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Conference Paper Relative Localization using Path Odometry Information
Cited 37 time in scopus Share share facebook twitter linkedin kakaostory
Authors
Nak Ju Lett Doh, Howie Choset, Wan Kyun Chung
Issue Date
2006-09
Citation
Autonomous Robots, v.21, no.2, pp.143-154
ISSN
0929-5593
Publisher
Springer
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1007/s10514-006-6474-8
Abstract
All mobile bases suffer from localization errors. Previous approaches to accommodate for localization errors either use external sensors such as lasers or sonars, or use internal sensors like encoders. An encoder's information is integrated to derive the robot's position; this is called odometry. A combination of external and internal sensors will ultimately solve the localization error problem, but this paper focuses only on processing the odometry information. We solve the localization problem by forming a new odometry error model for the synchro-drive robot then use a novel procedure to accurately estimate the error parameters of the odometry error model. This new procedure drives the robot through a known path and then uses the shape of the resulting path to estimate the model parameters. Experimental results validate that the proposed method precisely estimates the error parameters and that the derived odometry error model of the synchro-drive robot is correct.
KSP Keywords
Model parameter, Relative Localization, Synchro-drive, error model, external and internal, internal sensor, localization error, localization problem