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Object SLAM with Dual Quadric Parameterization

  • Beihang University
  • Zhejiang University of Technology

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

Abstract

Conventional SLAM systems lack the ability to create semantically meaningful maps for scene understanding of robots. In this paper, we estimate a quadric surface for each object by detecting objects from different views and propose an object SLAM that uses dual quadric representations as 3D landmarks to overcome this limitation. A dual quadric can represent the position, orientation, size of an object compactly. We devise a geometric ellipse measurement model that addresses the problem of reconstructed object projection, and demonstrate how to integrate it into the SLAM system in order to jointly estimate camera poses and constrained dual quadric parameters. Our method is valuated on the public dataset. Experiments show the validity of creating maps with high-level information.

Original languageEnglish
Title of host publicationProceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1649-1654
Number of pages6
ISBN (Electronic)9781665422482
DOIs
StatePublished - 1 Aug 2021
Event16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021 - Chengdu, China
Duration: 1 Aug 20214 Aug 2021

Publication series

NameProceedings of the 16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021

Conference

Conference16th IEEE Conference on Industrial Electronics and Applications, ICIEA 2021
Country/TerritoryChina
CityChengdu
Period1/08/214/08/21

Keywords

  • Object SLAM
  • Quadrics
  • Semantic SLAM

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