Probabilistic Appearance-Invariant Topometric Localization With New Place Awareness

@article{Xu2021ProbabilisticAT,
  title={Probabilistic Appearance-Invariant Topometric Localization With New Place Awareness},
  author={Ming Xu and Tobias Fischer and Niko Sunderhauf and Michael Milford},
  journal={IEEE Robotics and Automation Letters},
  year={2021},
  volume={6},
  pages={6985-6992}
}
Probabilistic state-estimation approaches offer a principled foundation for designing localization systems, because they naturally integrate sequences of imperfect motion and exteroceptive sensor data. Recently, probabilistic localization systems utilizing appearance-invariant visual place recognition (VPR) methods as the primary exteroceptive sensor have demonstrated state-of-the-art performance in the presence of substantial appearance change. However, existing systems 1) do not fully utilize… 

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