Expert Control for a Robot Body

Abstract

Mobile robots with dextrous hands and sophisticated sensory systems will require intelligent, knowledge‐based, expert controllers. A design is developed for a robot controller which can acquire task knowledge as it interacts in the world with its human users. The design is based on four reasonable assumptions which lead to a theoretical framework for robot learning systems. The framework is called a multiple‐context learning system. It is a production system with multiple templates for forming productions as the system interacts with the world. Elaborations of the framework and experimental tests of the system are discussed.