Indoor Point-to-Point Navigation with Deep Reinforcement Learning and Ultra-wideband

@inproceedings{Sutera2020IndoorPN,
  title={Indoor Point-to-Point Navigation with Deep Reinforcement Learning and Ultra-wideband},
  author={Enrico Sutera and Vittorio Mazzia and Francesco Salvetti and Giovanni Fantin and Marcello Chiaberge},
  booktitle={International Conference on Agents and Artificial Intelligence},
  year={2020}
}
Indoor autonomous navigation requires a precise and accurate localization system able to guide robots through cluttered, unstructured and dynamic environments. Ultra-wideband (UWB) technology, as an indoor positioning system, offers precise localization and tracking, but moving obstacles and non-line-of-sight occurrences can generate noisy and unreliable signals. That, combined with sensors noise, unmodeled dynamics and environment changes can result in a failure of the guidance algorithm of… 

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