An Approach for Integration of Industrial Robot with Vision System and Simulation Software
Utilization of various sensors has made it possible to
extend capabilities of industrial robots. Among these are vision
sensors that are used for providing visual information to assist robot
controllers. This paper presents a method of integrating a vision
system and a simulation program with an industrial robot. The vision
system is employed to detect a target object and compute its location
in the robot environment. Then, the target object-s information is sent
to the robot controller via parallel communication port. The robot
controller uses the extracted object information and the simulation
program to control the robot arm for approaching, grasping and
relocating the object. This paper presents technical details of system
components and describes the methodology used for this integration.
It also provides a case study to prove the validity of the methodology
developed.
[1] W. Dae Hee, L. Young Jae, S. Sangkyung, and K. Taesam, "Integration
of vision based SLAM and nonlinear filter for simple mobile robot
navigation," in Aerospace and Electronics Conference. 2008 NAECON
IEEE National, pp. 373-378.
[2] M. Marron, M. A. Sotelo, J. C. Garcia, D. Fernandez, and I. Parra, "3Dvisual
detection of multiple objects and structural features in complex
and dynamic indoor environments," in IEEE Industrial Electronics. 32nd
Annual Conference on 2006 IECON, pp. 3373-3378.
[3] J. Wang, T. I. Niekerk, D. G. Hattingh, and T. Hua, "Knowledge-based
robot vision system for automated part handling," South African (2008)
Journal of Industrial Engineering, 19(1), 119-119-130.
[4] S. Zhao, C. Chen, C. Liu, and M. Liu, "Algorithm of location of chessrobot
system based on computer vision," Control and Decision
Conference. 2008 CCDC.
[5] B. Muhammedali, M. Z. Abdullah, and M. N. M. Azemi, "Food
handling and packaging using computer vision and robot." Computer
Graphics, Imaging and Visualization, 2004,. Proceedings. International
Conference.
[6] Lab-Volt Ltd., Introduction to robotics manual, 1st edition ISBN 2-
89289-721-1, Canada, 2004, pp. 1-2-1-3.
[7] Intel Inc., the OpenCV computer vision library. Available in:
http://www.intel.com/research/mrl/research/opencv
[8] OpenSURF. Chris Evans development. Available in:
http://www.chrisevansdev.com/computer-vision-opensurf.html
[9] R. Brunelli, Template Matching Techniques in Computer Vision: Theory
and Practice, Wiley, ISBN 978-0-470-51706-2, 2009.
[10] Z. Qingjie, D. Hongbin, Z. Wenyao, and M. Aixia, "Selection of image
features for robot vision system," in Automation and Logistics. 2007
IEEE International Conference, pp. 2622-2626.
[1] W. Dae Hee, L. Young Jae, S. Sangkyung, and K. Taesam, "Integration
of vision based SLAM and nonlinear filter for simple mobile robot
navigation," in Aerospace and Electronics Conference. 2008 NAECON
IEEE National, pp. 373-378.
[2] M. Marron, M. A. Sotelo, J. C. Garcia, D. Fernandez, and I. Parra, "3Dvisual
detection of multiple objects and structural features in complex
and dynamic indoor environments," in IEEE Industrial Electronics. 32nd
Annual Conference on 2006 IECON, pp. 3373-3378.
[3] J. Wang, T. I. Niekerk, D. G. Hattingh, and T. Hua, "Knowledge-based
robot vision system for automated part handling," South African (2008)
Journal of Industrial Engineering, 19(1), 119-119-130.
[4] S. Zhao, C. Chen, C. Liu, and M. Liu, "Algorithm of location of chessrobot
system based on computer vision," Control and Decision
Conference. 2008 CCDC.
[5] B. Muhammedali, M. Z. Abdullah, and M. N. M. Azemi, "Food
handling and packaging using computer vision and robot." Computer
Graphics, Imaging and Visualization, 2004,. Proceedings. International
Conference.
[6] Lab-Volt Ltd., Introduction to robotics manual, 1st edition ISBN 2-
89289-721-1, Canada, 2004, pp. 1-2-1-3.
[7] Intel Inc., the OpenCV computer vision library. Available in:
http://www.intel.com/research/mrl/research/opencv
[8] OpenSURF. Chris Evans development. Available in:
http://www.chrisevansdev.com/computer-vision-opensurf.html
[9] R. Brunelli, Template Matching Techniques in Computer Vision: Theory
and Practice, Wiley, ISBN 978-0-470-51706-2, 2009.
[10] Z. Qingjie, D. Hongbin, Z. Wenyao, and M. Aixia, "Selection of image
features for robot vision system," in Automation and Logistics. 2007
IEEE International Conference, pp. 2622-2626.
@article{"International Journal of Information, Control and Computer Sciences:57987", author = "Ahmed Sh. Khusheef and Ganesh Kothapalli and Majid Tolouei-Rad", title = "An Approach for Integration of Industrial Robot with Vision System and Simulation Software", abstract = "Utilization of various sensors has made it possible to
extend capabilities of industrial robots. Among these are vision
sensors that are used for providing visual information to assist robot
controllers. This paper presents a method of integrating a vision
system and a simulation program with an industrial robot. The vision
system is employed to detect a target object and compute its location
in the robot environment. Then, the target object-s information is sent
to the robot controller via parallel communication port. The robot
controller uses the extracted object information and the simulation
program to control the robot arm for approaching, grasping and
relocating the object. This paper presents technical details of system
components and describes the methodology used for this integration.
It also provides a case study to prove the validity of the methodology
developed.", keywords = "industrial robot, integration, simulation, vision
system", volume = "5", number = "10", pages = "1126-6", }