Abstract This work introduces a self-supervised architecture for robust classification of moving obstacles in urban environments. Our approach presents a hierarchical scheme that r...
Roman Katz, Juan Nieto, Eduardo Mario Nebot, Bertr...
Classifiers favoring sparse solutions, such as support vector machines, relevance vector machines, LASSO-regression based classifiers, etc., provide competitive methods for classi...
This paper presents a new framework for anytime heuristic search where the task is to achieve as many goals as possible within the allocated resources. We show the inadequacy of t...
Abstract--Suppose for a given classification or function approximation (FA) problem data are collected using sensors. From the output of the th sensor, features are extracted, ther...
The problem of developing local reactive obstacle-avoidance behaviors by a mobile robot through online real-time learning is considered. The robot operated in an unknown bounded 2...