Feature selection criteria for real time EKF-SLAM algorithm

Fernando Auat Cheein, Gustavo Scaglia, Fernando Di Sciasio, Ricardo Carelli

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


This paper presents a seletion procedure for environmet features for the correction stage of a SLAM (Simultaneous Localization and Mapping) algorithm based on an Extended Kalman Filter (EKF). This approach decreases the computational time of the correction stage which allows for real and constant-time implementations of the SLAM. The selection procedure consists in chosing the features the SLAM system state covariance is more sensible to. The entire system is implemented on a mobile robot equipped with a range sensor laser. The features extracted from the environment correspond to lines and corners. Experimental results of the real time SLAM algorithm and an analysis of the processing-time consumed by the SLAM with the feature selection procedure proposed are shown. A comparison between the feature selection approach proposed and the classical sequential EKF-SLAM along with an entropy feature selection approach is also performed.

Original languageEnglish
Pages (from-to)115-124
Number of pages10
JournalInternational Journal of Advanced Robotic Systems
Issue number2
Publication statusPublished - Jun 2010


  • Feature selection
  • Mobile robots
  • SLAM

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Artificial Intelligence


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