Distributed Adaptive Sub-Filter for Range-Only SLAM

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Abstract

The primary challenge in 3D range-only SLAM is achieving rapid and accurate state estimation in high-dimensional environments. This paper introduces a distributed adaptive sub-filter framework, in which independent sub-filters are designed for each beacon. Within each sub-filter, a hybrid Unscented Kalman Filter (UKF) and particle filter(PF) approach is used for local state estimation. The global filter output is then derived by fusing the estimation results from all individual sub-filters. Simulation experiments show that, under identical experimental conditions, the proposed method outperforms the distributed UKF and distributed UIKF in terms of estimation accuracy.

Original languageEnglish
Title of host publicationProceedings of the 44th Chinese Control Conference, CCC 2025
EditorsJian Sun, Hongpeng Yin
PublisherIEEE Computer Society
Pages5083-5088
Number of pages6
ISBN (Electronic)9789887581611
DOIs
Publication statusPublished - 2025
Event44th Chinese Control Conference, CCC 2025 - Chongqing, China
Duration: 28 Jul 202530 Jul 2025

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference44th Chinese Control Conference, CCC 2025
Country/TerritoryChina
CityChongqing
Period28/07/2530/07/25

Keywords

  • Distributed Sub-filter
  • Particle Filter
  • Range-only
  • Simultaneous Localization and Mapping (SLAM)
  • Unscented Kalman Filter

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