@inproceedings{d5bb15259ba44176ad85b7d9beec5f91,
title = "Extended Kalman Filter for indoor and outdoor localization of a wheeled mobile robot",
abstract = "This paper presents a robot localization algorithm, that uses an Extended Kalman Filter (EKF) to fuse data from optical wheel encoders, a gyroscope and an accelerometer for an indoor navigation and additionally from DGPS unit for an outdoor scenario. The algorithm's performance is experimentally evaluated using a skid-steered SeekurJr mobile robot. Experimental results are provided to compare the localization accuracy achieved using the proposed algorithm with those using pure odometry readings and pure DGPS readings.",
author = "Anna Skobeleva and Valeri Ugrinovskii and Ian Petersen",
note = "Publisher Copyright: {\textcopyright} 2016 Engineers Australia.; 2016 Australian Control Conference, AuCC 2016 ; Conference date: 03-11-2016 Through 04-11-2016",
year = "2017",
month = mar,
day = "1",
doi = "10.1109/AUCC.2016.7868190",
language = "English",
series = "2016 Australian Control Conference, AuCC 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "212--216",
booktitle = "2016 Australian Control Conference, AuCC 2016",
address = "United States",
}