@inproceedings{62867824ab134426ae4cc856b4449042,
title = "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.",
keywords = "Associative Models, Classification, Morphological models, Wall-Following",
author = "Rodolfo Navarro and Elena Acevedo and Antonio Acevedo and Fabiola Mart{\'i}nez",
year = "2012",
doi = "10.1007/978-3-642-31149-9_18",
language = "Ingl{\'e}s",
isbn = "9783642311482",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "176--186",
booktitle = "Pattern Recognition - 4th Mexican Conference, MCPR 2012, Proceedings",
note = "4th Mexican Conference on Pattern Recognition, MCPR 2012 ; Conference date: 27-06-2012 Through 30-06-2012",
}