A survey of state-of-the-art on visual SLAM

Iman Abaspur Kazerouni, Luke Fitzgerald, Gerard Dooly, Daniel Toal

Research output: Contribution to journalReview articlepeer-review

Abstract

This paper is an overview to Visual Simultaneous Localization and Mapping (V-SLAM). We discuss the basic definitions in the SLAM and vision system fields and provide a review of the state-of-the-art methods utilized for mobile robot's vision and SLAM. This paper covers topics from the basic SLAM methods, vision sensors, machine vision algorithms for feature extraction and matching, Deep Learning (DL) methods and datasets for Visual Odometry (VO) and Loop Closure (LC) in V-SLAM applications. Several feature extraction and matching algorithms are simulated to show a better vision of feature-based techniques.

Original languageEnglish
Article number117734
JournalExpert Systems with Applications
Volume205
DOIs
Publication statusPublished - 1 Nov 2022

Keywords

  • Deep learning
  • Feature matching
  • Robot
  • Sensors
  • SLAM

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