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Stereovision Safety System for Identifying Workers’ Presence: Results of Tests

Grabowski A., Jankowski J., Dźwiarek M., Kosiński R. A.

International Journal of Occupational Safety and Ergonomics

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2014

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Vol. 20, No. 1

103--109

EN

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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Układ sieci neuronowych do analizy sytuacji niebezpiecznych na zautomatyzowanym stanowisku pracy

Kosiński R. A., Siemiątkowska B.

Pomiary Automatyka Robotyka

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1999

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R. 3, nr 7-8

17-20

PL

Przedstawiono zastosowanie układu komórkowych sieci neuronowych do analizy sytuacji niebezpiecznych na zautomatyzowanym stanowisku pracy. Obrazy z kamery telewizyjnej są przekazywane do układu sieci neuronowych. Czas reakcji systemu jest dostatecznie krótki, aby system bezpieczeństwa mógł pracować w czasie rzeczywistym.

EN

An application of neural network in robotics is presented. The task for the systems is to protect the work of an industrial robot. The images of the camera are analyzed using hybrid system of Cellular Neural Networks (CNN). The time of reaction of CNN is small enough towork in a real time.

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Artificial Neural Networks - Modern Systems for Safety Control

Kosiński R. A., Kozłowski C.

International Journal of Occupational Safety and Ergonomics

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1998

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Vol. 4, No. 3

317--332

EN

A short review of the applications of artificial neural networks in different fields of industry with a description of their main properties is made. Such systems have specific properties typical for the human brain, which can decide on the superiority of artificial neural networks over standard control systems. Basic types of such networks as well as their principles of operation and successful applications are described. The application of artificial neural networks in safety engineering is discussed with stress on their special properties, which are necessary in safety critical systems.