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.

A Review of NASA Human-Robot Interaction in Space

“…For example, NASA needs to better understand collocated human-robot teams, how humans and robots can safely interact, not just preventing physical collisions but also potentially negative social psychological effects on crew members. NASA also still needs to develop methods to assess team cohesiveness and effectiveness during space missions based on human-robot team composition and task allocations [17]. Additionally, successful robotic integration into spaceflight is compounded by the lack of formal standards (de facto or otherwise) for HRI [19].…”

Modeling the Effects of Machine Rigidities on Joint Work Strategies

“…The maintenance involves inspection of a panel and subsequent replacement of that panel if the inspection deems it necessary. This work builds on and integrates with prior work on computational modeling of work in human-machine teams (IJtsma, Ma, Pritchett, & Feigh, 2019). For a detailed overview of the case study and the work model, see IJtsma, 2019.…”

Requirements for Computational Approaches to Analyzing Resilience in Human-Machine Teams

“…We also hope that future developments will build on what is already available in existing computational modeling frameworks, for example those described in the fourth section of this paper. For example, our own work uses the modeling and simulation framework Work Models that Compute (WMC), which has been successfully employed in investigating the dynamics of air traffic control and manned space operations (Feigh et al, 2001;IJtsma, 2019;Rosso & Saurin, 2018). By expanding its existing simulation capabilities and developing new capabilities to capture resilience engineering principles, we can begin to identify the architectural characteristics and governance protocols that lead to resilient behavior, informing the development of actionable design inputs and methodology (Feigh et al, 2001;IJtsma, 2019;Rosso & Saurin, 2018).…”