Information Fusion for Command and Control (IFC2):
The Translation of Raw Data To Actionable Knowledge and Decision
 


Introduction

To respond to an ever-changing, uncertain environment, human commanders must maintain a general awareness of the battlespace, and yet focus on relevant contextual information when making decisions, without distraction from peripheral events. Decision cycles have shortened, available information has expanded, and missions have become increasingly variegated. The repertoire of traditional battle functions has expanded to include new types of operations, such as ad hoc responses to terrorism, response to biochemical threats, and operations other than those of war and coalition operations. To meet these new challenges, the commander needs enhanced decision support. Yet providing this automation becomes increasingly difficult as uncertainty increases.

Furthermore, while the volume of raw information available for command decisions at all echelons is rapidly increasing, its coordination and dissemination as useful information becomes far more difficult, leading to the problem of "data overload and information starvation." Data is often fragmented, multi-modal, uncertain, and distributed across disparate sources.

The next generation of battlefield information systems must meet the twin challenges of scaling up to accommodate the explosion of cheap ubiquitous sensors, while extending access to increasingly heterogeneous information sources, from the Air Force's own legacy systems to those of other cooperating services and nations. These new sources of information must not only be accessed; they must be converted from mere data into sources of usable, actionable knowledge.

To address these issues in high-level information fusion, we are conducting a multidisciplinary research effort involving computer scientists, engineers and cognitive psychologists, from Carnegie Mellon University, the University of Pittsburgh, the Munitions Directorate of Air Force Research Laboratory (MN/AFRL), Rome Labs, and Northrup Grumman. We will combine our various expertise to develop the next generation of information fusion systems.

The problems that must be addressed in order to build these systems are:

  • Integration of heterogeneous information sources both internal and external to the Air Force (e.g. intelligence reports)
  • Adaptation/Customization to rapidly changing threats and missions.
  • Automation of information selection and dissemination to provide the right information to the right decision maker at the right time, while also keeping pace with the shrinking decision cycle.
  • Scalability to accommodate ubiquitous sensing and other expanding information sources.

To meet these challenges a next generation information system must:

  • Be Modular and flexible enough to configure itself without explicit guidance, so that it can be deployed and used immediately.
  • Be Open enough to accommodate dynamically changing and heterogeneous information sources, legacy systems, and various levels of fused information.
  • Support automation to direct attention; and filter, and distribute information to warfighters at all levels.
  • Support technology for quality of information pedigrees.
  • Support information fusion across levels, maintaining coherent pictures from varied perspectives and levels of aggregation.

For future information processing and planning systems, an in-depth understanding of the cognitive processes of the user being aided must be understood, coupled with innovative approaches for real-time information fusion at all levels, including multimedia and multi-modal information from disparate and distributed sources that include enormous amounts of uncertainty and noise. Such cognitively congruent systems will provide an intuitively understandable common operational picture for enhanced situation assessment and battle management, along with planning guidance and monitoring functions in the uncertain and quickly evolving battlespace. Our overall research hypothesis is that the way to address the issues in information fusion at different levels is through adaptive and self-organizing collections of Intelligent Agents who also possess models for discriminating and communicating situational distinctions salient to humans and the current mission.

Our multidisciplinary and multi-institutional research project research will help translate information superiority into decision superiority, i.e., to make information into knowledge, in order to rapidly arrive at better decisions than adversaries can respond to.

IFC2 Demo Presentaton (.ppt)

Robotics Institute Project Page







Principal Investigator: Katia Sycara
(Air Force Office of Scientific Research Grant F49620-01-1-0542)

© 2003 Carnegie Mellon Robotics Institute