• Closing the Loop with Graphical SLAM 

      Folkesson, John; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2007-08)
      The problem of simultaneous localization and mapping (SLAM) is addressed using a graphical method. The main contributions are a computational complexity that scales well with the size of the environment, the elimination ...
    • A Discriminative Approach to Robust Visual Place Recognition 

      Pronobis, A.; Caputo, B.; Jensfelt, Patric; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2006-10)
      An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Usually localization ...
    • Exploiting Distinguishable Image Features in Robotic Mapping and Localization 

      Jensfelt, Patric; Folkesson, John; Kragic, Danica; Christensen, Henrik I. (Georgia Institute of TechnologySpringer Verlag, 2006-03)
      Simultaneous localization and mapping (SLAM) is an important research area in robotics. Lately, systems that use a single bearing-only sensors have received significant attention and the use of visual sensors have been ...
    • Information-based Reduced Landmark SLAM 

      Choudhary, Siddharth; Indelman, Vadim; Christensen, Henrik I.; Dellaert, Frank (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2015-05)
      In this paper, we present an information-based approach to select a reduced number of landmarks and poses for a robot to localize itself and simultaneously build an accurate map. We develop an information theoretic ...
    • The M-Space Feature Representation for SLAM 

      Folkesson, John; Jensfelt, Patric; Christensen, Henrik I. (Georgia Institute of TechnologyInstitute of Electrical and Electronics Engineers, 2007-10)
      In this paper, a new feature representation for simultaneous localization and mapping (SLAM) is discussed. The representation addresses feature symmetries and constraints explicitly to make the basic model numerically ...