Journal of the Korean Society of Industry Convergence (한국산업융합학회 논문집)

The Korean Society of Industry Convergence (한국산업융합학회)
권호 표지
DOI QR코드

DOI QR Code

A Study on Real Time Control of Moving Stuff Action Through Iterative Learning for Mobile-Manipulator System

  • Received : 2019.02.22
  • Accepted : 2019.06.05
  • Published : 2019.07.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study proposes a new approach to control Moving Stuff Action Through Iterative Learning robot with dual arm for smart factory. When robot moves object with dual arm, not only position of each hand but also contact force at surface of an object should be considered. However, it is not easy to determine every parameters for planning trajectory of the an object and grasping object concerning about variety compliant environment. On the other hand, human knows how to move an object gracefully by using eyes and feel of hands which means that robot could learn position and force from human demonstration so that robot can use learned task at variety case. This paper suggest a way how to learn dynamic equation which concern about both of position and path.

Keywords

SOOOB6_2019_v22n4_415_f0001.png 이미지

Fig. 1 Modeling of 5-DOF robot

SOOOB6_2019_v22n4_415_f0003.png 이미지

Fig. 2 Structure of 5-DOF Dual-arm robot

SOOOB6_2019_v22n4_415_f0004.png 이미지

Fig. 3 The basic structure of controller

SOOOB6_2019_v22n4_415_f0005.png 이미지

Fig. 4 Force and path in manipulating both hands

SOOOB6_2019_v22n4_415_f0006.png 이미지

Fig. 5 Coordinate of Coordinate of dual-arm for handling of objects

SOOOB6_2019_v22n4_415_f0007.png 이미지

Fig. 6 Name of each joint

SOOOB6_2019_v22n4_415_f0008.png 이미지

Fig. 7 Manipulability ellipsoid in xy, xz, yz dimension for box

SOOOB6_2019_v22n4_415_f0009.png 이미지

Fig. 8 Manipulability ellipsoid in xy, xz, yz dimension for ball

SOOOB6_2019_v22n4_415_f0010.png 이미지

Fig. 9 Experimental result graph of learning control

SOOOB6_2019_v22n4_415_f0011.png 이미지

Fig. 10 Learning scene of dual-arm robot

SOOOB6_2019_v22n4_415_f0012.png 이미지

Fig. 11 Experimental results of learning control

Table 1. D-H parameter table(1)

SOOOB6_2019_v22n4_415_t0001.png 이미지

References

  1. Y. C. Lee, S. J. Lim, S. W. Hwang and C. S. Han, "Object grasp method of the service robot using the robot vision," Conference on Korean Society for Precision Engineering, vol. 3, pp. 7-8, 2008.
  2. N. Vahrenkamp, A. Barski, T. Asfour, and R. Dillmann, "Planning and execution of grasping motions on a humanoid robot," IEEERAS International Conference on Humanoid Robots, 2009.
  3. C. Eitner, Y. Mori, K. Okada, and M. Inaba, "Task and vision based online manipulator trajectory generation for a humanoid robot," Humanoid Robots, 2008. Humanoids 2008. 8th IEEE-RAS International Conference, pp. 293-298, Dec. 2008.
  4. C. Ott, O. Eiberger, W. Friedl, B. Bauml, U. Hillenbrand, C. Borst, A. Albu-Schaffer, B. Brunner, H. Hirschmuller, S. Kielhofer, R. Konietschke, M. Suppa, T. Wimbock, F. Zacharias, and G. Hirzinger, "A humanoid two-arm system for dexterous manipulation," IEEE-RAS Int. Conf. on Humanoid Robots, pp. 276-283, Dec, 2006.
  5. A. Miller, S. Knoop, H. Christensen, and P. Allen, "Automatic grasp planning using shape primitives", IEEE International Conference on Robotics and Automation, vol. 2, pp.1824-1829, 2003.
  6. X. Zhixing, A. Kasper, J. M. Zoellner, R. Dillmann, "An automatic grasp planning system for service robots," 14th International Conference on Advanced Robotics, Munich, Germany, June, 2009.
  7. N. Vahrenkamp, D. Berenson, T. Asfour, J. Kuffner, and R. Dillmann, "Humanoid motion planning for dual-arm manipulation and re-grasping tasks," Intelligent Robots and Systems, IROS, Oct, 2009.