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In future long-duration exploration missions (LDEMs), communication with mission control will be significantly delayed. Crews will often need to react to time-sensitive issues or hazards without relying on mission control for assistance. The need for a higher degree of crew autonomy without direct oversight from mission control introduces the implementation of virtual assistants (VAs) to aid the crew; however, we must first create standards and guidelines for VAs in this context. For this purpose, we have developed a VA called Daphne-AT (Anomaly Treatment) to investigate the interaction between astronauts and virtual assistants in the context of anomaly resolution related to the Environmental Control and Life Support System (ECLSS). A series of experiments will be conducted in a laboratory environment and at the Human Exploration Research Analog (HERA) at NASA Johnson Space Center (JSC) to study user's performance, situational awareness, cognitive workload, and trust in Daphne-AT. Subjects in a simulated LDEM will be given several ECLSS anomalies to identify and solve with and without the support of Daphne-AT. We based the scenarios we developed on existing ECLSS hardware and pre-existing anomaly resolution procedures from the HERA environment. Solving an anomaly requires the subject to complete the correct anomaly resolution procedure(s) for the appropriate anomaly, which could include various tasks such as swapping out component parts and activating or deactivating ECLSS systems. In experiment sessions without Daphne-AT, subjects will rely on telemetry feeds as well as background knowledge and training to solve anomalies. However, during experiment sessions with Daphne-AT, the VA will also assist subjects in detecting and diagnosing these anomalies. We conducted an initial set of experiments at Texas A&M University (TAMU) prior to those at HERA. However, the subject must complete anomaly resolution procedures during an experiment that require access to hardware and components not available at the TAMU location. To emulate the HERA ECLSS hardware elements in our laboratory at TAMU, we recreated a virtual 3D representation of HERA and its ECLSS systems using the game engine Unreal Engine 4 (UE4). This virtual model will act as an analog for subjects who are tested on TAMU's campus to complete relevant ECLSS procedures. All subsystems featured in the UE4 model are interactive and allow the user to perform steps in an anomaly resolution procedure similar to how the user would do it in HERA. The UE4 model allows the user to complete more than 20 anomaly resolution procedures, thus increasing the TAMU experiment's fidelity compared to those conducted at HERA. This paper describes the development of the UE4 model and how we used it to validate the experimental protocol implemented at HERA. The results of these experiments will inform future guidelines for VAs deployed on LDEMs.

The Global Exploration Roadmap provides a pathway for humans to leave lower Earth orbit and develop a sustained presence in cislunar space as well as the lunar surface before embarking on a long journey to Mars. During these crewed Long Duration Exploration Missions (LDEM), communication delays will limit mission control availability to support the crew during critical in-flight anomalies. In order to address this challenge, future human spaceflight operations will benefit from intelligent Virtual Assistants (VAs) capable of assisting the crew in detecting, diagnosing, and resolving emergency anomalies. This intelligent technology could increase the probability of mission success and crew safety in emergency scenarios and could improve overall crew performance while operating in the hostile environment of deep space. Daphne-AT is a VA to support crewed LDEM in the context of diagnosing and resolving in-flight anomalies related to the Environmental Control and Life Support System (ECLSS) of a spacecraft. The overall research objective is to investigate the effect of Daphne-AT on human performance, cognitive workload, situational awareness, and trust in autonomous systems. Daphne-AT will be validated using controlled laboratory experiments, and further evaluation will occur during the Human Exploration Research Analog (HERA) C6 research campaign, consisting of four 45-day missions in 2020–21. In this paper, we provide an overview of our first version of Daphne-AT (i.e., baseline version), and discuss the design of anomaly scenarios using NASA's ECLSS simulator and the experimental set up for laboratory experiments. A preliminary within-subjects (i.e., with and without Daphne-AT) experiment was conducted with five human subjects, and preliminary results indicate that the use of Daphne-AT increases performance and decreases cognitive workload in the context of ECLSS anomaly scenarios. The data also show that subjects exhibited trust in using Daphne-AT, while it improved certain aspects of their situational awareness. Our work is part of the Human Capabilities Assessments for Autonomous Missions (HCAAM) Virtual NASA Science Center of Research (VNSCOR) within the NASA Human Research Program, and the ultimate goal is to generate standards and guidelines about how to design such VAs for future LDEMs.