Development of a room recognition system using a catadioptric sensor and artificial neural network

Abstract

Robot localization has been a challenging issue in robot navigation. In recent years, there has been increasing interest in topological localization. One popular approach for vision based topological localization is the appearance based method, where the image can be used for recognition in its basic form without extracting local features. The general aim of this work is to develop a room recognition system using appearance-based method for topological localization. In this work, the room recognition is achieved by matching color histogram of image using the Artificial Neural Network. A hardware module and a software module have been developed for this project. The hardware module consists of a catadioptric sensor system implemented on a mobile platform. The software module encompasses several sub modules namely image acquisition; image pre-processing; histogram plotting; histogram filtering, sampling and normalization; neural network for offline training and testing, and finally real time room recognition. A few experiments have been conducted to evaluate the performance of the system and the results have been favorable. Testing for suitable network setting was also carried out and a recommendable setting was proposed.