Task-based Guidance of Multiple UAV Using Cognitive Automation

This article discusses different dimensions of automation in the integration of multiple, detached, unmanned sensor platforms into a military helicopter scenario. Artificial cognitive units implement parts of human-like knowledge-rich task execution aboard a highly automated vehicle. Artificial cognition, being the method used, allows task execution beyond pre-scripted and predefined instruction sets, utilizing reasoning about the current situation to support goal-driven behaviour during task execution instead. The tasks assigned by the human operator are formulated at an abstraction level that might as well be used to task human subordinates within a mission. Like human subordinates, the UAV uses its cognitive capabilities to adapt task execution to the currently known situation including knowledge about the task assignments of

[1]  H. Eisenbeiss.  A MINI UNMANNED AERIAL VEHICLE (UAV): SYSTEM OVERVIEW AND IMAGE ACQUISITION , 2004 .

[2]  Robert P. Goldman,et al.  The Playbook (Trademark) Approach to Adaptive Automation , 2005 .

[3]  S. Hart,et al.  Development of NASA-TLX (Task Load Index): Results of Empirical and Theoretical Research , 1988 .

[4]  Axel Schulte,et al.  System-Ergonomic Design of Cognitive Automation: Dual-Mode Cognitive Design of Vehicle Guidance and Control Work Systems , 2010, Studies in Computational Intelligence.

[5]  Reiner Onken,et al.  COSA – A generic cognitive system architecture based on a cognitive model of human behavior , 2003, Cognition, Technology & Work.

[6]  Thomas B. Sheridan,et al.  Human and Computer Control of Undersea Teleoperators , 1978 .

[7]  Nadine B. Sarter,et al.  Learning from Automation Surprises and "Going Sour" Accidents: Progress on Human-Centered Automation , 1998 .

[8]  Allen Newell,et al.  SOAR: An Architecture for General Intelligence , 1987, Artif. Intell..

[9]  Jonathan P. How,et al.  Implementation of a Manned Vehicle - UAV Mission System , 2004 .

[10]  Mica R. Endsley,et al.  Situation awareness global assessment technique (SAGAT) , 1988, Proceedings of the IEEE 1988 National Aerospace and Electronics Conference.

[11]  A. Schulte,et al.  The MMP : A Mixed-Initiative Mission Planning System for the Multi-Aircraft Domain , 2011 .

[12]  I. Kaminer,et al.  Path Generation, Path Following and Coordinated Control for TimeCritical Missions of Multiple UAVs , 2006, 2006 American Control Conference.

[13]  Francis Y. Enomoto,et al.  UAV Autonomous Operations for Airborne Science Missions , 2004 .