Learning an Outlier-Robust Kalman Filter

  title={Learning an Outlier-Robust Kalman Filter},
  author={Jo-Anne Ting and Evangelos Theodorou and Stefan Schaal},
We introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by the user. Systems that rely on high quality sensory data (for instance, robotic systems) can be sensitive to data containing outliers. The standard Kalman filter is not robust to outliers, and other variations of the Kalman filter have been proposed to overcome this issue. However, these methods may require manual parameter tuning, use of heuristics or… CONTINUE READING
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