TY - GEN
T1 - Extended Kalman Filter for indoor and outdoor localization of a wheeled mobile robot
AU - Skobeleva, Anna
AU - Ugrinovskii, Valeri
AU - Petersen, Ian
N1 - Publisher Copyright:
© 2016 Engineers Australia.
PY - 2017/3/1
Y1 - 2017/3/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85017023578&partnerID=8YFLogxK
U2 - 10.1109/AUCC.2016.7868190
DO - 10.1109/AUCC.2016.7868190
M3 - Conference contribution
T3 - 2016 Australian Control Conference, AuCC 2016
SP - 212
EP - 216
BT - 2016 Australian Control Conference, AuCC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 Australian Control Conference, AuCC 2016
Y2 - 3 November 2016 through 4 November 2016
ER -