Robust localization using relative and absolute position estimates

Puneet Goel, Stergios I. Roumeliotis, Gaurav S. Sukhatme

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

113 Scopus citations

Abstract

A low cost strategy based on well calibrated odometry is presented for localizing mobile robots. The paper describes a two-step process for correction of 'systematic errors' in encoder measurements followed by fusion of the calibrated odometry with a gyroscope and GPS resulting in a robust localization scheme. A Kalman filter operating on data from the sensors is used for estimating position and orientation of the robot. Experimental results are presented that show an improvement of at least one order of magnitude in accuracy compared to the un-calibrated, un-filtered case. Our method is systematic, simple and yields very good results. We show that this strategy proves useful when the robot is using GPS to localize itself as well as when GPS becomes unavailable for some time. As a result robot can move in and out of enclosed spaces, such as buildings, while keeping track of its position on the fly.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Intelligent Robots and Systems
PublisherIEEE
Pages1134-1140
Number of pages7
Volume2
StatePublished - Dec 1 1999
Event1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots whith High Intelligence and Emotional Quotients' - Kyongju, South Korea
Duration: Oct 17 1999Oct 21 1999

Other

Other1999 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS'99): Human and Environment Friendly Robots whith High Intelligence and Emotional Quotients'
CityKyongju, South Korea
Period10/17/9910/21/99

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