ACTIVE SECURITY SYSTEM FOR AN INDUSTRIAL ROBOT BASED ON ARTIFICIAL VISION AND FUZZY LOGIC PRINCIPLES

B. Fevery, B. Wyns, L. Boullart, J. R. Llata García, C. Torre Ferrero

2008

Abstract

An active security system assures that interacting robots don’t collide or that a robot operating independently doesn’t hit any obstacle that is encountered in the robots workspace. In this paper, an active security system for a FANUC industrial robot is introduced. The active security problem where one robot needs to avoid a moving obstacle in its workspace is considered. An obstacle detection and localization mechanism based on stereoscopic vision methods was successfully developed. To connect the vision system, an operator’s pc and the robot environment a real-time communication is set up over Ethernet using socket messaging. We used fuzzy logic for intelligent trajectory planning. A multitask oriented robot application in the KAREL programming language of FANUC Robotics was implemented and tested.

References

  1. A. J. Baerveldt (1992). A safety system for close interaction between man and robot. Proceedings of IFAC Conference on Safety Security Reliability SAFECOMP 1992.
  2. Bischoff, A. (1999). Echtzeit Kollisionsvermeidung für einen Industrieroboter durch 3d-Sensorüberwachung.
  3. D. Ebert et al. (2005). Safe human-robot-coexistence: Emergency-stop using a high-speed vision-chip. 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages 1821-1826.
  4. Decotignie, J.-D. (2005). Ethernet-based real-time and industrial communications. IEEE, 93:1102-1117.
  5. J. Heikkilä et al. (1997). A four-step camera calibration procedure with implicit image correction. 1997 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
  6. J. R. Llata García et al. (2003). Introducción a las Técnicas de Inteligencia Artificial. Grupo de Ingeniería de Control, Departamento de Tecnología Electrónica e Ingeniería de Sistemas y Automática, Universidad de Cantabria.
  7. O. Cordon et al. (2001). Genetic fuzzy systems: Evolutionary tuning and learning of fuzzy knowledge bases. World Scientific.
  8. P. Zavlangas et al. (2000). Industrial robot navigation and obstacle avoidance employing fuzzy logic. Journal of Intelligent and Robotic Systems, 27:85-97.
  9. Torre Ferrero, C. (2002). Reconstrucción de piezas en 3d mediante técnicas basadas en visión estereoscópica.
  10. Van Moergestel, L. J. M. (2007). Computersystemen en Embedded Systemen, 2nd reviewed print. Academic Service, Den Haag.
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Paper Citation


in Harvard Style

Fevery B., Wyns B., Boullart L., R. Llata García J. and Torre Ferrero C. (2008). ACTIVE SECURITY SYSTEM FOR AN INDUSTRIAL ROBOT BASED ON ARTIFICIAL VISION AND FUZZY LOGIC PRINCIPLES . In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 978-989-8111-31-9, pages 17-23. DOI: 10.5220/0001477300170023


in Bibtex Style

@conference{icinco08,
author={B. Fevery and B. Wyns and L. Boullart and J. R. Llata García and C. Torre Ferrero},
title={ACTIVE SECURITY SYSTEM FOR AN INDUSTRIAL ROBOT BASED ON ARTIFICIAL VISION AND FUZZY LOGIC PRINCIPLES},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2008},
pages={17-23},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001477300170023},
isbn={978-989-8111-31-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - ACTIVE SECURITY SYSTEM FOR AN INDUSTRIAL ROBOT BASED ON ARTIFICIAL VISION AND FUZZY LOGIC PRINCIPLES
SN - 978-989-8111-31-9
AU - Fevery B.
AU - Wyns B.
AU - Boullart L.
AU - R. Llata García J.
AU - Torre Ferrero C.
PY - 2008
SP - 17
EP - 23
DO - 10.5220/0001477300170023