Self-localization of home robot ApriAttenda™ based on Monte Carlo approach

Nafis Ahmad, Jiang Zhu, Hideichi Nakamoto, Nobuto Matsuhira

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

1 Citation (Scopus)

Abstract

A self-localization technique for home robot is developed for in-door environment. This simple and robust self-localization approach based on Monte Carlo algorithm recovers the robot from catastrophic position tracking failure or kidnapped condition. Position of the robot at different location in the map are determined by using information obtained by laser range finder attached in front of the robot and marker distance measured by stereo vision camera.

Original languageEnglish
Title of host publicationInternational Symposium on Practical Cognitive Agents and Robots, PCAR 2006 - Proceedings
Pages212-220
Number of pages9
DOIs
Publication statusPublished - 2006 Dec 1
Externally publishedYes
EventInternational Symposium on Practical Cognitive Agents and Robots, PCAR 2006 - Perth, WA, Australia
Duration: 2006 Nov 272006 Nov 28

Publication series

NameACM International Conference Proceeding Series
Volume213

Conference

ConferenceInternational Symposium on Practical Cognitive Agents and Robots, PCAR 2006
CountryAustralia
CityPerth, WA
Period06/11/2706/11/28

Keywords

  • MCL
  • home robot
  • self-localization

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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    Ahmad, N., Zhu, J., Nakamoto, H., & Matsuhira, N. (2006). Self-localization of home robot ApriAttenda™ based on Monte Carlo approach. In International Symposium on Practical Cognitive Agents and Robots, PCAR 2006 - Proceedings (pp. 212-220). (ACM International Conference Proceeding Series; Vol. 213). https://doi.org/10.1145/1232425.1232452