IJAT Vol.4 No.2 pp. 161-168
doi: 10.20965/ijat.2010.p0161


Quasi-Minimum Time Trajectory Planning and Experiments for Prototype Direct-Drive Robot Arm Driven by Stepping Motors Using GA

Hiroyuki Kojima*, Kengo Motomura*, Yoshifumi Kuwano**,
Keiichi Abe** and Hajime Hosoya***

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

**Nidec Servo Co. Ltd., 3-93 Aioicho, Kiryu, Gunma 376-0011, Japan

***Gunma Industrial Technology Center, 884-1 Kamesatomachi, Maebashi, Gunma 379-2147, Japan

October 5, 2009
January 7, 2010
March 5, 2010
quasi-minimum time trajectory planning, direct-drive robot arm, stepping motor, genetic algorithm

In this paper, a quasi-minimum time trajectory planning of three-link direct-drive robot arm driven with stepping motors using a genetic algorithm (GA) was proposed. The prototype direct-drive robot arm was newly manufactured in this study. The trajectory for a semiconductor wafer transfer work consists of three trajectory portions: a straight line, a curved line, and a straight line. In the trajectory planning, three trajectory portions are expressed by polynomials of time. Using the boundary and continuous conditions concerning joint angle, joint angular velocity and joint angular acceleration, the whole trajectory is described by a chromosome consisting of five genes. Then, the fitness function of the genetic algorithm for the quasi-minimum time control was defined, under the constraint condition that the stepping motor torques should not exceed pull-out torques. Furthermore, the numerical calculations and experiments have been carried out, and it is confirmed that the quasi-minimum time trajectory planning can be executed successfully, and the trajectory tracking control can be well performed.

Cite this article as:
H. Kojima, K. Motomura, Y. Kuwano, <. Abe, and H. Hosoya, “Quasi-Minimum Time Trajectory Planning and Experiments for Prototype Direct-Drive Robot Arm Driven by Stepping Motors Using GA,” Int. J. Automation Technol., Vol.4, No.2, pp. 161-168, 2010.
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Last updated on Nov. 08, 2019