Kızılberisi algılayıcılarla hedef ayırdetme ve konum kestirim yöntemlerinin karşılaştırmalı incelemesi

This study compares the performances of various techniques for the differentia-tion and localization of commonly encountered features in indoor environments,such as planes, corners, edges, and cylinders, possibly with different surface prop-erties, using simple infrared sensors. The intensity measurements obtained fromsuch sensors are highly dependent on the location, geometry, and surface prop-erties of the reflecting feature in a way that cannot be represented by a simpleanalytical relationship, therefore complicating the localization and differentiationprocess. The techniques considered include rule-based, template-based, and neu-ral network-based target differentiation, parametric surface differentiation, andstatistical pattern recognition techniques such as parametric density estimation,various linear and quadratic classifiers, mixture of normals, kernel estimator,k-nearest neighbor, artificial neural network, and support vector machine classi-fiers. The geometrical properties of the targets are more distinctive than theirsurface properties, and surface recognition is the limiting factor in differentiation.Mixture of normals classifier with three components correctly differentiates threetypes of geometries with different surface properties, resulting in the best perfor-mance (100%) in geometry differentiation. For a set of six surfaces, we get a cor-rect differentiation rate of 100% in parametric differentiation based on reflectionmodeling. The results demonstrate that simple infrared sensors, when coupledwith appropriate processing, can be used to extract substantially more informa-tion than such devices are commonly employed for. The demonstrated systemwould find application in intelligent autonomous systems such as mobile robotswhose task involves surveying an unknown environment made of different geom-etry and surface types. Industrial applications where different materials/surfacesmust be identified and separated may also benefit from this approach.ivvKeywords: infrared sensors, optical sensing, target differentiation, target local-ization, surface recognition, position estimation, feature extraction, statisticalpattern recognition, artificial neural networks.