Research on Learning from Demonstration (LfD) employed various approaches to model the tasks (Argall et al., 2009), such as state-to-action mapping , predicate calculus (Hofmann et al., 2016), and Hierarchical Task Networks (Nejati et al., 2006;Hogg et al., 2009).
aspiring to enable human robot communication, the framework developed in this paper focuses on task representation using language grounded to a structure of state changes detected from the physical world.