Square Root Unscented Filter Based FastSLAM Approach tor SLAM Problem Solution

ANKIŞHAN H., Art F.

21st Signal Processing and Communications Applications Conference (SIU), CYPRUS, 24 - 26 Nisan 2013 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2013.6531206
  • Basıldığı Ülke: CYPRUS
  • Anahtar Kelimeler: Square root unscented Kalman filter, FastSlam, Simultaneous localization and mapping, particle filter, LOCALIZATION
  • Ankara Üniversitesi Adresli: Evet

Özet

There are different Bayesian based approaches proposed for the solution of simultaneous localization and mapping (SLAM) problem in the literature. In this study, square root unscented KaIman based (Sru)-FastSLAM and square root unscented particle filter based (SruPt) -FastSLAM were proposed for the SLAM problem solution. The first method used Sru - KaIman filter for estimating the robot position, the landmarks location and particle weights. The second method with the help of FastSlam II uses Sru-Kalman filter for each particle. FastSLAM II, unscented particle filter based (Upf) FastSlam II, unscented (U) FastSIam, unscented KaIman aided (UAided) FastSLAM, Sru-FastSlam and SruPf -FastSLAM were used for comparison of filter performance in the experimental results. It is seen that Sru - FastSlam and SruPf-FastSLAM are alternative to solving the problem of SLAM. The best results for heading, position error of robot/vehicle and uncertainty of position of landmarks were obtained by SruFastSlam II.