A new global localization algorithm based on feature extraction and particle filter

Daniele Caltabiano, Giovanni Muscato, Salvatore Sessa

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

1 Citation (Scopus)

Abstract

This paper describes a new global localization algorithm based on feature extraction and particle filter. This algorithm uses two kinds of sensors: wheels encoders and a laser scanner. A map of the environment is built by taking laser readings of the environment from well-known poses of the robot. The resulting map is composed by a list of features, representing the position of clusters obtained by using the mean shift algorithm. The mean shift algorithm is also applied for each sampling step in order to calculate the importance factor of the particles. The trials have been conducted by using a simulator of a differential drive robot.

Original languageEnglish
Title of host publication14th Mediterranean Conference on Control and Automation, MED'06
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event14th Mediterranean Conference on Control and Automation, MED'06 - Ancona
Duration: 2006 Jun 282006 Jun 30

Other

Other14th Mediterranean Conference on Control and Automation, MED'06
CityAncona
Period06/6/2806/6/30

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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  • Cite this

    Caltabiano, D., Muscato, G., & Sessa, S. (2006). A new global localization algorithm based on feature extraction and particle filter. In 14th Mediterranean Conference on Control and Automation, MED'06 [1700761] https://doi.org/10.1109/MED.2006.328798