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Novel Manipulability for Parallel Mechanisms with Prismatic-Revolute Actuators, GA-DP Trajectory Planning Application

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Abstract—

Performance measures have been utilized for numerous applications in robotics research. In this paper, the manipulability and dexterity indices have been focused. These indices have been used successfully when parallel robots have either completely revolute or prismatic joints. But, in a manipulator with both revolute and prismatic joints, these may not be used because of the dimensional inconsistency of the components in the Jacobian matrix. Moreover, in the kinematic or dynamic case, for manipulability and dexterity analysis, the Euclidean norm for the velocity inputs is considered while the velocity inputs for active joints are generally independent; therefore, the manipulability and dexterity indices are explained based on the infinity-norm. Thus, the final solution is represented by the new concept of mixed manipulability polytope. Next, an example of the 3-RPC parallel robot is analyzed based on the notion of this index. As an application, the index is applied for trajectory planning in multi-objective optimal control. For this, one of the direct methods of optimal control, dynamic programming (DP), is selected. But for the DP, the genetic algorithm (GA) is used for searching the optimum path. This analysis is applied for a novel PU-3RPR redundant parallel manipulator. First, the parallel mechanism is introduced, and the kinematics and Jacobian analysis is discussed. Then the objective function that minimizes the pseudo kinetic energy and maximizes the index, is adopted for an optimization problem. Finally, the trajectory of the PU-3RPR redundant parallel mechanism is planned by the proposed GA-DP method.

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REFERENCES

  1. M. Bamdad and M. M. Bahri, “Kinematics and manipulability analysis of a highly articulated soft robotic manipulator,” Robotica 37, 868-882 (2019).

    Article  Google Scholar 

  2. E. Mirshekari, A. Ghanbarzadeh, and K. H. Shirazia, “Structure comparison and optimal design of 6-RUS parallel manipulator based on kinematic and dynamic performances,” Lat. Am. J. Solids Struct. 13, 2414–2438 (2016).

    Article  Google Scholar 

  3. S. Kucuk and Z. Bingul, “Comparative study of performance indices for fundamental robot manipulators,” Rob. Auton. Syst. 54, 567–573 (2006).

    Article  Google Scholar 

  4. S. Kucuk, “A dexterity comparison for 3-DOF planar parallel manipulators with two kinematic chains using genetic algorithms,” Mechatronics 19, 868–877 (2009).

    Article  Google Scholar 

  5. C. Zhang, Y. Chen, H. Xu, et. al., “Kinematic modeling and dexterity evaluation of a PS-RRS-2RUS parallel manipulator used for controllable pitch propeller,” Mech. Based Des. Struct. Mach. 46, 533–551 (2018).

    Article  Google Scholar 

  6. S. Shayya, S. Krut, O. Company, et al. “On the performance evaluation and analysis of general robots with mixed dofs,” in Intelligent Robots and Systems (IROS 2014), Chicago, IL, 2014, pp. 490–497.

  7. A. Bowling and O. Khatib, “Dynamic loading criteria in actuator selection for desired dynamic performance,” Adv. Rob. 17, 641–656 (2003).

    Article  Google Scholar 

  8. S.-G. Kim and J. Ryu, “Force transmission analyses with dimensionally homogeneous jacobian matrices for parallel manipulators,” J. Mech. Sci. Technol. 18, 780–788 (2004).

    Google Scholar 

  9. G. Boschetti, R. Rosa, and A. Trevisani, “Parallel robot translational performance evaluation through direction-selective index (DSI),” J. Rob. 2011 (2011).

  10. I. Mansouri and M. Ouali, “The power manipulability–A new homogeneous performance index of robot manipulators,” Rob. Comput. Integr. Manuf. 27, 434–449 (2011).

    Article  Google Scholar 

  11. A. P. Bowling, “Dynamic performance, mobility, and agility of multilegged robots,” J. Dyn. Syst., Meas., Control. 128, 765–777 (2006).

    Article  Google Scholar 

  12. S. G. Kim and J. Ryu, “New dimensionally homogeneous Jacobian matrix formulation by three end-effector points for optimal design of parallel manipulators,” IEEE Trans. Rob. Autom. 19, 731–736 (2003).

    Article  Google Scholar 

  13. O. Altuzarra, O. Salgado, V. Petuya, and A. Hernández, “Point-based Jacobian formulation for computational kinematics of manipulators,” Mech. Mach. Theory. 41, 1407–1423 (2006).

