Seamless human robot interaction (HRI) and cooperative human-robot (HR) teaming critically rely upon accurate and timely human mental workload (MW) models. Cognitive Load Theory (CLT) suggests representative physical environments produce representative mental processes; physical environment fidelity corresponds with improved modeling accuracy. Virtual Reality (VR) systems provide immersive environments capable of replicating complicated scenarios, particularly those associated with high-risk, high-stress scenarios. Passive biosignal modeling shows promise as a noninvasive method of MW modeling. However, VR systems rarely include multimodal psychophysiological feedback or capitalize on biosignal data for online MW modeling. Here, we develop a novel VR simulation pipeline, inspired by the NASA Multi-Attribute Task Battery II (MATB-II) task architecture, capable of synchronous collection of objective performance, subjective performance, and passive human biosignals in a simulated hazardous exploration environment. Our system design extracts and publishes biofeatures through the Robot Operating System (ROS), facilitating real time psychophysiology-based MW model integration into complete end-to-end systems. A VR simulation pipeline capable of evaluating MWs online could be foundational for advancing HR systems and VR experiences by enabling these systems to adaptively alter their behaviors in response to operator MW.
翻译:无缝的人类机器人互动(HRI)和人类-机器人合作(HR)团队关系严重依赖准确和及时的人类心理工作量模型。认知式载荷理论(CLT)建议有代表性的物理环境产生有代表性的心理过程;物理环境忠诚与改进的模型准确性相匹配。虚拟现实(VR)系统提供了可以复制复杂情景的隐性环境,特别是那些与高风险、高压力情景有关的情景。被动生物信号模型显示作为MW建模的非侵入性方法的前景。然而,VR系统很少包括多式心理生理反馈或利用生物信号数据进行在线MW建模。在这里,我们开发了一个新型VR模拟管道,受美国航天局多属性任务二号(MATB-II)任务架构的启发,能够在模拟危险勘探环境中同步收集客观性业绩、主观性能和被动性人类生物信号。我们系统的设计摘录和通过机器人操作系统公布生物功能。在基于MW的在线运行过程中促进实时心理物理学反馈反馈或利用生物信号数据进行生物信号数据模拟模拟模拟。通过机器人操作系统对基于MW的模型的模型进行实时模拟整合,可以将这些模型的MWMW的模型整合系统进行完整的升级,从而将这些模型系统进行升级到最终评估。