PARTICLE FILTER IN SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) USING DIFFERENTIAL DRIVE MOBILE ROBOT

Authors

  • Norhidayah Mohamad Yatim Faculty Electronics and Computer Engineering, Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia
  • Norlida Buniyamin Faculty of Engineering, Universiti Teknologi MARA (UiTM), Shah Alam, Selangor, Malaysia

DOI:

https://doi.org/10.11113/jt.v77.6557

Keywords:

SLAM, mapping, particle filter, e-puck

Abstract

Simultaneous Localization and Mapping (SLAM) problem is a well-known problem in robotics, where a robot has to localize itself and map its environment simultaneously. Particle filter (PF) is one of the most adapted estimation algorithms for SLAM apart from Kalman filter (KF) and Extended Kalman Filter (EKF). In this work, particle filter algorithm has been successfully implemented using a simple differential drive mobile robot called e-puck. The performance of the algorithm implemented is analyzed via varied number of particles. From simulation, accuracy of the resulting maps differed according to the number of particles used. The Root Mean Squared Error (RMSE) of a larger number of particles is smaller compared to a lower number of particles after a period of time.  

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Published

2015-12-01

How to Cite

Mohamad Yatim, N., & Buniyamin, N. (2015). PARTICLE FILTER IN SIMULTANEOUS LOCALIZATION AND MAPPING (SLAM) USING DIFFERENTIAL DRIVE MOBILE ROBOT. Jurnal Teknologi, 77(20). https://doi.org/10.11113/jt.v77.6557