    Article  MathSciNet  Google Scholar 

  14. G. Pond and J. A. Carretero, “Dexterity measures and their use in quantitative dexterity comparisons,” Meccanica 46, 51–64 (2011).

    Article  MathSciNet  Google Scholar 

  15. J. P. Merlet, “Jacobian, manipulability, condition number, and accuracy of parallel robots,” Journal of Mechanical Design. 128, 199–206 (2006).

    Article  Google Scholar 

  16. K. C. Olds, “Global Indices for kinematic and force transmission performance in parallel robots,” IEEE Transactions on Robotics. 31, 494–500 (2015).

    Article  Google Scholar 

  17. Q. Meng, F. Xie, X.-J. Liu, and Y. Takeda, “Screw Theory-Based Motion/Force Transmissibility Analysis of High-Speed Parallel Robots With Articulated Platforms,” Journal of Mechanisms and Robotics. 12 (2020).

  18. T. Yoshikawa, Foundations of Robotics: Analysis and Control (MIT press, 1990).

    Google Scholar 

  19. Y. Nakamura and H. Hanafusa, “Optimal redundancy control of robot manipulators,” Int. J. Rob. Res. 6, 32–42 (1987).

    Article  Google Scholar 

  20. T. Chettibi, H. Lehtihet, M. Haddad, and S. Hanchi, “Minimum cost trajectory planning for industrial robots,” Eur. J. Mech. A/Solids. 23, 703–715 (2004).

    Article  Google Scholar 

  21. O. Wigström and B. Lennartson, “Energy optimization of trajectories for high level scheduling,” in 2011 IEEE International Conference on Automation Science and Engineering, Trieste, 2011, pp. 654–659.

  22. O. Wigstrom, B. Lennartson, A. Vergnano, and C. Breitholtz, “High-level scheduling of energy optimal trajectories,” IEEE Trans. Autom. Sci. Eng. 10, 57–64 (2013).

    Article  Google Scholar 

  23. C. M. Gosselin, “The optimum design of robotic manipulators using dexterity indices,” Rob. Auton. Syst. 9, 213–226 (1992).

    Article  Google Scholar 

  24. X. Kong and C. M. Gosselin, “Type synthesis of 3-DOF translational parallel manipulators based on screw theory,” J. Mech. Des. 126, 83–92 (2004).

    Article  Google Scholar 

  25. X. Kong and C. M. Gosselin, Type Synthesis of Parallel Mechanisms Vol. 33 (Springer, 2007).

    MATH  Google Scholar 

  26. I. Prause, M. Lorenz, and B. Corves, “Kinetostatic analysis of the translational RPC-manipulator with different actuator and frame configurations,” in 2015 IEEE International Conference on Robotics and Automation (ICRA) (Seattle, 2015), pp. 1605–1612.

  27. I. Prause and B. Corves, “Dynamic modeling of the RPC-manipulator with prismatic or revolute joint actuation for different frame configurations,” in 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (Hamburg, 2015), pp. 4105–4112.

  28. D. S. Naidu, Optimal Control Systems (CRC Press, 2002).

    Google Scholar 

  29. W. Alt, U. Felgenhauer, and M. Seydenschwanz, “Euler discretization for a class of nonlinear optimal control problems with control appearing linearly,” Comput. Optim. Appl. 69, 825–856 (2018).

    Article  MathSciNet  Google Scholar 

  30. V. Azimirad and H. Shorakaei, “Dual hierarchical genetic-optimal control: A new global optimal path planning method for robots,” J. Manuf. Syst. 33, 139–148 (2014).

    Article  Google Scholar 

  31. H. Khakpour, L. Birglen, and S.-A. Tahan, “Analysis and optimization of a new differentially driven cable parallel robot,” J. Mech. Rob. 7, 034503 (2015).

    Article  Google Scholar 

  32. Y. Nakamura, Advanced Robotics: Redundancy and Optimization (Addison-Wesley, Inc., 1990).

    Google Scholar 

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Correspondence to M. Badrikouhi or M. Bamdad.

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Badrikouhi, M., Bamdad, M. Novel Manipulability for Parallel Mechanisms with Prismatic-Revolute Actuators, GA-DP Trajectory Planning Application. Mech. Solids 56, 278–291 (2021). https://doi.org/10.3103/S0025654421020023

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  • DOI: https://doi.org/10.3103/S0025654421020023

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