Institute of Aeronautics and Astronautics Inc.
Pages946-953
Number of pages8
ISBN (Print)1563477270, 9781563477270
DOIs
StatePublished - 2005
Event1st Space Exploration Conference: Continuing the Voyage of Discovery - Orlando, FL, United States
Duration: Jan 30 2005Feb 1 2005

Publication series

NameA Collection of Technical Papers - 1st Space Exploration Conference: Continuing the Voyage of Discovery
Volume2

Other

Other1st Space Exploration Conference: Continuing the Voyage of Discovery
CountryUnited States
CityOrlando, FL
Period1/30/052/1/05

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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