Computational design of mixed-initiative human–robot teaming that considers human factors: situational awareness, workload, and workflow preferences

Abstract

Advancements in robotic technology are making it increasingly possible to integrate robots into the human workspace in order to improve productivity and decrease worker strain resulting from the performance of repetitive, arduous physical tasks. While new computational methods have significantly enhanced the ability of people and robots to work flexibly together, there has been little study of the ways in which human factors influence the design of these computational techniques. In particular, collaboration with robots presents unique challenges related to the preservation of human situational awareness and the optimization of workload allocation for human teammates while respecting their workflow preferences. We conducted a series of human subject experiments to investigate these human factors, and provide design guidelines for the development of intelligent collaborative robots based on our results.