Toward Image-Based Localization for AIBO Using Wavelet Transform

Abstract

Abstract. This paper describes a similarity measure for images to be used in image-based localization for autonomous robots with low computational resources. We propose a novel signature to be extracted from the image and to be stored in memory. The proposed signature allows, at the same time, memory saving and fast similarity calculation. The signature is based on the calculation of the 2D Haar Wavelet Transform of the gray-level image. We present experiments showing the effectiveness of the proposed image similarity measure. The used images were collected using the AIBOs ERS-7 of the RoboCup Team Araibo of the University of Tokyo on a RoboCup field, however, the proposed image similarity measure does not use any information on the structure of the environment and do not exploit the peculiar features of the RoboCup environment.

Appearance‐based approach to hybrid metric‐topological simultaneous localisation and mapping

“…As regards appearance‐based vision methods, the whole information in the scenes is used. Several alternatives can be used to describe images, such as the principal components of the image [30, 31], Haar wavelet coefficients [32, 33], Fourier components [34, 35], image histograms [36] or image frequency filtering [37]. To complete the information provided by vision systems, it is possible to take also into account the wheel odometry, GPS information or visual odometry and to set up a probabilistic context with all this information.…”