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Accurate Map-Based RGB-D SLAM for Mobile Robots

  • Dominik Belter
  • Michał Nowicki
  • Piotr Skrzypczyński
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 418)

Abstract

In this paper we present and evaluate a map-based RGB-D SLAM (Simultaneous Localization and Mapping) system employing a novel idea of combining efficient visual odometry and a persistent map of 3D point features used to jointly optimize the sensor (robot) poses and the feature positions. The optimization problem is represented as a factor graph. The SLAM system consists of a front-end that tracks the sensor frame-by-frame, extracts point features, and associates them with the map, and a back-end that manages and optimizes the map. We propose a robust approach to data association, which combines efficient selection of candidate features from the map, matching of visual descriptors guided by the sensor pose prediction from visual odometry, and verification of the associations in both the image plane and 3D space. The improved accuracy and robustness is demonstrated on publicly available data sets.

Keywords

SLAM Point features Tracking Factor graph RGB-D data 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Dominik Belter
    • 1
  • Michał Nowicki
    • 1
  • Piotr Skrzypczyński
    • 1
  1. 1.Institute of Control and Information EngineeringPoznań University of TechnologyPoznańPoland

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