RT info:eu-repo/semantics/article T1 Are you ABLE to perform a life-long visual topological localization? A1 Arroyo Contera, Roberto A1 Fernández Alcantarilla, Pablo A1 Bergasa Pascual, Luis Miguel A1 Romera Carmena, Eduardo K1 Localization across seasons K1 Visual place recognition K1 Loop closure detection K1 Image matching K1 Binary descriptors K1 Electrónica K1 Electronics AB Visual topological localization is a process typically required by varied mobile autonomous robots, but it is a complex task if long operating periods are considered. This is because of the appearance variations suffered in a place: dynamic elements, illumination or weather. Due to these problems, long-term visual place recognition across seasons has become a challenge for the robotics community. For this reason, we propose an innovative method for a robust and efficient life-long localization using cameras. In this paper, we describe our approach (ABLE), which includes three different versions depending on the type of images: monocular, stereo and panoramic. This distinction makes our proposal more adaptable and effective, because it allows to exploit the extra information that can be provided by each type of camera. Besides, we contribute a novel methodology for identifying places, which is based on a fast matching of global binary descriptors extracted from sequences of images. The presented results demonstrate the benefits of using ABLE, which is compared to the most representative state-of-the-art algorithms in long-term conditions. PB Springer Nature SN 0929-5593 YR 2018 FD 2018-03-20 LK http://hdl.handle.net/10017/43268 UL http://hdl.handle.net/10017/43268 LA eng NO Ministerio de Economía y Competitividad DS MINDS@UW RD 29-mar-2024