Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 5

Proceedings of the 2015 Federated Conference on Computer Science and Information Systems

Robotic Arm Detection in Space with Image Recognition Made in Linux with the Hough Circles Method

,

DOI: http://dx.doi.org/10.15439/2015F10

Citation: Proceedings of the 2015 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 5, pages 895900 ()

Full text

Abstract. This paper presents a method to recognize a robotic arm in space using the Hough circles method. The robotic arm has colored bottle stoppers glued at the joints, which are recognized with color filtering. After this step, the biggest colored spot is detected and marked using the Hough circle method. The joints are numbered, this way each joint's position is known. The joints can be united with lines and this way a skeleton of the robotic arm can be drawn which can be loaded in a PC to create a control application.

References

  1. W. G. Hao, Y. Y. Leck, L. C. Hun, “6-DOF PC-Based Robotic Arm (PC-ROBOARM) with efficient trajectory planning and speed control,” 4th International Conference On Mechatronics, Kuala Lumpur, 2011, pp. 1–7, http://dx.doi.org/10.1109/ICOM.2011.5937171.
  2. W. Yang, J. H. Bae, Y. Oh, N. Y. Chong, B. J. You, S. R. Oh, “CPG based self-adapting multi-DOF robotic arm control,” International Conference on Intelligent Robots and Systems, Taipei, 2010, pp. 4236–4243, http://dx.doi.org/10.1109/IROS.2010.5651377.
  3. E. Oyama, T. Maeda, J. Q. Gan, E. M. Rosales, K. F. MacDorman, S. Tachi, A. Agah, “Inverse kinematics learning for robotic arms with fewer degrees of freedom by modular neural network systems,” International Conference on Intelligent Robots and Systems, 2005, pp. 1791–1798, http://dx.doi.org/10.1109/IROS.2005.1545084.
  4. N. Ahuja, U. S. Banerjee, V. A. Darbhe, T. N. Mapara, A. D. Matkar, R.K. Nirmal, S. Balagopalan, “Computer controlled robotic arm,” 16th IEEE Symposium on Computer-Based Medical Systems, New York, 2003, pp. 361–366, http://dx.doi.org/10.1109/CBMS.2003.1212815.
  5. M. H. Liyanage, N. Krouglicof, R. Gosine, “Design and control of a high performance SCARA type robotic arm with rotary hydraulic actuators,” Canadian Conference on Electrical and Computer Engineering, St. John's, CA, 2009, pp. 827–832, http://dx.doi.org/10.1109/CCECE.2009.5090244.
  6. M. Mariappan, T. Ganesan, M. Iftikhar, V. Ramu, B. Khoo, “A design methodology of a flexible robotic arm vision system for OTOROB,” International Conference on Mechanical and Electrical Technology, Singapore, 2010, pp. 161–164, http://dx.doi.org/10.1109/ICMET.2010.5598341.
  7. H. Guo-Shing, C. Xi-Sheng, C. Chung-Liang, “Development of dual robotic arm system based on binocular vision,” International Automatic Control Conference, Nantou, 2013, pp. 97–102, http://dx.doi.org/10.1109/CACS.2013.6734114
  8. R. Szabó, A. Gontean, “Controlling a Robotic Arm in the 3D Space with Stereo Vision,” 21th Telecommunications Forum, Belgrade, 2013, pp. 916–919, http://dx.doi.org/10.1109/TELFOR.2013.6716380.
  9. R. Szabó, A. Gontean, “Robotic arm control in 3D space using stereo distance calculation,” International Conference on Development and Application Systems, Suceava, 2014, pp. 50–56, http://dx.doi.org/10.1109/DAAS.2014.6842426.
  10. R. Szabó, A. Gontean, “Remotely Commanding the Lynxmotion AL5 Type Robotic Arms,” 21th Telecommunications Forum, Belgrade, 2013, pp. 889–892, http://dx.doi.org/10.1109/TELFOR.2013.6716373.
  11. R. Szabó, A. Gontean, “Creating a Programming Language for the AL5 Type Robotic Arms,” 36th International Conference on Telecommunications and Signal Processing, Rome, 2013, pp. 62–65. [Online]. Available: http://dx.doi.org/10.1109/TSP.2013.6613892.
  12. R. Szabó, A. Gontean, “Full 3D Robotic Arm Control with Stereo Cameras Made in LabVIEW,” Federated Conference on Computer Science and Information Systems, Kraków, 2013, pp. 37–42.
