Quasi-Minimum Time Trajectory Planning Method of Robot Arm with Electromagnetic Attraction Hand Using Genetic Algorithm and Experiments

Yusuke Mutsuura; Hiroyuki Kojima; Yuuichi Takeuchi; Hiroki Saitou

doi:10.20965/ijat.2009.p0099

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IJAT Vol.3 No.1 pp. 99-106

doi: 10.20965/ijat.2009.p0099

(2009)

Paper:

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Quasi-Minimum Time Trajectory Planning Method of Robot Arm with Electromagnetic Attraction Hand Using Genetic Algorithm and Experiments

Yusuke Mutsuura^, Hiroyuki Kojima^, Yuuichi Takeuchi^*, and Hiroki Saitou^**

^*Department of Mechanical System Engineering, Graduate School of Engineering, Gunma University
1-5-1 Tenjincho, Kiryu, Gunma 376-8515, Japan

^**Tokyo Rhythm Watch Corporation
1-299-12 Kitabukuromachi, Omiya, Saitama 330-9551, Japan

Received:

October 21, 2008

Accepted:

November 10, 2008

Published:

January 5, 2009

Keywords:

electromagnetic attraction hand, quasi-minimum time trajectory planning, electromagnetic attraction transfer control, genetic algorithm

Abstract

In this study, a quasi-minimum time trajectory planning method for the electromagnetic attraction transfer control of a magnetic object by use of a three-link robot arm with an electromagnetic attraction hand is proposed. The three joints of the robot arm are driven with reduction gears and DC motors. In the trajectory planning using a genetic algorithm, the magnetic object is assumed to be transferred along a linear trajectory, and the trajectory of the robot arm is formulated by use of a chromosome consisting of two genes. Then, the fitness function of the genetic algorithm for a quasi-minimum time trajectory planning is defined using two kinds of the constraint conditions as to the allowable maximum moment applied to the magnetic object and the allowable maximum DC motor torque. Furthermore, the numerical calculations and the experiments have been carried out, and the usefulness of the present quasi-minimum time trajectory planning method is confirmed theoretically and experimentally.

Cite this article as:

Y. Mutsuura, H. Kojima, Y. Takeuchi, and H. Saitou, “Quasi-Minimum Time Trajectory Planning Method of Robot Arm with Electromagnetic Attraction Hand Using Genetic Algorithm and Experiments,” Int. J. Automation Technol., Vol.3 No.1, pp. 99-106, 2009.

Data files:

References

[1] C. S. Lin, P. R. Chang, and J. Y. S. Luh, “Formulation and optimization of cubic polynomial joint trajectories for industrial robots,” IEEE Transactions on Automatic Control, Vol.AC-28, No.12, pp. 1066-1074, 1983.
[2] B. Tondu and S. A. Bazaz, “The three-cubic method: an optimal online robot joint trajectory generator under velocity,” acceleration, and wandering constraints, The Int. Journal of Robotics Research, Vol.18, No.9, pp. 893-901, 1999.
[3] T. Izumi, “Path Planning for Saving Energy of a Manipulator in PTP Motions,” Journal of the Robotics Society of Japan, Vol.18, No.7, pp. 972-978, 2000.
[4] D. Knjazew, “OmeGA (A component genetic algorithm for solving permutation and scheduling problems),” Kluwer Academic Publishers, 2002.
[5] E. Shintaku, “Minimum energy trajectory for an underwater manipulator and its simple planning method by using genetic algorithm,” Advanced Robotics, Vol.13, No.2, pp. 115-138, 1999.
[6] H. Kojima and T. Kibe, “Residual Vibration Reduction Control of a Two-Link Flexible Robot Arm Using Optimal Trajectory Planning based on Genetic Algorithm,” Journal of the Robotics Society of Japan, Vol.19, No.7, pp. 905-912, 2001.
[7] L. Tian and C. Collins, “An effective robot trajectory planning method using a genetic algorithm,” Mechatronics, Vol.14, pp. 455-470, 2004.
[8] H. Kojima, Y. Hashimoto, Y. Kuwano, K. Abe, and H. Hosoya, “Trajectory Planning of Semiconductor Wafer Transfer Robot Arm Driven by stepping Motors Using Genetic Algorithm and Experiments,” Journal of the Robotics Society of Japan, Vol.25, No.5, pp. 102-110, 2007.
[9] http://www.sanshin-kk.co.jp/products/unit/magfit.htm

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] C. S. Lin, P. R. Chang, and J. Y. S. Luh, “Formulation and optimization of cubic polynomial joint trajectories for industrial robots,” IEEE Transactions on Automatic Control, Vol.AC-28, No.12, pp. 1066-1074, 1983.

[2] [2] B. Tondu and S. A. Bazaz, “The three-cubic method: an optimal online robot joint trajectory generator under velocity,” acceleration, and wandering constraints, The Int. Journal of Robotics Research, Vol.18, No.9, pp. 893-901, 1999.

[3] [3] T. Izumi, “Path Planning for Saving Energy of a Manipulator in PTP Motions,” Journal of the Robotics Society of Japan, Vol.18, No.7, pp. 972-978, 2000.

[4] [4] D. Knjazew, “OmeGA (A component genetic algorithm for solving permutation and scheduling problems),” Kluwer Academic Publishers, 2002.

[5] [5] E. Shintaku, “Minimum energy trajectory for an underwater manipulator and its simple planning method by using genetic algorithm,” Advanced Robotics, Vol.13, No.2, pp. 115-138, 1999.

[6] [6] H. Kojima and T. Kibe, “Residual Vibration Reduction Control of a Two-Link Flexible Robot Arm Using Optimal Trajectory Planning based on Genetic Algorithm,” Journal of the Robotics Society of Japan, Vol.19, No.7, pp. 905-912, 2001.

[7] [7] L. Tian and C. Collins, “An effective robot trajectory planning method using a genetic algorithm,” Mechatronics, Vol.14, pp. 455-470, 2004.

[8] [8] H. Kojima, Y. Hashimoto, Y. Kuwano, K. Abe, and H. Hosoya, “Trajectory Planning of Semiconductor Wafer Transfer Robot Arm Driven by stepping Motors Using Genetic Algorithm and Experiments,” Journal of the Robotics Society of Japan, Vol.25, No.5, pp. 102-110, 2007.

[9] [9] http://www.sanshin-kk.co.jp/products/unit/magfit.htm

Quasi-Minimum Time Trajectory Planning Method of Robot Arm with Electromagnetic Attraction Hand Using Genetic Algorithm and Experiments

Yusuke Mutsuura*, Hiroyuki Kojima*, Yuuichi Takeuchi*, and Hiroki Saitou**

Yusuke Mutsuura^, Hiroyuki Kojima^, Yuuichi Takeuchi^*, and Hiroki Saitou^**