Integrating Robot Task Scripts with a Cognitive Architecture for Cognitive Human-Robot Interactions

In spite of the long history of intelligent humanoid robots, endowing human-like commonsense knowledge to a robot is still a difficult problem. Since a knowledge base consisting of a large number of rules and facts is not an efficient structure that can express situational and background knowledge for humanoid robots, more compact yet forgiving representation is required. Our proposal is to employ a script design that contains richness and diversity needed for robot's task planning, in conjunction with a robust cognitive architecture called EM-ONE, the latest extant account of an implemented cognitive architecture. The script structure has its advantages in flexibility and extensibility for a variety of situations or tasks at hand, along with reusability. As the number of scripts increases, the coverage for diverseness of human-robot interaction (HRI) situation grows. In this paper, we discuss three cognitive models used as our cognitive architecture basis and describe our efforts for generating task scripts in a semi-automatic way by reusing the already existing scripts.