Control Algorithm for an Industrial Robotic Arm Using Computer Vision

Germán Buitrago Salazar; Olga Lucía Ramos; Dario Amaya

doi:10.15866/ireme.v9i2.5457

Control Algorithm for an Industrial Robotic Arm Using Computer Vision

Germán Buitrago Salazar⁽¹⁾, Olga Lucía Ramos⁽²⁾, Dario Amaya^(3*)

^(*) Corresponding author

Authors' affiliations

DOI: https://doi.org/10.15866/ireme.v9i2.5457

Abstract

This paper presents the results of applying a proposed control algorithm for a Mitsubishi industrial robot by using a computer vision system. A Kinect was placed on top of the work cell in order to sense the position of the robot. The Kinect captures the RGB-D image so it can be processed to determine the robot's position relative to a reference object or guide. The path that the robotic arm follows depends on the trajectory of the guide object and the reference values of the system. Three proportional controllers (one for each axis) were designed to stabilize the robot's position while the error signal reaches zero. The control algorithm was developed in C#, using the Ethernet port of the arm. This project allows the users to design and develop their own control strategies, without the need of using the development tools of the manufacturer.
Copyright © 2015 Praise Worthy Prize - All rights reserved.

Keywords

Computer Vision; Kinect; Ethernet Communication; Robotic Arm; Servo Control System

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References

G. Awcock, Where is the Intelligence in Machine Vision?,Fourth International Conference on Knowledge-Based Intelligent Engineering Systems & Allied Technologies, Brighton, 2000, pp 25-32 Vol 1.
http://dx.doi.org/10.1109/kes.2000.885755

A. Jaramillo, R. Jiménez and L. Ramos, Inspección de calidad para un sistema de producción industrial basado en el procesamiento de imágenes,Tecnura, Vol. 18, n. 41, pp. 76-90, 2014.
http://dx.doi.org/10.14483/udistrital.jour.tecnura.2014.3.a06

M. A. Montironi, P. Castellini, L. Stroppa, N. Paone, Adaptive autonomous positioning of a robot vision system: Application to quality control on production lines,Robotics and Computer-Integrated Manufacturing, Vol. 30, n. 5, pp. 489-498, 2014.
http://dx.doi.org/10.1016/j.rcim.2014.03.004

J. García, J. Pomarez, P. Gil and F. Torres, Seguimiento intemporal de trayectorias en la imagen basado en control visual dinámico, XXX Jornadas de Automática, Valladolid, 2009.

Tan, C., Khalil, S.N., Tamaldin, N., Karjanto, J., Nidzamuddin, M.Y., Wahidin, L.S., Chen, W., Rauterberg, G.W., A knowledge-based industrial robot selection system for manufacturing industries, (2014) International Review of Mechanical Engineering (IREME), 8 (6), pp. 1047-1051.
http://dx.doi.org/10.15866/ireme.v8i6.2752

N. Tao, Z. Hongyan, X. Peng and Y. Hironao, Vision-based virtual force guidance for tele-robotic system, Computers and Electrical Engineering, Vol. 39, no. 7, pp. 2135-2144, 2013.
http://dx.doi.org/10.1016/j.compeleceng.2013.07.016

F. Chaumette and S. Hutchinson, Visual Servo Control Part I: Basic Approaches,IEEE Robotics & Automation Magazine, Vol. 13, n. 4, pp. 82-90, 2006.
http://dx.doi.org/10.1109/mra.2006.250573

F. Chaumette and S. Hutchinson, Visual Servo Control Part II: Advanced Approaches,IEEE Robotics & Automation Magazine, Vol. 14, n. 1, pp. 109-118, 2007.
http://dx.doi.org/10.1109/mra.2007.339609

A. Traslocheros, J. Sebastian y Zuñiga, P. Pari and L. Ángel, Estudio comparativo de planificadores de trayectorias en servo control visual, XXIX Jornadas de Automática, Tarragona, 2009.

