Simulation of Position Based Visual Control and Performance Tests of 6R Robot

Document Type : Research Article

Authors

Abstract

This paper presents simulation and experimental results of position-based visual servoing control process of a 6R robot using 2 fixed cameras. This method has the ability to deal with real time changes in the relative position of the target-object with respect to robot. Also, greater accuracy and independency of servo control structure from the target pose coordinates are the additional advantages of this method. Forward and inverse kinematics of 6R robot have been simulated then simulation of image processing, object recognition and pose estimation of the end effector as well as target-object in Cartesian space and visual control of robot have been prescribed. Performance tests of the 6R robot with two cameras have been simulated. Finally, analysis of error and test data has been carried out according to ISO9283, ANSI-RIA R15.05-2 standards and statistical toolbox of MATLAB. Experimental results obtained from actual implementation of visual control and tests of 6R robot in lab are presented and used to validate simulation tests.

Keywords

References

  1. G. Lopez, C. Sagues and J.J. Guerrero, “Homography-Based Visual Control of Nonholonomic Vehicles”, IEEE Int. Conference on Robotics and Automation, Italy, April 2007. pp. 1703- 1708
  2. A. Gilbert , M. Giles, G. Flachs , R. Rogers, and H. Yee . “A Real Time Video Tracking Systems.” IEEE , Trans. Pattern Anal. Mech. Intel. 2(1), pp. 47 – 56 Jan. 1983 
  3. A. C. Sanderson, L. E. Weiss, and C. P. Neuman. Dynamic visual servo control of robots: an adaptive image-based approach. Proc. IEEE, pages 662.667, 1985.
  4. M Saedan and M H Ang Jr, “3D Vision-Based Control of an Industrial Robot”, Proceedings of the IASTED International Conference on Robotics and Applications, Nov 19-22, 2001, Florida, USA, pp. 152-157.
  5. S. Skaar,W. Brockman, and R. Hanson. Camera-space manipulation. Int. J. Robot. Res., 6(4):20.32, 1987.
  6. J. T. Feddema, C. S. G. Lee, and O. R. Mitchell. Weighted selection of image features for resolved rate visual feedback control. IEEE Trans. Robot. Autom. 7(1):31.47, February 1991.
  7. F. Chaumette, P. Rives, and B. Espiau. Positioning of a robot with respect to an object, tracking it and estimating its velocity by visual servoing. In Proc. IEEE Int. Conf. Robotics and Automation, pages 2248.2253, 1991.
  1. H. Hashimoto, T. Kimoto, T. Ebin, “Manipulator Control with Image Based Visual Servoing” In Proc. IEEE, Conf. Robotics and Automation, pp. 2267 – 2272, 1991.
  2. M. H. Korayem, N. Shiehbeiki, and T. Khanali, “Design, Manufacturing and Experimental Tests of Prismatic Robot for Assembly Line”, International J. of AMT, Vol. 29, No.3-4, pp. 379-388, 2006.
  3. M. H. Korayem, K. Khoshhal, A. Aliakbarpour, “Vision Based Robot Simulation and Experiment for Performance Tests of Robot“, International J. of AMT, Vol. 25, No. 11-12, pp. 1218-1231, 2005.
  4. American National Standard for Industrial Robots and Robot Systems Path-Related and Dynamic Performance Characteristics Evaluation. ANSI/RIA R15.05-2. 2002.
  5. ISO9283, “Manipulating Industrial Robots Performance Criteria & Related Test Methods”, 1998.
  6. D. Koichiro, S. Hironari and U. Shun, “A Goal Oriented Just-In-Time Visual Servoing for Ball Catching Robot Arm”, IEEE Int. Conference on Robotics and Automation, France, Sep. 2008. pp. 3034- 3039.

Files

Share

How to cite

Statistics