Low-Cost IR sensor-based localization using accumulated range information

Yun Kyu Choi, Jae-Bok Song

Research output: Contribution to journalArticle

Abstract

Localization which estimates a robot's position and orientation in a given environment is very important for mobile robot navigation. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to increasing the success rate of low-cost sensor-based localization. In this paper, both the previous and the current data obtained from the IR sensors are used for localization in order to utilize as much environment information as possible without increasing the number of sensors. The sensor model used in the monte carlo localization (MCL) is modified so that the accumulated range information may be used to increase the accuracy in estimating the current robot pose. The experimental results show that the proposed method can robustly estimate the robot's pose in indoor environments with several similar places.

Original languageEnglish
Pages (from-to)845-850
Number of pages6
JournalJournal of Institute of Control, Robotics and Systems
Volume15
Issue number8
DOIs
Publication statusPublished - 2009 Aug 1

Fingerprint

Sensor
Robots
Sensors
Range of data
Robot
Costs
Service Robot
Robot Navigation
Inaccurate
Mobile Robot
Estimate
Mobile robots
Navigation
Experimental Results
Model

Keywords

  • Localization
  • MCL (monte carlo localization)
  • Mobile robot
  • Virtual IR sensor

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Applied Mathematics

Cite this

Low-Cost IR sensor-based localization using accumulated range information. / Choi, Yun Kyu; Song, Jae-Bok.

In: Journal of Institute of Control, Robotics and Systems, Vol. 15, No. 8, 01.08.2009, p. 845-850.

Research output: Contribution to journalArticle

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