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

  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},
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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  • O. Brock, O. Khatib
  • Computer Science
    Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)
  • 1999
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