A Comparison between Extended Kalman Filtering and Sequential Monte Carlo Techniques for Simultaneous Localisation and Map-building

@inproceedings{Yuen2002ACB,
  title={A Comparison between Extended Kalman Filtering and Sequential Monte Carlo Techniques for Simultaneous Localisation and Map-building},
  author={David C. K. Yuen and Bruce A. MacDonald},
  year={2002}
}
Monte Carlo Localisation has been applied to solve many different classes of localisation problems. In this paper, we present a possible Simultaneous Localisation and Map-building implementation using the Sequential Monte Carlo technique. Multiple particle filters are created to estimate both the robot and landmark positions simultaneously. The proposed technique shows promising results when compared with those obtained with the Extended Kalman filter. 

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