Improving Situation Awareness in Distributed Human-Robot Teams

Abstract

The interaction between human and robots differs in many ways from human interactions andthese differences can contribute to poor teaming. Human teammates not only have teamworkskills (e.g., communication, back-up behaviors, conflict management), but they also are able tounderstand and relate to the actions of other teammates. They are able to recognize theintentions of team members, and to interact with them in a way that makes sense (i.e., is“explainable”). This basic ability to relate to human teammates may be especially importantwhen there is minimal ability to communicate (e.g., communicating underground, denied andcontested environments, limitations of natural language processing on the part of the robot).We propose a transdisciplinary effort drawing from cognitive science (team cognition), artificialintelligence (robotic planning), and human systems engineering to improve situation awarenessin such settings (see Figure 1). Deep knowledge integration across these disciplines will result inthe most innovative science and solution to the problem. The extant literature on team cognitioncoupled with studies of human teams will inform robotic algorithms. A human systemsengineering approach will evaluate the resulting robotic algorithms in terms of ability to teamsuccessfully with humans and preserve team situation awareness. Option years will be dedicatedto extending this work over time (i.e., longer term human-robot teaming) and to the RemotelyPiloted Aircraft System context.

Document Details

Document Type
DoD Grant Award
Publication Date
Apr 09, 2018
Source ID
FA95501810067

Entities

People

  • Nancy J Cooke

Organizations

  • Air Force Office of Scientific Research
  • Arizona State University
  • United States Air Force

Tags

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Data Mining and Knowledge Discovery.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - DoD AI Strategy
  • Autonomy
  • Autonomy - Autonomous System Control
  • Autonomy - Human-Robot Interaction