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FLIRT: Interest Regions for 2D Range Data with Applications to Robot Navigation

  • Gian Diego TipaldiEmail author
  • Manuel Braun
  • Kai O. Arras
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 79)

Abstract

In this paper we present the Fast Laser Interest Region Transform (FLIRT), a multi-scale interest region operator for 2D range data. FLIRT combines a detector based on a geodesic curve approximation of the range signal and a descriptor based on a polar histogram of occupancy probabilities. This combination was found to perform best in a set of comparative benchmarks on standard indoor and outdoor data sets. The experiments show that FLIRT features have similar repeatability and matching performance than interest points in the computer vision literature.We demonstrate how FLIRT in conjunction with RANSAC make up an accurate, highly robust and particularly simple SLAM front-end that can be applied for navigation tasks such as loop closing, global localization, incremental mapping and SLAM. In the experiments carried out in structured, unstructured, indoor, outdoor, highly dynamic and static environments, we find that FLIRT is able to robustly capture the invariant structures in the data, allowing for very high global localization and loop detection probabilities from single scans. As data association with FLIRT scales linearly with the map size, the method is also fast. The evaluation of FLIRT maps using a recently introduced SLAM characterization metric further shows that the maps are better or on par with the state of the art while being produced by simpler algorithms. Finally, the presented methods are structurally identical to the algorithms for visual interest points making the unified treatment of range and image data possible.

Keywords

Interest Point Data Association Robot Navigation Global Localization Interest Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2014

Authors and Affiliations

  • Gian Diego Tipaldi
    • 1
    Email author
  • Manuel Braun
    • 1
  • Kai O. Arras
    • 1
  1. 1.Social Robotics Laboratory, Department of Computer ScienceUniversity of FreiburgFreiburgGermany

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