Mobile Robot Localization via Machine Learning

  • Alexander Kuleshov
  • Alexander Bernstein
  • Evgeny Burnaev
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10358)

Abstract

We consider an appearance-based robot self-localization problem in the machine learning framework. Using recent manifold learning techniques, we propose a new geometrically motivated solution. The solution includes estimation of the robot localization mapping from the appearance manifold to the robot localization space, as well as estimation of the inverse mapping for image modeling. The latter allows solving the robot localization problem as a Kalman filtering problem.

Keywords

Machine learning Robotics Mobile robot self-localization Appearance-based learning Manifold learning Regression on manifolds 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Alexander Kuleshov
    • 1
  • Alexander Bernstein
    • 1
    • 2
  • Evgeny Burnaev
    • 1
    • 2
  1. 1.Skolkovo Institute of Science and TechnologyMoscowRussia
  2. 2.Kharkevich Institute for Information Transmission Problems RASMoscowRussia

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