Published on Wed Apr 18 2018
The limits and potentials of deep learning for robotics
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The application of deep learning in robotics leads to very specific problems
and research questions that are typically not addressed by the computer vision
and machine learning communities. In this paper we discuss a number of
robotics-specific learning, reasoning, and embodiment challenges for deep
learning. We explain the need for better evaluation metrics, highlight the
importance and unique challenges for deep robotic learning in simulation, and
explore the spectrum between purely data-driven and model-driven approaches. We
hope this paper provides a motivating overview of important research directions
to overcome the current limitations, and help fulfill the promising potentials
of deep learning in robotics.