Computational Methodology for the Allocation of Work and Interaction in Human-Robot Teams

Abstract

This paper presents a three-phase computational methodology for making informed design decisions when determining the allocation of work and the interaction modes for human-robot teams. The methodology highlights the necessity to consider constraints and dependencies in the work and the work environment as a basis for team design, particularly those dependencies that arise within the dynamics of the team’s collective activities. These constraints and dependencies form natural clusters in the team’s work, which drive the team’s performance and behavior. The proposed methodology employs network visualization and computational simulation of work models to identify dependencies resulting from the interplay of taskwork distributed between teammates, teamwork, and the work environment. Results from these analyses provide insight into not only team efficiency and performance, but also quantified measures of required teamwork, communication, and physical interaction. The paper describes each phase of the methodology in detail and demonstrates each phase with a case study examining the allocation of work in a human-robot team for space operations.