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A State-of-the-Art Review on SLAM

  • Harbin Institute of Technology Shenzhen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

SLAM (Simultaneous Localization and Mapping), also known as CML (Concurrent Mapping and Localization), refers to real-time positioning and map building, or concurrent mapping and positioning. After nearly 30 years of research on SLAM, there have been quite a few breakthroughs in the SLAM community. This paper aims to provide an insightful review of information background, recent development, feature, implementation, and recent issue in SLAM. This paper includes the following parts: First of all, it gives an overview of the basic development of SLAM from its introduction to the present. Then, and most importantly, it summarizes the mainstream SLAM technology and theoretical basis. In addition, some cutting-edge and novel SLAM research results are discussed respectively. Finally, this paper summarizes and introduces some practical applications of SLAM technology.

Original languageEnglish
Title of host publicationIntelligent Robotics and Applications - 15th International Conference, ICIRA 2022, Proceedings
EditorsHonghai Liu, Weihong Ren, Zhouping Yin, Lianqing Liu, Li Jiang, Guoying Gu, Xinyu Wu
PublisherSpringer Science and Business Media Deutschland GmbH
Pages240-251
Number of pages12
ISBN (Print)9783031138348
DOIs
StatePublished - 2022
Externally publishedYes
Event15th International Conference on Intelligent Robotics and Applications, ICIRA 2022 - Harbin, China
Duration: 1 Aug 20223 Aug 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13457 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Intelligent Robotics and Applications, ICIRA 2022
Country/TerritoryChina
CityHarbin
Period1/08/223/08/22

Keywords

  • Perception
  • Robots
  • Sensing
  • Simultaneous localization and mapping

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