RP-VIO: Robust Plane-based Visual-Inertial Odometry for Dynamic Environments

@article{Ram2021RPVIORP,
  title={RP-VIO: Robust Plane-based Visual-Inertial Odometry for Dynamic Environments},
  author={Karnik Ram and Chaitanya Kharyal and Sudarshan S. Harithas and K. Madhava Krishna},
  journal={2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year={2021},
  pages={9198-9205}
}
Modern visual-inertial navigation systems (VINS) are faced with a critical challenge in real-world deployment: they need to operate reliably and robustly in highly dynamic environments. Current best solutions merely filter dynamic objects as outliers based on the semantics of the object category. Such an approach does not scale as it requires semantic classifiers to encompass all possibly-moving object classes; this is hard to define, let alone deploy. On the other hand, many realworld… 

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