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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.