Robotic Command and Control Intelligent Enablers

Battle command of mixed human and robotic units is an inherently complex problem. Even within a SoSCOE architecture, implementing such a capability such that it improves commander and combat effectiveness is beyond current state of the art. Such an implementation will require integration, cooperation, and shared awareness among multiple agents, algorithms, other services, and humans. Developing intelligent, highly capable technologies to support efficient and effective human-robot and other human-automation interaction will require the integration of not just data, but of knowledge, semantics, processing, and problem-solving paradigms. Our research will develop a capability to integrate multiple agent and algorithmic techniques in the service of a tactical commander’s operational requirements. This capability includes an ability to define and refine battle plans, constraints, information requirements, objectives, and success criteria in a form that is both natural to the commander and computationally executable. We will build on prior and current Army-sponsored work developing cooperative multi-agent systems and will utilize current and emerging standards. We will integrate heuristic, numeric, and constraint-satisfaction approaches to problem solving using a well-defined battle-plan format and protocol. We will demonstrate this capability using an OTB-based simulated environment within an urban that will require air-ground cooperation, ground-ground cooperation, and human-robotic cooperation.