E. Mattar, Robotics Arm Visual Servo: Estimation of Arm-Space Kinematics Relations with Epipolar Geometry, Robotics Systems - Applications, Control and Programming, pp. 439-454, 2012.
http://dx.doi.org/10.5772/25605

J. Sattar, P. Giguere, G. Dudek and C. Prahacs, A visual servoing system for an aquatic swimming robot, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2005), Alberta, 2005, pp. 1483-1488.
http://dx.doi.org/10.1109/iros.2005.1545282

W. Hong-Rui, D. Hui, X. Jin-Zhuang and M. Li, Design and Implementationof a Visual Servo System, Proceedings of the Eighth International Conference on Machine Learning and Cybernetics, Baoding, 2009, pp. 2404-2408.
http://dx.doi.org/10.1109/icmlc.2009.5212155

C. Soria, F. Roberti, R. Carelli, J. Sebastián, Control Servo-Visual de un Robot Manipulador Planar Basado en Pasividad,Revista Iberoamericana de Automática e Informática Industrial, Vol. 5, n. 4, pp. 54-61, 2008.
http://dx.doi.org/10.1016/s1697-7912(08)70177-8

R. González, L. Hernández, E. Izaguirre, E. Rubio, Estrategia de control para robots manipuladores con realimentación visual y plataforma electro-neumática de 3 GDL,Ingeniería Mecánica, Vol. 14, n. 3, pp. 245-257, 2011.

Jebelli, A., Yagoub, M.C.E., Lotfi, N., Kazemi Riabi, S.H., Fuzzy-based controller design for intelligent robot arm, (2014) International Review of Mechanical Engineering (IREME), 8 (1), pp. 214-222.

Jebelli, A., Yagoub, M.C.E., Abdul Rahim, R.H.J., Kazemi, H., Design and construction of an underwater robot based fuzzy logic controller, (2013) International Review of Mechanical Engineering (IREME), 7 (1), pp. 147-153.

J. Smisek, M. Jancosek, T. Pajdla, 3D with Kinect, IEEE International Conference on Computer Vision Workshops, Barcelona, 2011, pp. 1154-1160.
http://dx.doi.org/10.1109/iccvw.2011.6130380

J. Hernández, A. Quintanilla, J. López, F. Rangel, M. Ibarra, D. Almanza, Detecting objects using color and depth segmentation with Kinect sensor, Procedia Technology, vol. 3, pp. 196-204, 2012.
http://dx.doi.org/10.1016/j.protcy.2012.03.021

M. D. Gupta, X. Jing, Bi-affinity Filter: Abilateral Type Filter for Color Images, Trends and Topics in Computer Vision, vol. 6554, pp. 27-40, 2012.
http://dx.doi.org/10.1007/978-3-642-35740-4_3

K. Konolige, P. Mihelich, Technical aspects of the Kinect device and its calibration, [Online]. Available: http://wiki.ros.org/kinect_calibration/technical#Focal_lengths. (Accessed 31 October 2014).

J. Webb, J. Ashley, Depth Image Processing, inApress (Ed.),Beginning Kinect Programming with the Microsoft Kinect SDK, (New York, Springer Science+Business, 2012, pp. 49-82).
http://dx.doi.org/10.1007/978-1-4302-4105-8_3

Mitsubishi Electric Corporation, CRnQ/CRnD Controller. Instruction Manual. Detailed explanations of functions and operations, (1st, Tokio, 2012).

B. Siciliano, l. Sciavicco, L. Villani, G. Oriolo, Visual Servoing, Robotic. Modelling, Planning and Control, (London: Springer, 2009, 440-450).

W. Weber and H. Darmstadt, Automatic Generation of the Denavit-Hartemberg Convention, 2010 41st International Symposium on and 2010 6th German Conference on Robotics (ROBOTIK) Robotics (ISR), Munich, 2010, pp. 1-7.

P. Bellandi, G. Sansoni, A. Vertuan, Development and characterization of a multi-camera 2D-vision system for enhanced performance of a drink serving robotic cell, Robotics and Computer-Integrated Manufacturing, Vol. 28, n. 1, pp. 35-49, 2012.
http://dx.doi.org/10.1016/j.rcim.2011.06.004

A. Y. Yazicioglu, B. Calli, M. Unel, Image based visual servoing using algebraic curves applied to shape alignment, 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2009) , St. Louis, 2009, pp. 5444-5449.
http://dx.doi.org/10.1109/iros.2009.5354310

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