Deep learning in robotics: a review of recent research |
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Authors: | Harry A. Pierson Michael S. Gashler |
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Affiliation: | 1. Department of Industrial Engineering, University of Arkansas, Fayetteville, AR, USA;2. Department of Computer Science and Computer Engineering, University of Arkansas, Fayetteville, AR, USA |
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Abstract: | Advances in deep learning over the last decade have led to a flurry of research in the application of deep artificial neural networks to robotic systems, with at least 30 papers published on the subject between 2014 and the present. This review discusses the applications, benefits, and limitations of deep learning vis-à-vis physical robotic systems, using contemporary research as exemplars. It is intended to communicate recent advances to the wider robotics community and inspire additional interest in and application of deep learning in robotics. |
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Keywords: | Deep neural networks artificial intelligence human–robot interaction |
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