Framework for Multi-Human Multi-Robot Interaction: Impact of Operational Context and Team Configuration on Interaction Task Demands

摘要

Increasing prevalence and complexity of robotic and autonomous systems (RAS) and promising applications of hybrid multi-human multi-RAS teams across a wide range of domains pose a challenge to user interface designers, autonomy researchers, system developers, program managers, and manning/personnel analysts. These stakeholders need a principled, generalizable approach to analyze these teams in an operational context to design effective team configurations and human-system interfaces. To meet this need, we have developed a theoretical framework and software simulation that supports analysis to understand and predict the type and number of human-RAS and human-human interaction task demands imposed by the mission and operational context. We extend previous research to include multihuman multi-RAS teams, and emphasize generalizability across a wide range of current and future RAS technologies and military and commercial applications. To ensure that our framework is grounded in mission and operational realities, we validated the framework structure with domain experts. The framework characterizes Operational Context, Team Configuration, and Interaction Task Demands, and defines relationships between these constructs. These relationships are complex, and prediction of Interaction Task Demands quickly becomes difficult even for small teams. Therefore, to support analysis, we developed a software simulation (Beer, Rieth, Tran, & Cook, 2016) that predicts these demands and allows testing and validation of the framework. The framework and simulation presented here provide a step forward in the development of a systematic, well-defined, principled process to analyze the design tradeoffs and requirements for a wide range of future hybrid multi-human multi-RAS teams.