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To facilitate continuous development of novel HRI systems, it is beneficial to have tools that enable quick adjustments, flexibility, or re-invention of the human interfaces when system requirements change due to updates in the state-of-the-art, application domain, etc. Thus, modularity is a key design principle which promotes software reuse, scalability, and reduces development time and cost. Hence, a robot’s autonomous capabilities should not depend on the command interface and should be decoupled via a common format that possesses the descriptive capabilities for outlining tasks and has a sensible syntax for HRI. In this paper, we propose the Unified Meaning Representation Format (UMRF), which provides the syntax and semantics for passing both simple and complex commands modelled as control flow graphs. UMRF is a standalone meaning representation container that supports embedding other meaning representation formalisms, such as predicate-argument semantics and graphical meaning representation formats, making it adoptable as a standard task description format for semi-autonomous systems in HRI domains. In this article, we define the UMRF syntax and semantics, summarize its unique aspects relative to related task description formats, and demonstrate its descriptiveness by navigating a robot via concurrent (e.g., gestures and speech) and interchangeable input systems (e.g., Google Assistant, Amazon Alexa).

Unified Meaning Representation Format (UMRF) - A Task Description and Execution Formalism for HRI