Adaptive localization for mobile robots in urban environments using low-cost sensors and enhanced topological map

Yu Cheol Lee, Christiand, Wonpil Yu, Jae Il Cho

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

This paper presents a technique for accurate localization of mobile robots using an enhanced topological map and using the low-cost sensors such as wheel odometer, global positioning system (GPS), and mono-camera. The localization framework is based on EKF to fuse the sensor data and the topological map. The sensor data include the positions of traffic marks measured by camera and topological map having the actual positions of traffic marks extracted from aerial or satellite images in advance. Our approach obtains the adaptive parameter for EKF localization by matching two positions, measured by camera and extracted from topological map, on each traffic mark. The adaptive parameter reflects the geographical characteristics, e.g. hill, corner, and road surfaces. The proposed method has shown high accuracy result and apparently better performance of the EKF localization with adaptive parameter. The proposed method is economically feasible and practically applicable to commercial robots using the low-cost sensors and providing the reliable localization services.

Original languageEnglish
Title of host publicationIEEE 15th International Conference on Advanced Robotics
Subtitle of host publicationNew Boundaries for Robotics, ICAR 2011
Pages569-575
Number of pages7
DOIs
StatePublished - 2011
EventIEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011 - Tallinn, Estonia
Duration: 20 Jun 201123 Jun 2011

Publication series

NameIEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011

Conference

ConferenceIEEE 15th International Conference on Advanced Robotics: New Boundaries for Robotics, ICAR 2011
Country/TerritoryEstonia
CityTallinn
Period20/06/1123/06/11

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