Application of neural networks in robotic control

Abstract

The application of the fuzzy neural-logic network theory to improve the performance of controlling a robot is explored. Neural-logic is a three-valued logic and as such it can represent many more logical variations than the two-valued Boolean logic, e.g., the neural-logic network can implement the logical 'NOT' operation, which is essential for logical inference. It is concluded that the performance of a robot using the fuzzy neural-logic network controller will be significantly improved because it can handle the logical 'DON'T KNOW' operations so that it provides not only the conventional pattern matching capability, but also the inferencing capability.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>