Probabilistic localization with a blind robot

Lawrence H. Erickson, Joseph Knuth, Jason M. O'Kane, Steven M. LaValle

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

Abstract

Researchers have addressed the localization problem for mobile robots using many different kinds of sensors, including rangefinders, cameras, and odometers. In this paper, we consider localization using a robot that is virtually "blind", having only a clock and contact sensor at its disposal. This represents a drastic reduction in sensing requirements, even in light of existing work that considers localization with limited sensing. We present probabilistic techniques that represent and update the robot's position uncertainty and algorithms to reduce this uncertainty. We demonstrate the experimental effectiveness of these methods using a Roomba autonomous vacuum cleaner robot in laboratory environments.

Original languageEnglish (US)
Title of host publication2008 IEEE International Conference on Robotics and Automation, ICRA 2008
Pages1821-1827
Number of pages7
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Robotics and Automation, ICRA 2008 - Pasadena, CA, United States
Duration: May 19 2008May 23 2008

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729

Other

Other2008 IEEE International Conference on Robotics and Automation, ICRA 2008
Country/TerritoryUnited States
CityPasadena, CA
Period5/19/085/23/08

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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