Operator Workload and Heart-Rate Variability During a Simulated Reconnaisance Mission with an Unmanned Ground Vehicle

Abstract

In this study, we simulated a generic mounted crew station environment and conducted an experiment to examine the workload and performance of the operator of a ground robot. Participants were randomly assigned to four tasking conditions: robotics tasks only, robotics plus an auditory task, robotics plus a visual monitoring task, or all three tasks simultaneously. Participants completed four mission scenarios. In two of these scenarios, their robot was semiautonomous. In the other two scenarios, they had to teleoperate the robot. An Aided Target Recognition (AiTR) system was available to help them with their target detection tasks in only two of the four scenarios. Results showed that operators' situational awareness and perceived workload were significantly worse when they teleoperated the robot. Individual differences factors such as the operator's spatial ability and attentional control were also investigated. Implications for military personnel selection were discussed.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2008
Accession Number
ADA504292

Entities

People

  • Denise Nicholson
  • Jessie Y. Chen
  • Julie M. Drexler
  • Keryl A. Cosenzo
  • Lee W. Sciarini
  • Michael J. Barnes

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Applied Psychology
  • Cognitive Workload
  • Command And Control
  • Detection
  • Human Factors Engineering
  • Human Systems Integration
  • Human-Robot Interaction
  • Psychology
  • Recognition
  • Robotics
  • Robots
  • Situational Awareness
  • Target Detection
  • Target Recognition
  • Unmanned Ground Vehicles
  • Unmanned Systems
  • Unmanned Vehicles

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Sensor Fusion and Tracking Systems.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • Autonomy
  • Autonomy - Human-Robot Interaction