Conference or Workshop Item #27963

Abstract

In this paper a supervised learning approach using a multilayer neural network for learning the position in a 3-D space and the radius of a generic sphere is introduced. Learning is based on laser range finder measurements of the surface of spheres of known radii at known positions. The problem is first formulated. An analytical solution for a set of four laser range finders and a solution based on supervised learning are then given. Both solutions are compared. Experimental results are reported showing the feasibility and novelty of the approach.