Scan likelihood evaluation in FastSLAM using binary Bayes filter

Hyukdoo Choi, Euntai Kim, Gwang Woong Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

FastSLAM is a fundamental algorithm for Simultaneous Localization and Mapping (SLAM). FastSLAM based on grid map is a popular method to build a map of both the structured and unstructured environment. The performance of FastSLAM significantly depends on evaluation of measurement likelihood. In this paper, we propose a new method to evaluate laser scan likelihood using the binary Bayes filter. This method supports the right particles but does not suffer from particle depletion problem. We implemented the hardware system based on the Pioneer 2-DX platform equipped with the Hokuyo laser scanner. The experimental result shows that the proposed method builds the map accurately.

Original languageEnglish
Title of host publication2013 IEEE 11th IVMSP Workshop
Subtitle of host publication3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings
DOIs
Publication statusPublished - 2013 Nov 28
Event2013 IEEE 11th Workshop on 3D Image/Video Technologies and Applications, IVMSP 2013 - Seoul, Korea, Republic of
Duration: 2013 Jun 102013 Jun 12

Publication series

Name2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings

Other

Other2013 IEEE 11th Workshop on 3D Image/Video Technologies and Applications, IVMSP 2013
CountryKorea, Republic of
CitySeoul
Period13/6/1013/6/12

All Science Journal Classification (ASJC) codes

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Choi, H., Kim, E., & Yang, G. W. (2013). Scan likelihood evaluation in FastSLAM using binary Bayes filter. In 2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings [6611891] (2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings). https://doi.org/10.1109/IVMSPW.2013.6611891