An approach to global localization problem using mean shift algorithm

Giovanni Muscato, Salvatore Sessa

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

1 Citation (Scopus)

Abstract

This paper describes a global localization algorithm (GLA) for a mobile robot in indoor environments, based on a particle filter. This algorithm uses data obtained by two kinds of sensors: encoder and scanner laser. Given a map of the environment, where the robot moves, a GLA tries to localize the robot on the map by using its sensor data. The map of the environment is preliminary built mixing laser readings from well-known poses of the robot. The mean shift algorithm (MSA) processes the map and obtains a list of features, which is the synthetic map of the environment used in the GLA. The MSA is also applied for each sampling step in order to calculate the importance factor of the particles. The trials have been performed by using a dynamic simulator of a differential drive robot and the 3Morduc mobile robot.

Original languageEnglish
Title of host publicationAdvances in Climbing and Walking Robots - Proceedings of 10th International Conference, CLAWAR 2007
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages565-574
Number of pages10
ISBN (Print)9812708154, 9789812708151
Publication statusPublished - 2007
Externally publishedYes
Event10th International Conference on Climbing and Walking Robots, CLAWAR 2007 - Singapore
Duration: 2007 Jul 162007 Jul 18

Other

Other10th International Conference on Climbing and Walking Robots, CLAWAR 2007
CitySingapore
Period07/7/1607/7/18

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ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction

Cite this

Muscato, G., & Sessa, S. (2007). An approach to global localization problem using mean shift algorithm. In Advances in Climbing and Walking Robots - Proceedings of 10th International Conference, CLAWAR 2007 (pp. 565-574). World Scientific Publishing Co. Pte Ltd.