Hostname: page-component-74656f9884-2dmjx Total loading time: 0 Render date: 2026-11-09T00:13:59.754Z Has data issue: false hasContentIssue false
  • English
  • Français

Multi-objective optimal design based kineto-elastostatic performance for the delta parallel mechanism

Published online by Cambridge University Press:  04 June 2014

Belkacem Bounab
Belkacem Bounab*
Affiliation:
Laboratoire de Mécanique des Structures, École Militaire Polytechnique BP 17, 16111-Bordj El-Bahri, Algiers, Algeria
*
*Corresponding author. E-mail: bounabbelkacem.emp@gmail.com
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

This paper addresses the dimensional-synthesis-based kineto-elastostatic performance optimization of the delta parallel mechanism. For the manipulator studied here, the main consideration for the optimization criteria is to find the maximum regular workspace where the robot delta must posses high stiffness and dexterity. The dexterity is a kinetostatic quality measure that is related to joint's stiffness and control accuracy. In this study, we use the Castigliano's energetic theorem for modeling the elastostatic behavior of the delta parallel robot, which can be evaluated by the mechanism's response to external applied wrench under static equilibrium. In the proposed formulation of the design problem, global structure's stiffness and global dexterity are considered together for the simultaneous optimization. Therefore, we formulate the design problem as a multi-objective optimization one and, we use evolutionary genetic algorithms to find all possible trade-offs among multiple cost functions that conflict with each other. The proposed design procedure is developed through the implementation of the delta robot and, numerical results show the effectiveness of the proposed design method to enhancing kineto-elastostatic performance of the studied manipulator's structure.

Keywords

delta robotOptimal designKineto-elastostatic performanceMulti-objective optimizationEvolutionary algorithms

Information

Type
Articles
Information
Robotica , Volume 34 , Issue 2 , February 2016 , pp. 258 - 273
Copyright
Copyright © Cambridge University Press 2014 

