Today, as humans reach beyond the earth to near and deep space, there is obvious and urgent need to augment the capabilities of human astronauts and (ground-) controllers with smarter and more capable automation. In conventional approaches to human-robot interactions for supervisory control paradigms, coordination often breaks down for a variety of reasons and progress toward interactive goals is often impeded due to the inability of the work system to adapt to context shifts. Hence, human-robot teams can be almost entirely non-adaptive. To address these complex problems, CHI Systems and the Institute for Human Machine Cognition have teamed to create a human-robot interaction system based on recent theories and tools developed by CHI Systems leveraging cognitive representations of shared context as basis for a fundamentally new approach to human-robotic interaction. This approach includes a framework for representing context and using it to support decision making and control of automation and will form the core of the proposed solution termed the Context-Augmented Robotic Interaction Layer or CARIL. CARIL will enable efficient and effective human-robot control-oriented cooperation through the use of adaptive behaviors to mediate cooperation between humans and robots. Phase I will focus on development and demonstration of the CARIL concept.