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Optimal design of 6-DOF eclipse mechanism based on task-oriented workspace

Published online by Cambridge University Press:  25 July 2011

Donghun Lee
Affiliation:
Mechatronics Center, Samsung Heavy Industry, Daejeon, Republic of Korea
Jongwon Kim
Affiliation:
School of Mechanical and Aerospace Engineering, Seoul National University, Seoul, Republic of Korea
TaeWon Seo*
Affiliation:
School of Mechanical Engineering, Yeungnam University, Gyeongsan, Republic of Korea
*
*Corresponding author. E-mail: [email protected]

Summary

We present a new numerical optimal design for a redundant parallel manipulator, the eclipse, which has a geometrically symmetric workspace shape. We simultaneously consider the structural mass and design efficiency as objective functions to maximize the mass reduction and minimize the loss of design efficiency. The task-oriented workspace (TOW) and its partial workspace (PW) are considered in efficiently obtaining an optimal design by excluding useless orientations of the end-effector and by including just one cross-sectional area of the TOW. The proposed numerical procedure is composed of coarse and fine search steps. In the coarse search step, we find the feasible parameter regions (FPR) in which the set of parameters only satisfy the marginal constraints. In the fine search step, we consider the multiobjective function in the FPR to find the optimal set of parameters. In this step, fine search will be kept until it reaches the optimal set of parameters that minimize the proposed objective functions by continuously updating the PW in every iteration. By applying the proposed approach to an eclipse-rapid prototyping machine, the structural mass of the machine can be reduced by 8.79% while the design efficiency is increased by 6.2%. This can be physically interpreted as a mass reduction of 49 kg (the initial structural mass was 554.7 kg) and a loss of 496 mm3/mm in the workspace volume per unit length. The proposed optimal design procedure could be applied to other serial or parallel mechanism platforms that have geometrically symmetric workspace shapes.

Type
Articles
Copyright
Copyright © Cambridge University Press 2011

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References

1. Tsai, K. Y., Lee, T. K. and Huang, K. D., “Determining the workspace boundary of 6-DOF parallel manipulators,” Robotica 24, 605611 (2006).CrossRefGoogle Scholar
2. Merlet, J. P., “Determination of the orientation workspace of parallel manipulators,” J. Intell. Robot. Syst. 13, 143160 (1995).CrossRefGoogle Scholar
3. Waldron, K. J. and Kumar, A., “The workspaces of a mechanical manipulator,” ASME J. Mech. Des. 103, 665672 (1981).Google Scholar
4. Tsai, Y. C. and Soni, A. H., “Accessible region and synthesis of robot arm,” ASME J. Mech. Des. 103, 803811 (1981).Google Scholar
5. Gupta, K. G. and Roth, B., “Design considerations for manipulator workspace,” ASME J. Mech. Des. 104, 704711 (1982).Google Scholar
6. Davidson, J. K. and Hunt, K. H., “Rigid body location and robot workspace: Some alternative manipulator forms,” ASME J. Mech. Transm. 109, 224242 (1987).CrossRefGoogle Scholar
7. Yang, F.-C. and Haug, E. J., “Numerical analysis of the kinematic working capability of mechanisms,” ASME J. Mech. Des. 116, 111118 (1994).CrossRefGoogle Scholar
8. Haug, E. J., Luh, C.-M., Adkins, F. A. and Wang, J.-Y., “Numerical algorithms for mapping boundaries of manipulator workspaces,” ASME J. Mech. Des. 118, 228234 (1996).CrossRefGoogle Scholar
9. Pond, G. T. and Carretero, J. A., “Quantitative dexterous workspace comparison parallel manipulators,” Mech. Mach. Theory 42, 13881400 (2007).CrossRefGoogle Scholar
10. Bonev, I. A. and Ryu, J., “A new approach to orientation workspace analysis of 6-dof parallel manipulators,” Mech. Mach. Theory 36, 1528 (2001).CrossRefGoogle Scholar
11. Oh, K.-K., Liu, X.-J., Kang, D. S. and Kim, J., “Optimal design of a micro parallel positioning platform. Part I: Kinematic analysis,” Robotica 22, 599606 (2004).CrossRefGoogle Scholar
12. Oh, K.-K., Liu, X.-J., Kang, D. S. and Kim, J., “Optimal design of a micro parallel positioning platform. Part. II: Real machine design,” Robotica 23, 109122 (2005).CrossRefGoogle Scholar
13. Ahn, C., Seo, T., Kim, J. and Kim, T., “High-tilt parallel positioning mechanism development and cutter path simulation for laser micro-machining,” Comput.-Aided Des. 39, 218228 (2007).CrossRefGoogle Scholar
14. Kim, J., Park, F. C., Ryu, S. J., Kim, J., Hwang, J., Park, C. and Iurascu, C., “Design and analysis of a redundantly actuated parallel mechanism for rapid machining,” IEEE Trans. Robot. Autom. 17, 423434 (2001).CrossRefGoogle Scholar
15. Kim, J., Cho, K. S., Hwang, J., Iurascu, C. and Park, F. C., “Eclipse-RP: A new RP machine based on deposition and machining,” J. Multi-body Dyn. 216, 1320 (2002).Google Scholar
16. Craig, J. J., Introduction to Robotics: Mechanics and Control, 3rd ed. (Prentice Hall, Upper Side River, New Jersey, USA) ISBN-13: 978-0201543612.Google Scholar
17. Kucuk, S. and Bingul, Z., “Comparative study of performance indices for fundamental robot manipulator,” Robot. Auton. Syst. 54, 567573 (2006).CrossRefGoogle Scholar
18. Hao, F. and Merlet, J.-P., “Multi-criteria optimal design of parallel manipulators based on interval analysis,” Mech. Mach. Theory 40, 157171 (2004).CrossRefGoogle Scholar
19. Homaifar, A., Lai, S. H. Y. and Qi, X., “Constrained optimization via genetic algorithms,” Simulation 62, 242254 (1994).CrossRefGoogle Scholar
20. Michalewicz, Z., “Evolutionary algorithms for constrained engineering problems,” Comput. Ind. Eng. 30, 851870 (1996).CrossRefGoogle Scholar