TY  - CONF
AV  - none
TI  - An implementation of SLAM with extended Kalman filter
ID  - scholars8963
KW  - Bandpass filters; Computer software; Hardware; High level languages; Indoor positioning systems; Kalman filters; Range finders; Robotics
KW  -  Hardware implementations; Indoor environment; Laser range finders; Python; Simultaneous localization and mapping; SLAM; Software and hardwares; Software implementation
KW  -  Extended Kalman filters
N1  - cited By 16; Conference of 6th International Conference on Intelligent and Advanced Systems, ICIAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125970
N2  - This paper discusses an implementation of Extended Kalman filter (EKF) in performing Simultaneous Localization and Mapping (SLAM). The implementation is divided into software and hardware phases. The software implementation applies EKF using Python on a library dataset to produce a map of the supposed environment. The result was verified against the original map and found to be relatively accurate with minor inaccuracies. In the hardware implementation stage, real life data was gathered from an indoor environment via a laser range finder and a pair of wheel encoders placed on a mobile robot. The resulting map shows at least five marked inaccuracies but the overall form is passable. © 2016 IEEE.
PB  - Institute of Electrical and Electronics Engineers Inc.
SN  - 9781509008452
Y1  - 2017///
A1  - Saman, A.B.S.H.M.
A1  - Lotfy, A.H.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011977071&doi=10.1109%2fICIAS.2016.7824105&partnerID=40&md5=212572503d8af499d137e71d98366506
ER  -