Adaptive computation algorithm for simultaneous localization and mapping (SLAM)

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

Abstract

Computationally Efficient SLAM (CESLAM) was proposed to improve the accuracy and runtime efficiency of FastSLAM 1.0 and FastSLAM 2.0. This method adopts the landmark measurement with the maximum likelihood, where the particle state is updated before updating the landmark estimate. Also, CESLAM solves the problem of real-time performance. In this paper, a modified version of CESLAM, called adaptive computation SLAM (ACSLAM), as an adaptive SLAM enhances the localization and mapping accuracy along with better runtime performance. In an empirical evaluation in a rich environment, we show that ACSLAM runs about twice as fast as FastSLAM 2.0 and increases the accuracy of the location estimate by a factor of two.

Original languageEnglish
Title of host publicationRobot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications
EditorsFakhri Karray, Jong-Hwan Kim, Hyun Myung, Jun Jo, Peter Sincak
PublisherSpringer Verlag
Pages75-83
Number of pages9
ISBN (Print)9783319312910
DOIs
Publication statusPublished - 2017 Jan 1
Event4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015 - Bucheon, Korea, Republic of
Duration: 2015 Dec 142015 Dec 16

Publication series

NameAdvances in Intelligent Systems and Computing
Volume447
ISSN (Print)2194-5357

Other

Other4th International Conference on Robot Intelligence Technology and Applications, RiTA 2015
CountryKorea, Republic of
CityBucheon
Period15/12/1415/12/16

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Keywords

  • CESLAM
  • Extended kalman filter
  • Fastslam
  • Particle filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Kung, D. W., Hsu, C. C., Wang, W. Y., & Baltes, J. (2017). Adaptive computation algorithm for simultaneous localization and mapping (SLAM). In F. Karray, J-H. Kim, H. Myung, J. Jo, & P. Sincak (Eds.), Robot Intelligence Technology and Applications 4 - Results from the 4th International Conference on Robot Intelligence Technology and Applications (pp. 75-83). (Advances in Intelligent Systems and Computing; Vol. 447). Springer Verlag. https://doi.org/10.1007/978-3-319-31293-4_7