Event-Driven Notation and Hierarchical Automata Semantics for Incremental Task Modeling

Task modeling and specification for autonomous agents (e.g. robots) normally start with exploring typical scenarios and situational variations. Numerous behavioral procedures of an agent are thus collected. Those procedures are partially different from one another, varying in fragmentation or in abstraction levels. To describe task procedures having this characteristic, we propose an Event-driven Task Script (ETS) notation and a formal semantic framework for modeling agent's tasks directly from a set of redundant and partially described scripts. Sequential and parallel behavior control and an event handling mechanism are supported by ETS. The semantics of ETS notation is defined by the corresponding Hierarchical Automata (HA), which is concise and widely used in the area of discrete event systems. The semantic mapping from ETS notation to the semantic domain of HA is also formally defined. An HA task model is incrementally constructed from the ETS scripts. This model transformation enables verification of possibly incomplete task scripts in the HA model. As an illustrative example, we provide a virtual task scenario for a museum guide robot and describe the process of the model transformation.