Deep Auxiliary Learning for Visual Localization and Odometry

@article{Valada2018DeepAL,
  title={Deep Auxiliary Learning for Visual Localization and Odometry},
  author={Abhinav Valada and Noha Radwan and Wolfram Burgard},
  journal={2018 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2018},
  pages={6939-6946}
}
Localization is an indispensable component of a robot's autonomy stack that enables it to determine where it is in the environment, essentially making it a precursor for any action execution or planning. Although convolutional neural networks have shown promising results for visual localization, they are still grossly outperformed by state-of-the-art local feature-based techniques. In this work, we propose VLocNet, a new convolutional neural network architecture for 6-DoF global pose regression… CONTINUE READING
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