References

1.Adkins, F. A. and Haug, E. J., “Operational envelope of a spatial stewart platform,” Trans. ASME, J. Mech. Des. 2 (119), 330–332 (1997).CrossRefGoogle Scholar
2.Bhattacharya, S., Hatwal, H. and Ghosh, A., “On the optimum design of a stewart platform type parallel manipulators,” Robotica 13 (2), 133–140 (1995).CrossRefGoogle Scholar
3.Chablat, D., Wenger, P., Majou, F. and Merlet, J-P., “An interval analysis based study for the design and the comparison of three-degrees-of-freedom parallel kinematic machines,” Int. J. Robot. Res. 23 (6), 615–624 (2004).CrossRefGoogle Scholar
4.Clavel, R., “Delta, a Fast Robot with Parallel Geometry,” Proceedings of the 18th International Symposium on Industrial Robots, Lausanne (1988) pp. 91–100.Google Scholar
5.Clavel, R., Conception d'un robot parallèle rapide à quatre degrés de liberté. PhD thesis (EPFL, Lausanne, 1991).Google Scholar
6.Courteille, E., Deblaise, D. and Maurine, P., “Design optimization of a delta-like parallel robot through global stiffness performance evaluation,” (Oct. 2009) pp. 5159–5166.CrossRefGoogle Scholar
7.Deb, K., Multi-Objective Optimization using Evolutionary Algorithms (John Wiley & Sons, 2001).Google Scholar
8.Gosselin, C., “Stiffness mapping for parallel manipulators,” IEEE Trans. Robot. Autom. 3 (6), 377–382 (1990).CrossRefGoogle Scholar
9.Gosselin, C. and Angeles, J., “The optimum kinematic design of a planar three-degree-of-freedom parallel manipulator,” ASME J. Mech. Des. 110 (1), 35–41 (1988).Google Scholar
10.Gosselin, C. and Angeles, J., “The optimum kinematic design of a spherical three-degree-of-freedom parallel manipulator,” ASME J. Mech. Des. 111 (2), 202–207 (1989).Google Scholar
11.Gosselin, C. and Angeles, J., “A global performance index for the kinematic optimization of robotic manipulators,” Trans. ASME J. Mech. Des. (113), 220–226 (1991).CrossRefGoogle Scholar
12.Haugh, E. J., Adkins, F. A., and Luh, C. M., “Operational envelopes for working bodies of mechanisms and manipulators,” Trans. ASME J. Mech. Des. 1 (120), 84–91 (1998).CrossRefGoogle Scholar
13.Kelaiaia, R., Companya, O. and Zaatri, A., “Multiobjective optimization of parallel kinematic mechanisms by the genetic algorithms,” Robotica 30 (5), 783–797 (2012).CrossRefGoogle Scholar
14.Lara-Molina, F. A., Rosrio, J. M and Dumur, D., “Multi-objective design of parallel manipulator using global indices,” Open Mech. Eng. J. 4, 37–47 (2010).CrossRefGoogle Scholar
15.Li, Y. and Xu, Q., “A new approach to the architecture optimization of a general 3-puu translational parallel manipulator,” J. Int. Robot. Syst. 46 (1), 59–72 (2006).CrossRefGoogle Scholar
16.Liu, X.-J., “Optimal kinematic design of a three translational dofs parallel manipulator,” Robotica 24 (2), 239–250 (2006).CrossRefGoogle Scholar
17.Liu, X.-J., Wang, J., Oh, K.-K. and Kim, J., “A new approach to the design of a delta robot with a desired workspace,” J. Intell. Robot. Syst. 39 (2), 209–225 (2004).CrossRefGoogle Scholar
18.Lou, Y., Liu, G. and Li, Z., “Randomized optimal design of parallel manipulators,” IEEE Trans. Autom. Sci. Eng. 5 (2), 223–233 (2008).Google Scholar
19.MathWorks. Global Optimization Toolbox, Multiobjective Optimization, UsersGuide (2012).Google Scholar
20.Merlet, J.-P., “Determination of 6d workspaces of gough-type parallel manipulator and comparison between different geometries,” Int. J. Robot. Res. 9 (18), 902–916 (1999).CrossRefGoogle Scholar
21.Merlet, J. P., Parallel Robots, 2nd edn. (Springer Publishing Company, Incorporated, 2010) pp. 12–62.Google Scholar
22.Pisla, D., Ceccarelli, M., Husty, M. and Corves, B., New Trends in Mechanism Science: Analysis and Design (Springer Dordrecht Heidelberg, London, New York, 2010) pp. 633–640.CrossRefGoogle Scholar
23.Przemieniecki, J. S., Theory of Matrix Structural Analysis (Courier Dover Publications, 1985).Google Scholar
24.Salisbury, J. K. and Craig, J. J., “Articulated hands: force control and kinematic issues,” Int. J. Robot. Res. 1 (1), 4–17 (1982).CrossRefGoogle Scholar
25.Siciliano, B. and Khatib, O., Handbook of Robotics (Springer, 2008) pp. 229–319.CrossRefGoogle Scholar
26.Stock, M. and Miller, K., “Optimal kinematic design of spatial parallel manipulators: application to linear delta robot,” ASME J. Mech. Des. (125), 292–301 (2003).CrossRefGoogle Scholar
27.Tsai, L. W., Robot Analysis, the Mechanics of Serial and Parallel Manipulators (John Wiley & Sons, 1999).Google Scholar
28.Wang, L., Amos, H. C. Ng and Deb, K., Multi-objective Evolutionary Optimisation for Product Design and Manufacturing (Springer, 2011).Google Scholar
29.Xu, Q. and Li, Y., “Kinematic analysis and optimization of a new compliant parallel micromanipulator,” Int. J. Adv. Robot. Syst. 3 (4), 59–72 (2006).CrossRefGoogle Scholar
30.Zanganeh, K. E. and Angeles, J., “Kinematic isotropy and the optimum design of parallel manipulators,” Int. J. Robot. Res. 16 (2), 185–197 (1997).CrossRefGoogle Scholar
31.Zhang, D., Parallel Robotic Machine Tools (Springer, 2010).CrossRefGoogle Scholar
32.Zhao, Y., “Dimensional synthesis of a three translational degrees of freedom parallel robot while considering kinematic anisotropic property,” Robot. Comput.-Integr. Manuf. 29 (1), 169–179 (2013).CrossRefGoogle Scholar