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Urban Search and Rescue (USAR) missions continue to benefit from the incorporation of human–robot teams (HRTs). USAR environments can be ambiguous, hazardous, and unstable. The integration of robot teammates into USAR missions has enabled human teammates to access areas of uncertainty, including hazardous locations. For HRTs to be effective, it is pertinent to understand the factors that influence team effectiveness, such as having shared goals, mutual understanding, and efficient communication. The purpose of our research is to determine how to (1) better establish human trust, (2) identify useful levels of robot transparency and robot explanations, (3) ensure situation awareness, and (4) encourage a bipartisan role amongst teammates. By implementing robot transparency and robot explanations, we found that the driving factors for effective HRTs rely on robot explanations that are context-driven and are readily available to the human teammate. 

Virtual testbeds are fundamental to the success of research on cognitive work in safety-critical domains. A testbed that can meet researchers' objectives and create a sense of reality for participants positively impacts the research process; they have the potential to allow researchers to address questions not achievable in physical environments. This paper discusses the development of a synthetic task environment (STE) for Urban Search and Rescue (USAR) to advance the boundaries of Human-Robot Teams (HRTs) using Roblox. Virtual testbeds can simulate USAR task environments and HRT interactions. After assessing alternative STE platforms, we discovered Roblox not only met our research capabilities but also would prove invaluable for research teams without substantial coding experience. This paper outlines the design process of creating an STE to meet our research team's objectives. 

The goal of the Space Challenge project is to identify the challenges faced by teams in space operations and then represent those challenges in a distributed human-machine teaming scenario that resembles typical space operations and to measure the coordination dynamics across the entire system. Currently, several challenges have been identified through semi-structured interviews with nine subject matter experts (SMEs) who were astronauts or those who have experienced or have been involved with interplanetary space exploration. We conducted a thematic analysis on the interviews through an iterative process. Challenges were categorized into four categories, including, communication, training, distributed teaming, and complexity. Based on the findings, challenges and key teamwork characteristics of space operations were integrated into the initial scenario development. In addition to the scenario, we plan to use dynamical system methods to analyze team activity in real time. 

Urban Search and Rescue (USAR) missions often involve a need to complete tasks in hazardous environments. In such situations, human-robot teams (HRT) may be essential tools for future USAR missions. Transparency and explanation are two information exchange processes where transparency is real-time information exchange and explanation is not. For effective HRTs, certain levels of transparency and explanation must be met, but how can these modes of team communication be operationalized? During the COVID-19 pandemic, our approach to answering this question involved an iterative design process that factored in our research objectives as inputs and pilot studies with remote participants. Our final research testbed design resulted in converting an in-person task environment to a completely remote study and task environment. Changes to the study environment included: utilizing user-friendly video conferencing tools such as Zoom and a custom-built application for research administration tasks and improved modes of HRT communication that helped us avoid confounding our performance measures.