Towards robust place recognition for robot localization

— Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place recognition algorithm should be robust to dynamic changes and it should perform consistently when recognizing a room (for instance a corridor) in different geographical locations. Also, it should be able to categorize places, a crucial capability for transfer of knowledge and continuous learning. In order to test the suitability of visual recognition algorithms for these tasks, this paper presents a new database, acquired in three different labs across Europe. It contains image sequences of several rooms under dynamic changes, acquired at the same time with a perspective and omnidirectional camera, mounted on a socket. We assess this new database with an appearancebased algorithm that combines local features with support vector mach...

• Type: Conference
• Year: 2008
• Where: ICRA
• Authors: Muhammad Muneeb Ullah, Andrzej Pronobis, Barbara Caputo, Jie Luo, Patric Jensfelt, Henrik I. Christensen
• Keywords: Dynamic Changes, ICRA 2008, Place Recognition, Recognition Algorithms, Robotics