Matej Artač and Aleš Leonardis (2002) Mobile robot localisation with incremental PCA. In: 11th IEEE Mediterranean Electrotechnical Conference, MELECON 2002, May 7-9 2002, Cairo, Egypt.
Mobile robots can employ different sensors to collect data about the environment. We propose to use a special sensor (a catadioptric camera) which provides panoramic views at each robot position. To model the environment for later navigation and localisation, we build a representation of the appearance by compressing the set of panoramic images by Principal Component Analysis (PCA). Since the batch application of the PCA is inappropriate in this case, we propose to apply an incremental approach. This leads to novel aspects regarding the adaptation of compressed partial representation. We provide empirical results which indicate the performance of the proposed method is comparable to the performance of the batch method in terms of compression, computational cost, and, most importantly, precision of localisation.
|Item Type: ||Conference or Workshop Item (Paper)|
|Keywords: ||computer vision, principal component analysis, mobile robots, omnidirectional vision, visual learning, visual localisation|
|Language of Content: ||English|
|Institution: ||University of Ljubljana|
|Department: ||Faculty of Computer and Information Science|
|Divisions: ||Faculty of Computer and Information Science > Computer Vision Laboratory|
|Item ID: ||78|
|Date Deposited: ||15 May 2003|
|Last Modified: ||13 Aug 2011 00:32|
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