Human-Agent Teaming For Effective Multirobot Management: Effects Of Agent Transparency

Keywords

Human factors; Intelligent agents; Patterns of human-agent interaction; Supervisory control; Transparency

Abstract

The U.S. Army Research Laboratory is engaged in a multi-year program focusing on the human role in supervising autonomous vehicles. We discuss this research with regard to patterns of human/intelligent agent (IA) interrelationships, and explore the dynamics of these patterns in terms of supervising multiple autonomous vehicles. The first design pattern focuses on a human operator controlling multiple autonomous vehicles via a single IA. The second design pattern involves multiple intelligent systems including (a) human operator, (b) IA-asset manager, (c) IA-planning manager, (d) IA-mission monitor, and (e) multiple autonomous vehicles. Both scenarios require a single operator to control multiple heterogeneous autonomous vehicles, and yet the complexity of both the mission variables and the relations among the autonomous vehicles makes efficient operations by a single operator difficult at best. Key findings of two recent research programs are summarized with an emphasis on their implications for developing future systems with similar design patterns. Our conclusions stress the importance of operator situation awareness, not only of the immediate environment, but also of the IA’s intent, reasoning and predicted outcomes.

Publication Date

1-1-2016

Publication Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

9736

Number of Pages

169-178

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-319-40030-3_18

Socpus ID

84978306121 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84978306121

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