Hierarchical intelligent control for robotic motions-hybrid neuromorphic and symbolic control

Abstract

This paper presents a new scheme for intelligent control of robotic manipulators. This scheme is an integrated approach of the neuromorphic and symbolic control of robotic manipulators, including the applied neural network for the servo control and the knowledge based approximation. Therefore, this scheme has a hierarchical structure, and is known as 'hierarchical intelligent control'. The neural network in the servo control level is the numerical manipulation, while the knowledge based part is the symbolic manipulation. In the neuromorphic control, the neural network compensates the nonlinearity of the system and the uncertainty in environment. The knowledge base part makes control strategy symbolically for the servo level. This is an analogous control system to the human cerebral control structure.