Virtual Bin Picking - A Generic Framework to Overcome the Bin Picking Complexity by the Use of a Virtual Environment

Adrian Schyja, Bernd Kuhlenkötter

Abstract

Bin Picking is a very popular topic in the scope of robotic applications. For many years, R&D facilities as well as the industry work on Bin Picking solutions. However, it is challenging to bring such systems into industrial shop floors mainly due to the design and economical calculability accompanied by the acceptance of stable Bin Picking systems without any downtime. This paper presents a versatile interface-based framework for the planning, designing and in particular for the simulation of various Bin Picking applications. For that, the term ’Virtual Bin Picking’ has been introduced, which associates the simulation of Bin Picking scenarios in a virtual environment without the need for hardware components. Thus, it enables the design of Bin Picking work cells and it allows to predict the quality of such cells in an early virtual commissioning stage.

References

  1. Bartelt, M., Schyja, A., Kuhlenktter, B., and Benkner, T. (2013). Interdisziplinre zusammenarbeit in einer heterogenen cax-software-landschaft. PRODUCTIVITY Management, 3/2013.
  2. B öhnke, K. (2007). Object localization in range data for robotic bin picking. In International Conference on Automation Science and Engineering, CASE, pages 572-577.
  3. , B. (2011). Autonome Roboter mit sensorbasierter Bahnplanung. Industrie Management, 1:21-24.
  4. Denavit, J. and Hartenberg, R. S. (1955). A kinematic notation for lower-pair mechanisms based on matrices. Transactions of the ASME. Journal of Applied Mechanics, 22:215-221.
  5. Diankov, R. (2010). Automated Construction of Robotic Manipulation Programs. PhD thesis, Carnegie Mellon University, Robotics Institute.
  6. Drumwright, E., Hsu, J., Koenig, N., and Shell, D. (2010). Extending open dynamics engine for robotics simulation. In Proceedings of the Second International Conference on Simulation, Modeling, and Programming for Autonomous robots, SIMPAR'10, pages 38- 50, Berlin, Heidelberg. Springer-Verlag.
  7. Francois, C., Hebert, M., and Ikeuchi, K. (1991). A threefinger gripper for manipulation in unstructured environments. In IEEE International Conference on Robotics and Automation.
  8. Ghita, O. and Whelan, P. F. (2003). A bin picking system based on depth from defocus. Machine Vision and Applications, 13(4):234-244.
  9. Ghita, O. and Whelan, P. F. (2008). A systems engineering approach to robotic bin picking. In Bhatti, A., editor, Stereo Vision, chapter 4, pages 59-72. InTech.
  10. Gottschalk, S., Lin, M. C., and Manocha, D. (1996). Obbtree: a hierarchical structure for rapid interference detection. In Proceedings of the 23rd annual conference on Computer graphics and interactive techniques, SIGGRAPH 7896, pages 171-180, New York, NY, USA. ACM.
  11. Johnson, M. (2013). Flexible Path Planning For BinPicking Applications. Masterarbeit, Technische Universitt Dortmund.
  12. Kirkegaard, J. and Moeslund, T. B. (2006). Bin-picking based on harmonic shape contexts and graph-based matching. In 18th International Conference on Pattern Recognition, volume 2 of ICPR, pages 581-584.
  13. Kneupner, K. (2004). Entwicklung eines Programmier- und Steuerungskonzepts für Robotersysteme auf der Basis eines Umweltmodells. PhD thesis, TU Dortmund University. ISBN 3-18-338920-7 VDI Verlag, Dü sseldorf.
  14. Kuhlenkö tter, B., Hypki, A., Schyja, A., and Miegel, V. (2010). Robot Workcell Simulation with AutomationML Support - An Element of the CAx-Tool Chain in Industrial Automation. In Proceedings for the joint conference of ISR 2010 (41st International Symposium on Robotics) und ROBOTIK 2010 (6th German Conference on Robotics). VDE Verlag GmbH.
  15. Leonard, S., Chan, A., Little, J. J., and Croft, E. A. (2007). Robust motion generation for vision-guided robot bin-picking. ASME Conference Proceedings, 2007(43033):651-658.
  16. Martinez, A. and Fernndez, E. (2013). Learning ROS for Robotics Programming. Packt Publishing.
  17. McKee, J. W. and Aggarwal, J. K. (1977). Computer recognition of partial views of curved objects. IEEE Transactions on Computers, 26(8):790-800.
  18. Palzkill, M., Ledermann, T., and Verl, A. (2010). Anticipation-preprocessing for object pose detection. In 41st International Symposium on Robotics, ISR 2010, pages 440-445.
  19. Pochyly, A., Kubela, T., Singule, V., and Cihak, P. (2012). 3d vision systems for industrial bin-picking applications. In 15th International Conference on Mechatronics, MECHATRONIKA, pages 1-6. IEEE.
  20. Project Group 510 (2008). Entwicklung einer echtzeitfhigen Kollisionsbehandlung fr die physikalische Simulation in virtuellen Umgebungen. Project Group, TU Dortmund University, Computer Science VII.
  21. RRS-Owners (1991). Realistic Robot Simulation Interface Specification, version 1.3. Technical report, Fraunhofer-Institut fü r Produktionsanlagen und Konstruktionstechnik (IPK), Berlin.
  22. Schraft, R. D. and Ledermann, T. (2003). Intelligent picking of chaotically stored objects. Assembly Automation, 23(1):38-42.
  23. Schyja, A., Bartelt, M., and Kuhlenkötter, B. (2014). From conception phase up to virtual verification using automationml. In 5th CATS 2014 - CIRP Conference on Assembly Systems and Technologies. Status: accepted.
  24. Schyja, A., Hypki, A., and Kuhlenkö tter, B. (2012). A modular and extensible framework for real and virtual bin-picking environments. In 2012 IEEE International Conference on Robotics and Automation (ICRA), pages 5246 -5251.
  25. Tsuboi, Y. and Inoue, T. (1976). Robot assembly system using tv camera. Industrial Robot: An International Journal, 3(2):67-72.
  26. Wurdemann, H. A., Aminzadeh, V., Cui, L., and Dai, J. S. (2011). Feature extraction of non-uniform food products using rgb and rgb-d data combined with shape models. In International Conference on Robotics and Biomimetics, ROBIO, pages 1652-1657. IEEE.
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Paper Citation


in Harvard Style

Schyja A. and Kuhlenkötter B. (2014). Virtual Bin Picking - A Generic Framework to Overcome the Bin Picking Complexity by the Use of a Virtual Environment . In Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-038-3, pages 133-140. DOI: 10.5220/0005011401330140


in Bibtex Style

@conference{simultech14,
author={Adrian Schyja and Bernd Kuhlenkötter},
title={Virtual Bin Picking - A Generic Framework to Overcome the Bin Picking Complexity by the Use of a Virtual Environment},
booktitle={Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2014},
pages={133-140},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005011401330140},
isbn={978-989-758-038-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Virtual Bin Picking - A Generic Framework to Overcome the Bin Picking Complexity by the Use of a Virtual Environment
SN - 978-989-758-038-3
AU - Schyja A.
AU - Kuhlenkötter B.
PY - 2014
SP - 133
EP - 140
DO - 10.5220/0005011401330140