Visible to the public Modelling and evaluating failures in human-robot teaming using simulation

TitleModelling and evaluating failures in human-robot teaming using simulation
Publication TypeConference Paper
Year of Publication2018
AuthorsMa, L. M., IJtsma, M., Feigh, K. M., Paladugu, A., Pritchett, A. R.
Conference Name2018 IEEE Aerospace Conference
Date PublishedMarch 2018
PublisherIEEE
ISBN Number978-1-5386-2014-4
Keywordsaerospace robotics, Computational modeling, computational simulation, Extraterrestrial measurements, failure evaluation, Fault tolerance, human-robot interaction, human-robot teaming, human-robot teams, multi-robot systems, pubcrawl, resilience, Resiliency, Resource management, robot failures, robotic capabilities, robots, Scalability, space EVA operations, Task Analysis, team designers, team performance, team working, Teamwork, work factor metrics, Work Models that Compute
Abstract

As robotic capabilities improve and robots become more capable as team members, a better understanding of effective human-robot teaming is needed. In this paper, we investigate failures by robots in various team configurations in space EVA operations. This paper describes the methodology of extending and the application of Work Models that Compute (WMC), a computational simulation framework, to model robot failures, interruptions, and the resolutions they require. Using these models, we investigate how different team configurations respond to a robot's failure to correctly complete the task and overall mission. We also identify key factors that impact the teamwork metrics for team designers to keep in mind while assembling teams and assigning taskwork to the agents. We highlight different metrics that these failures impact on team performance through varying components of teaming and interaction that occur. Finally, we discuss the future implications of this work and the future work to be done to investigate function allocation in human-robot teams.

URLhttps://ieeexplore.ieee.org/document/8396581
DOI10.1109/AERO.2018.8396581
Citation Keyma_modelling_2018