Unscented SLAM for large-scale outdoor environments

  title={Unscented SLAM for large-scale outdoor environments},
  author={Ruben Martinez-Cantin and Jos{\'e} A. Castellanos},
  journal={2005 IEEE/RSJ International Conference on Intelligent Robots and Systems},
This paper presents an experimentally validated alternative to the classical extended Kalman filter approach to the solution of the probabilistic state-space simultaneous localization and mapping (SLAM) problem. Several authors have reported the divergence of this classical approach due to the linearization of the inherent nonlinear nature of the SLAM problem. Hence, the approach described in this work aims to avoid the analytical linearization based on Taylor-series expansion of both the model… CONTINUE READING
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Estimation with Applications to Tracking and Navigation

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