A Graph-Based Conceptual Modeling Framework to Design for Human-Robot Coordination

This research presents a novel computational framework integrating functional modeling with graph-theoretic representations to analyze joint work strategies in human-robot systems. The framework characterizes collective work by relationships among system functions and the physical/informational structure of the environment, explicitly capturing how coordination demands evolve over time. A case study in disaster robotics demonstrates its use for early trade-space exploration of human-robot coordination strategies and identifying cooperative competencies to support flexible management of coordination overhead. Results show the framework makes coordination demands and their temporal evolution explicit, supporting design-time reasoning about cooperative competency requirements prior to implementation.