Currently, multiple humans are needed to operate a single uninhabited aerial vehicle (UAV). In the near future, combat techniques will involve single operators controlling multiple uninhabited ground and air vehicles. This situation creates both technological hurdles as well as interaction design challenges that must be addressed to support future fighters. In particular, the system will need to negotiate with the operator about proper task delegation, keeping the operator appropriately apprised of autonomous actions. This in turn implies that the system must know what the user is doing, what needs to be done in the present situation, and the comparative strengths for of the human and the system in each task. Towards building such systems, we are working on an Intelligent Control Framework (ICF) that provides a layer of intelligence to support future warfighters in complex task environments. The present paper presents the Adjustable Autonomy Module (AAM) in ICF. The AAM encapsulates some capabilities for user plan recognition, situation reasoning, and authority delegation control. The AAM has the knowledge necessary to support operator-system dialogue about autonomy changes, and it also provides the system with the ability to act on this knowledge. Combined with careful interaction design, planning and plan-execution capabilities, the AAM enables future design and development of effective human-robot teams.
KEYWORDS: Data modeling, Cognitive modeling, Data fusion, Visualization, Sensors, Analytical research, Intelligence systems, Missiles, Systems modeling, Geographic information systems
In order to wage successful campaigns, the next generation of intelligence analysts and battle commanders will need to assimilate an enormous amount of information that will come from a wide range of heterogeneous data sources. Complicating this problem further is the fact that warfighters need to be able to manage information in an environment of rapidly changing events and priorities. The consequence of not addressing this problem, or not addressing it as effectively as hostile forces do, is a potential loss of assets, personnel, or tactical advantage.
To design effective information displays there needs to be an extensible framework that models the warfighters context including characteristics of the information sources being displayed, the current Intelligence Surveillance Reconnaissance (ISR) picture or Common Operating Picture (COP), the warfighters current state and task, and the state of the information display. BINAH (Battlespace Information and Notification through Adaptive Heuristics) uses an agent-based modeling approach coupled with research into temporal and spatial reasoning, novel display management techniques, and development of a formal high-level language for describing model-based information configuration.
The result is an information configuration pipeline designed to provide perceptual and cognitive analysis support to Air Force analysts engaged in Time-Critical Targeting target nomination. It has been integrated with the Air Force Research Laboratory's (AFRL) XML-based Joint Battlespace Infosphere (JBI) combat information management system and combines JBI delivered sensor data with a local user model and display strategies to configure a geospatial information display. The BINAH framework will provide a firm grounding for developing new C4ISR displays that maximize the ability of warfighters to assimilate the information presented.
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