  13. R. Szabo, A. Gontean, “Robotic Arm Control with Stereo Vision Made in LabWindows/CVI,” 37th International Conference on Telecommunications and Signal Processing, Berlin, 2014, pp. 635– 639.
  14. M. Seelinger, E. Gonzalez-Galvan, M. Robinson, S. Skaar, “Towards a robotic plasma spraying operation using vision,” IEEE Robotics & Automation Magazine, vol. 5, issue 4, 1998, pp. 33–38, 49, http://dx.doi.org/10.1109/100.740463.
  15. R. Kelly, R. Carelli, O. Nasisi, B. Kuchen, F. Reyes, “Stable visual servoing of camera-in-hand robotic systems,” IEEE/ASME Transactions on Mechatronics, vol. 5, issue 1, 2000, pp. 39–48, http://dx.doi.org/10.1109/3516.828588.
  16. V. Lippiello, F. Ruggiero, B. Siciliano, L. Villani, “Visual Grasp Planning for Unknown Objects Using a Multifingered Robotic Hand”, IEEE/ASME Transactions on Mechatronics, vol. 18, issue 3, 2013, pp. 1050–1059, http://dx.doi.org/10.1109/TMECH.2012.2195500.
  17. M. Kazemi, K. K. Gupta, M. Mehrandezh, “Randomized Kinodynamic Planning for Robust Visual Servoing”, IEEE Transactions on Robotics, vol. 29, issue 5, 2013, pp. 1197–1211, http://dx.doi.org/10.1109/TRO.2013.2264865.
  18. R. T. Fomena, O. Tahri, F. Chaumette, “Distance-Based and Orientation-Based Visual Servoing From Three Points”, IEEE Transactions on Robotics, vol. 27, issue 2, 2011, pp. 256–267, http://dx.doi.org/10.1109/TRO.2011.2104431.
  19. N. C. Orger, T. B. Karyot, “A symmetrical robotic arm design approach with stereo-vision ability for CubeSats,” 6th International Conference on Recent Advances in Space Technologies, Istanbul, 2013, pp. 961–965, http://dx.doi.org/10.1109/RAST.2013.6581353.
  20. F. Medina, B. Nono, H. Banda, A. Rosales, “Classification of Solid Objects with Defined Shapes Using Stereoscopic Vision and a Robotic Arm,” Andean Region International Conference, Cuenca, 2012, pp. 226, http://dx.doi.org/10.1109/Andescon.2012.71.
  21. M. Puheim, M. Bundzel, L. Madarasz, “Forward control of robotic arm using the information from stereo-vision tracking system,” 14th International Symposium on Computational Intelligence and Informatics, Budapest, 2013, pp. 57–62, http://dx.doi.org/10.1109/CINTI.2013.6705259.
  22. T. P. Cabre, M. T. Cairol, D. F. Calafell, M. T. Ribes, J. P. Roca, “Project-Based Learning Example: Controlling an Educational Robotic Arm With Computer Vision,” IEEE Revista Iberoamericana de Tecnologias del Aprendizaje, vol. 8, issue 3, 2013, pp. 135–142, http://dx.doi.org/10.1109/RITA.2013.2273114.
  23. G. S. Gupta, S. C. Mukhopadhyay, M. Finnie, “WiFi-based control of a robotic arm with remote vision,” Instrumentation and Measurement Technology Conference, Singapore, 2009, pp. 557–562, http://dx.doi.org/10.1109/IMTC.2009.5168512.
  24. L. Haoting, W. Wei, G. Feng, L. Zhaoyang, S. Yuan, L. Zhenlin, “Development of Space Photographic Robotic Arm based on binocular vision servo,” Sixth International Conference on Advanced Computational Intelligence, Hangzhou, 2013, pp. 345–349, http://dx.doi.org/10.1109/ICACI.2013.6748528.
  25. C. Wen-Chung, C. Chih-Wei, “Automatic Mobile Robotic Manipulation with Active Eye-to-Hand Binocular Vision,” 33rd Annual Conference of the IEEE Industrial Electronics Society, Taipei, 2007, pp. 2944–2949, http://dx.doi.org/10.1109/IECON.2007.4460000.
  26. P. C. Nunnally, J. M. Weiss, “An inexpensive robot arm for computer vision applications,” Energy and Information Technologies in the Southeast, Columbia, vol. 1, 10989, pp. 1–6, http://dx.doi.org/10.1109/SECON.1989.132303.
  27. T. Kizaki, A. Namiki, “Two ball juggling with high-speed hand-arm and high-speed vision system,” IEEE International Conference on Robotics and Automation, Saint Paul, MN, 2012, pp. 1372–1377, http://dx.doi.org/10.1109/ICRA.2012.6225090.