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Automatic Learning Improves Human-Robot Interaction in Productive Environments: A Review
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Author(s): Mauricio Andres Zamora Hernandez (University of Costa Rica, Costa Rica), Eldon Caldwell Marin (University of Costa Rica, Costa Rica), Jose Garcia-Rodriguez (University of Alicante, Spain), Jorge Azorin-Lopez (University of Alicante, Spain)and Miguel Cazorla (University of Alicante, Spain)
Copyright: 2018
Pages: 11
Source title:
Computer Vision: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-5225-5204-8.ch087
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Abstract
In the creation of new industries, products and services -- all of which are advances of the Fourth Industrial Revolution -- the human-robot interaction that includes automatic learning and computer vision are elements to consider since they promote collaborative environments between people and robots. The use of machine learning and computer vision provides the tools needed to increase productivity and minimizes delivery reaction times by assisting in the optimization of complex production planning processes. This review of the state of the art presents the main trends that seek to improve human-robot interaction in productive environments, and identifies challenges in research as well as in industrial - technological development in this topic. In addition, this review offers a proposal on the needs of use of artificial intelligence in all processes of industry 4.0 as a crucial linking element among humans, robots, intelligent and traditional machines; as well as a mechanism for quality control and occupational safety.
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