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Technical Briefs

Repetitive Motion Planning and Control on Redundant Robot Manipulators With Push-Rod-Type Joints

[+] Author and Article Information
Z. Zhang

School of Information Science and Technology,
Sun Yat-sen University,
Guangzhou, Guangdong, 510006, PRC
e-mail: iloveyouzhijun@126.com;
drzhangzhijun@gmail.com

Y. Zhang

Professor
School of Information Science and Technology,
Sun Yat-sen University,
Guangzhou, Guangdong, 510006, PRC;
Research Institute of Sun Yat-sen
University in Shenzhen,
Shenzhen, Guangdong, 518057, PRC
e-mail: zhynong@mail.sysu.edu.cn; ynzhang@ieee.org

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the Journal of Dynamic Systems, Measurement, and Control. Manuscript received December 20, 2011; final manuscript received July 27, 2012; published online November 7, 2012. Assoc. Editor: Alexander Leonessa.

J. Dyn. Sys., Meas., Control 135(2), 024502 (Nov 07, 2012) (4 pages) Paper No: DS-11-1400; doi: 10.1115/1.4007608 History: Received December 20, 2011; Revised July 27, 2012

To demonstrate the hardware realizability and efficacy of the quadratic program (QP) based methods for solving the nonrepetitive problem, this paper proposes a novel repetitive motion planning and control (RMPC) scheme and realizes this scheme on a physical planar six degrees-of-freedom (DOF) push-rod-joint (PRJ) manipulator. To control the PRJ manipulator, this scheme considers variable joint-velocity limits and joint-limit margins. In addition, to decrease the errors, this scheme considers the position-error feedback. Then, the scheme is reformulated as a QP problem. Due to control of the digital computer, a discrete-time QP solver is presented to solve the QP problem. For comparison, both of the nonrepetitive and repetitive motions are performed on the manipulator to track square and B-shaped paths. Experimental results validate the physical realizability and effectiveness of the RMPC scheme.

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References

Agrawal, S. K., and Veeraklaew, T., 1998, “Designing Robots for Optimal Performance During Repetitive Motion,” IEEE Trans. Rob. Autom., 14(5), pp. 771–777. [CrossRef]
Liu, T. S., and Lee, W. S., 2000, “A Repetitive Learning Method Based on Sliding Mode for Robot Control,” ASME J. Dyn. Sys., Meas., Control, 122(1), pp. 40–48. [CrossRef]
Shamir, T., and Yomdin, Y., 1988, “Repeatability of Redundant Manipulators: Mathematical Solution of the Problem,” IEEE Trans. Autom. Control, 33(11), pp. 1004–1009. [CrossRef]
De Luca, A., Mattone, R., and Oriolo, G., 1997, “Control of Redundant Robots Under End-Effector Commands: A Case Study in Underactuated Systems,” J. Appl. Math. Comput. Sci., 7(2), pp. 101–127. Available at http://www.dis.uniroma1.it/~labrob/pub/papers/AM&CS97_final.pdf
Zhang, Y., Tan, Z., Chen, K., Yang, Z., and Lv, X., 2009, “Repetitive Motion of Redundant Robots Planned by Three Kinds of Recurrent Neural Networks and Illustrated With a Four-Link Planar Manipulator's Straight-Line Example,” Rob. Auton. Syst., 57(6–7), pp. 645–651. [CrossRef]
Zhang, Z., and Zhang, Y., 2012, “Variable Joint-Velocity Limits of Redundant Robot Manipulators Handled by Quadratic Programming,” IEEE Trans. Mechatron., PP, pp. 1–13. [CrossRef]

Figures

Grahic Jump Location
Fig. 1

Hardware system of the six-DOF PRJ manipulator

Grahic Jump Location
Fig. 2

Limit conversion with margins considered for 0 < θi- < θi+

Grahic Jump Location
Fig. 3

Images of the actual task execution when the end-effector of the robot tracks a square path with η=4

Grahic Jump Location
Fig. 4

Images of the actual task execution when the end-effector of the robot tracks a B-shaped path with η=4

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