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Editorial

Machine Learning Techniques for Assistive Robotics

Institute for Computing Research, University of Alicante, 03690 Alicante, Spain
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Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Electronics 2020, 9(5), 821; https://doi.org/10.3390/electronics9050821
Received: 4 May 2020 / Accepted: 14 May 2020 / Published: 16 May 2020
(This article belongs to the Special Issue Machine Learning Techniques for Assistive Robotics)
Note: In lieu of an abstract, this is an excerpt from the first page.

Assistive robots are a category of robots that share their area of work and interact with humans [...] View Full-Text
MDPI and ACS Style

Martinez-Martin, E.; Cazorla, M.; Orts-Escolano, S. Machine Learning Techniques for Assistive Robotics. Electronics 2020, 9, 821. https://doi.org/10.3390/electronics9050821

AMA Style

Martinez-Martin E, Cazorla M, Orts-Escolano S. Machine Learning Techniques for Assistive Robotics. Electronics. 2020; 9(5):821. https://doi.org/10.3390/electronics9050821

Chicago/Turabian Style

Martinez-Martin, Ester, Miguel Cazorla, and Sergio Orts-Escolano. 2020. "Machine Learning Techniques for Assistive Robotics" Electronics 9, no. 5: 821. https://doi.org/10.3390/electronics9050821

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