Furthering human-robot teaming, interaction, and metrics through computational methods and analysis

Human-robot teaming is a complex design trade space with dynamic aspects and particulars. In order to support future day human-robot teams and scenarios, we need to assist team designers and evaluators in understanding core teaming components. This work is centered around teams that complete space missions and operations. The central scope and theme of this work target the way users should design, evaluate, and think about human-robot teams. This work attempts to do so by defining a framework, conceptual methodology, and operationalized metrics for human-robot teams. We begin by scoping and distilling common components from human-only teaming and human-robot teaming research based in areas such as human factors, cognitive psychology, robotics, and human-robot interaction. Taking these constructs, we derive a framework that describes and organizes the factors, as well as relationships between them. This work also presents a theoretical methodology to support designers to understand the impact teaming components have on expected interaction. This methodology is implemented for four case studies of distinct team types and scenarios including moving furniture, a SWAT team operation, a rover recon, and an in-orbit maintenance mission. After assessing various existing methodologies and perspectives, we derive metrics operationalized from work allocation. To test these learnings, this work modeled and simulated human-robot teams in action, specifically in an in-orbit maintenance scenario. In addition to analyzing simulation results given different team configurations, task allocations, and teamwork modes, a HITL experiment confirmed a human perspective of robotic team members. This experiment also refines the modeling of teams and validates our performance metrics. This dissertation makes the following contributions to the field of human-robot teaming and interaction: 1) Created a new comprehensive framework for human-robot teaming by combining key components of team design and interaction, 2) Developed a method to identify distinct archetypes of interaction in human-robot teams (and showed how they fit into a universal framework), 3) Derived metrics from the HRT framework to capture the teaming elements beyond performance and efficiency; operationalized the method and metrics in a computational framework for simulation and analysis, 4) Extended existing computational framework for function allocation to include the metrics, 5) Demonstrated the sensitivity of effective teams to attributes of both teamwork and taskwork.Ph.D