Adaptive filtering for pose estimation in visual servoing

@inproceedings{Ficocelli2001AdaptiveFF,
  title={Adaptive filtering for pose estimation in visual servoing},
  author={Maurizio Ficocelli and Farrokh Janabi-Sharifi},
  booktitle={IROS},
  year={2001}
}
The extended Kalman filter has been shown to produce accurate pose estimates for visual servoing, assuming that the dynamic noise covariance is known prior to application. Poor estimation of the dynamic noise covariance matrix, Q, can lead to large tracking error or divergence. The following paper discusses the use of an adaptive filtering technique to update, Q . This provides robwt object tracking with unknown trajectory for a visual servoing system with little increase in computational cost… CONTINUE READING
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