Journal
INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS
Volume 20, Issue 1, Pages 103-109Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/10803548.2014.11077024
Keywords
human-machine interaction; neural networks; safety control; vision-based protective devices
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This article presents the results of extensive tests of a stereovision safety system performed using real and artificial images. A vision based protective device (VBPD) analyses images from 2 cameras to calculate the position of a worker and moving parts of a machine (e.g., an industrial robot's arm). Experiments show that the stereovision safety system works properly in real time even when subjected to rapid changes in illumination level. Experiments performed with a functional model of an industrial robot indicate that this safety system can be used to detect dangerous situations at workstations equipped with a robot, in human robot cooperation. Computer-generated artificial images of a workplace simplify and accelerate testing procedures, and make it possible to compare the effectiveness of VBPDs and other protective devices at no additional cost.
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