Panta Rhei: Curiosity-Driven Exploration to Learn the Image-Schematic Affordances of Pouring Liquids

Despite rapid progress, cognitive robots have yet to match the facility with which humans acquire and find ways to reuse manipulation skills. An important component of human cognition seems to be our curiosity-driven exploration of our environments, which results in generalizable theories for action outcome prediction via analogical reasoning. In this paper, we implement a method to emulate this curiosity drive in simulations of the situation of pouring liquids between containers, and to use these simulations to construct a symbolic theory of pouring. The theory links qualitative descriptions of an initial state and manner of pouring with observed behaviors, and can be used to predict qualitative outcomes or select manners of pouring towards achieving a goal.