Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Indoor Point-to-Point Navigation with Deep Reinforcement Learning and
  Ultra-wideband   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 the robot. We demonstrate how
a power-efficient and low computational cost point-to-point local planner,
learnt with deep reinforcement learning (RL), combined with UWB localization
technology can constitute a robust and resilient to noise short-range guidance
system complete solution. We trained the RL agent on a simulated environment
that encapsulates the robot dynamics and task constraints and then, we tested
the learnt point-to-point navigation policies in a real setting with more than
two-hundred experimental evaluations using UWB localization. Our results show
that the computational efficient end-to-end policy learnt in plain simulation,
that directly maps low-range sensors signals to robot controls, deployed in
combination with ultra-wideband noisy localization in a real environment, can
provide a robust, scalable and at-the-edge low-cost navigation system solution.

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The categories of this paper are: bayes-an
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-ex
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The categories of this paper are: chem-ph
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The categories of this paper are: hep-th
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The categories of this paper are: solv-int
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The categories of this paper are: supr-con
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The categories of this paper are: alg-geom
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The categories of this paper are: adap-org
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The categories of this paper are: hep-lat
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The categories of this paper are: astro-ph
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The categories of this paper are: funct-an
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The categories of this paper are: econ
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The categories of this paper are: math-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: atom-ph