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More Precise SLAM Using Controlled Filter Augmented with Active Alignment

EasyChair Preprint 11562

6 pagesDate: December 18, 2023

Abstract

This work presents a novel method, called Controlled Filter with Active Alignment (CFAA), to address the problem of Simultaneous Localization and Mapping (SLAM). SLAM aims to map an unknown environment while estimating the trajectory of a mobile agent moving within that environment. CFAA combines the two fundamental pillars of SLAM, scan alignment, and loop closure, into a single process. The method is inspired by human perception of self-location and utilizes a mental map for guidance. CFAA employs a Gaussian distribution to estimate possible poses and conducts the alignment process in cycles, where each cycle is influenced by the results of the previous cycle. The Active Alignment mechanism is used in each cycle to determine the quality of each of the possible poses, enabling more accurate simultaneous localization and mapping. Benchmarking tests were conducted on five public datasets, confirming the effectiveness and efficiency of the proposed method.

Keyphrases: Alinhamento, Localização, Mapeamento, Percepção, Robôs

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:11562,
  author    = {Luigi Maciel Ribeiro and Nadia Nedjah and Paulo Victor Rodrigues de Carvalho},
  title     = {More Precise SLAM Using Controlled Filter Augmented with Active Alignment},
  howpublished = {EasyChair Preprint 11562},
  year      = {EasyChair, 2023}}
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