A Review of Visual SLAM for Dynamic Objects

Lina Zhao, Baoguo Wei, Lixin Li, Xu Li

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

5 Scopus citations

Abstract

With the wide application of SLAM in fields such as autonomous driving and robot navigation, higher requirements for human-robot interaction capabilities in real scenes have been put forward, so the processing of dynamic targets has developed into one of the research hotspots of SLAM. In this review, visual SLAM is divided into two categories according to the different ways for dynamic target processing: static background map reconstruction, tracking and real scene reconstruction of dynamic targets. This paper discusses the two types of SLAM methods, summarizes the advantages and disadvantages of different methods, compares the experimental results of some methods, and finally provides an outlook on the future trend of visual SLAM and concludes the whole review.

Original languageEnglish
Title of host publicationICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications
EditorsWenxiang Xie, Shibin Gao, Xiaoqiong He, Xing Zhu, Jingjing Huang, Weirong Chen, Lei Ma, Haiyan Shu, Wenping Cao, Lijun Jiang, Zeliang Shu
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1080-1085
Number of pages6
ISBN (Electronic)9781665409841
DOIs
StatePublished - 2022
Event17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022 - Chengdu, China
Duration: 16 Dec 202219 Dec 2022

Publication series

NameICIEA 2022 - Proceedings of the 17th IEEE Conference on Industrial Electronics and Applications

Conference

Conference17th IEEE Conference on Industrial Electronics and Applications, ICIEA 2022
Country/TerritoryChina
CityChengdu
Period16/12/2219/12/22

Keywords

  • Dynamic objects
  • Real Scene
  • Visual SLAM

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