Adaptive Automation for Human-Robot Teaming in Future Command and Control Systems

Abstract

Advanced command and control (C2) systems such as the U.S. Army's Future Combat Systems (FCS) will increasingly use more flexible, reconfigurable components, including numerous robotic (unmanned) air and ground vehicles. Human operators will be involved in supervisory control of unmanned vehicles (UVs) with the need for occasional manual intervention. This paper discusses the design of automation support in C2 systems with multiple UVs. Following a model of effective human-automation interaction design, the authors propose that operators can best be supported by high-level automation of information acquisition and analysis functions. Automation of decision-making functions, on the other hand, should be set at a moderate level, unless 100 percent reliability can be assured. The use of adaptive automation support technologies also is discussed. They present a framework for adaptive and adaptable processes as methods that can enhance human-system performance while avoiding some of the common pitfalls of "static" automation such as over-reliance, skill degradation, and reduced situational awareness. Adaptive automation invocation processes are based on critical mission events, operator modeling, and real-time operator performance and physiological assessment, or hybrid combinations of these methods. They describe the results of human-in-the-loop experiments involving human operator supervision of multiple UVs under multi-task conditions in simulations of reconnaissance missions. The results support the use of adaptive automation to enhance human-system performance in supervision of multiple UVs, balance operator workload, and enhance situational awareness. Implications for the design and fielding of adaptive automation architectures for C2 systems involving UVs are discussed.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2007
Accession Number
ADA503770

Entities

People

  • Keryl Cosenzo
  • Michael Barnes
  • Raja Parasuraman
  • Sandeep Mulgund

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Adaptive Systems
  • Automated Target Recognition
  • Automation
  • Cognitive Systems Engineering
  • Cognitive Workload
  • Command And Control
  • Control Systems
  • Human Factors Engineering
  • Human-Robot Interaction
  • Information Processing
  • Psychology
  • Reliability
  • Robots
  • Situational Awareness
  • Target Recognition
  • Unmanned Ground Vehicles
  • Unmanned Vehicles

Readers

  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Human-Robot Interaction
  • Fully Networked C3
  • Fully Networked C3 - Command and Control