A Geometric Radial Basis Function Network for Robot Perception and Action

Abstract

This paper presents a new hyper complex valued Radial Basis Network. This network constitutes a generalization of the standard real valued RBF. This geometric RBF can be used in real time to estimate changes in linear transformations between sets of geometric entities. Experiments using stereo image sequences validate this proposal. We propose a Geometric RBF Network (GRBF-N) designed in the geometric algebra framework. We present an application to estimate linear transformations between sets of geometric entities. Our experiments validate our proposal.