publication . Preprint . 2010

A Neuro-Fuzzy Multi Swarm FastSLAM Framework

Havangi, R.; Teshnehlab, M.; Nekoui, M. A.;
Open Access English
  • Published: 22 Mar 2010
FastSLAM is a framework for simultaneous localization using a Rao-Blackwellized particle filter. In FastSLAM, particle filter is used for the mobile robot pose (position and orientation) estimation, and an Extended Kalman Filter (EKF) is used for the feature location's estimation. However, FastSLAM degenerates over time. This degeneracy is due to the fact that a particle set estimating the pose of the robot loses its diversity. One of the main reasons for loosing particle diversity in FastSLAM is sample impoverishment. It occurs when likelihood lies in the tail of the proposal distribution. In this case, most of particle weights are insignificant. Another proble...
arXiv: Computer Science::Robotics
free text keywords: Computer Science - Robotics
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