Normative Coordination for Embodied AI: A Noumostásian Framework

Current embodied AI systems excel at task execution but lack protocols for normative coordination: detecting whether a human has accepted, modified, or rejected an interaction, not merely whether a task is completed. This gap produces friction, distrust, and inefficient re-engagement. We introduce Noumostásia, a framework for embodied accountability that specifies (1) the Ratification Loop—a state machine for detecting multi-modal uptake signals; (2) tactile-to-deontic translation (NTDTT), mapping sensor data to normative meaning; and (3) Sol Maintenance, a protocol for preserving the phatic ground between actions. We demonstrate the framework's applicability to humanoid robots, teleoperated systems, and collaborative agents. A reference implementation is available upon reqquest. This work establishes normative coordination as a foundational layer for trustworthy human-robot interaction.