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A Real-Time Algorithm for Mobile Robot Mapping Based on Rotation-Invariant Descriptors and Iterative Close Point Algorithm

  • A. VokhmintcevEmail author
  • K. Yakovlev
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 661)

Abstract

Nowadays many algorithms for mobile robot mapping in indoor environments have been created. In this work we use a Kinect 2.0 camera, a visible range cameras Beward B2720 and an infrared camera Flir Tau 2 for building 3D dense maps of indoor environments. We present the RGB-D Mapping and a new fusion algorithm combining visual features and depth information for matching images, aligning of 3D point clouds, a “loop-closure” detection, pose graph optimization to build global consistent 3D maps. Such 3D maps of environments have various applications in robot navigation, real-time tracking, non-cooperative remote surveillance, face recognition, semantic mapping. The performance and computational complexity of the proposed RGB-D Mapping algorithm in real indoor environments is presented and discussed.

Keywords

Fusion Simultaneous location and mapping Iterative closest point algorithm Matching algorithm Histograms of oriented gradients Depth map 

Notes

Acknolwledgments

The work was supported by the RFBR, project no 16-08-00342 and the Ministry of Education and Science of Russian Federation, grant no.2.1766.2014.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Research LaboratoryChelyabinsk State UniversityChelyabinskRussia
  2. 2.Computer Science and Control of Russian Academy of SciencesNational Research University Higher School of EconomicsMoscowRussia

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