CHI Systems and the Institute for Human Machine Cognition have teamed to create a human-robot interaction system that leverages cognitive representations of shared context as a basis for a fundamentally new approach to human-robotic interaction. This approach centers on a framework for representing context, and for using context to enable robot adaptive decision-making and behavior. The framework is called CARIL (the Context-Augmented Robotic Interaction Layer). Context is an important part of human-human interaction. Unfortunately, context is often overlooked when designing robotic systems. The challenge is to translate high-level concepts, such as teamwork and collaboration, into specific requirements that can be implemented within control algorithms, interface elements, and behaviors. During Phase I, CHI Systems developed a proof-of-concept CARIL implementation and applied it to a notional simulated robot in a simple station model. This simulation demonstrated CARIL's feasibility by demonstrating how it gave the simulated robot a capability to reason about its context to avoid spatial interference with astronaut activities and tasks.