Title :
A network science approach to future human-robot interaction
Author :
Schaefer, Kristin E. ; Cassenti, Daniel N.
Author_Institution :
Human Res. & Eng. Directorate, U.S. Army Res. Lab., Aberdeen Proving Ground, MD, USA
Abstract :
The vision for future Soldier-robot relationships has supported the transition of the robot´s role from a tool to an integrated team member. This vision has provided support for the advancement of robot autonomy and intelligence as a means to better support action and cognitive decision-making in the network-centric operational environment. To accomplish this goal, the Soldier´s perspective of the human-robot interaction must be further developed, as it directly impacts overall situation management: mission planning, operational roles, function allocation, and decision-making. Here we present a theoretical concept paper that promotes using the foundation of network science to better understand how and why advances in effective Soldier-robot situation management may be realized. We begin by providing a primer on how a network science approach may be used to understand multi-agent teams and network-centric operations. This is followed with a review on the impact of human perception on the human-robot team network structure. Two key points are highlighted. First, the network structure is influenced by the extent to which a Soldier-robot coupling performs independent operations. Second, the degree of automaticity for several properties of the robot specifies the strength of their networked relationship. We conclude with possible advantages of using a network science approach for understanding situation management of Soldier-robot teams in an operational environment. This approach provides a structure for creating visual maps of team structures to understand perceived and anticipated role interdependency, which thus provides the foundation for developing a mathematical description of the dynamic Soldier-robot relationship.
Keywords :
control engineering computing; human-robot interaction; military computing; multi-agent systems; cognitive decision-making; degree of automaticity; dynamic soldier-robot relationship; function allocation; human perception; human-robot interaction; human-robot team network structure; integrated team member; mission planning; multiagent teams; network science approach; network-centric operational environment; operational roles; robot autonomy; robot intelligence; Cognitive science; Read only memory; Resource management; Robot sensing systems; Social network services; Visualization; decision-making; human-robot interaction; network science; trust;
Conference_Titel :
Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2015 IEEE International Inter-Disciplinary Conference on
Conference_Location :
Orlando, FL
DOI :
10.1109/COGSIMA.2015.7108187