Associative model for solving the wall-following problem

Abstract

A navigation system for a robot is presented in this work. The Wall-Following problem has become a classic problem of Robotics due to robots have to be able to move through a particular stage. This problem is proposed as a classifying task and it is solved using an associative approach. In particular, we used Morphological Associative Memories as classifier. Three testing methods were applied to validate the performance of our proposal: Leave-One-Out, Hold-Out and K-fold Cross-Validation and the average obtained was of 91.57%, overcoming the neural approach. © 2012 Springer-Verlag Berlin Heidelberg.