CAOS: A hierarchical robot control system
Control systems which enable robots to behave intelligently is a major issue in todays process of automating factories. This paper presents a hierarchical robot control system, termed CAOS for Control using Action Oriented Schemas, with ideas taken from the neurosciences. We are using action oriented schemas (called neuroschemas) as the basic building blocks in a hierarchical control structure which is being implemented on a BBN Butterfly Parallel Processor. Serial versions in C and LISP are presented with examples showing how CAOS achieves the goals of recognizing three-dimensional polyhedral objects. We also describe a simulation on how it manipulates objects. Moreover, the ongoing implementation of a parallel version of the system is discussed.