A Multi-criteria Design Optimization Framework for Haptic Interfaces

This paper presents a general framework for optimization of haptic interfaces, in particular for haptic interfaces with closed kinematic chains, with respect to multiple design objectives, namely kinematic and dynamic criteria. Both performance measures are discussed and optimization problems for a haptic interface with best worst-case kinematic and dynamic performance are formulated. Non-convex single objective optimization problems are solved with a branch-and-bound type (culling) algorithm. Pareto methods characterizing the trade-off between multiple design criteria are advocated for multi-criteria optimization over widely used scalarization approaches and Normal Boundary Intersection method is applied to efficiently obtain the Pareto-front hyper-surface. The framework is applied to a sample parallel mechanism (five-bar mechanism) and the results are compared with the results of previously published methods in the literature. Finally, dimensional synthesis of a high performance haptic interface utilizing its Pareto-front curve is demonstrated.

[1]  John E. Dennis,et al.  Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems , 1998, SIAM J. Optim..

[2]  Roland W. Lewis,et al.  Several algorithms of global optimal search , 1994 .

[3]  William A. Gruver,et al.  Optimizing multiple performance criteria in redundant manipulators by subtask-priority control , 1995, 1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century.

[4]  C. Fonseca,et al.  GENETIC ALGORITHMS FOR MULTI-OBJECTIVE OPTIMIZATION: FORMULATION, DISCUSSION, AND GENERALIZATION , 1993 .

[5]  O. Weck,et al.  MULTIOBJECTIVE OPTIMIZATION : HISTORY AND PROMISE , 2004 .

[6]  Xin-Jun Liu,et al.  Optimum design of the 5R symmetrical parallel manipulator with a surrounded and good-condition workspace , 2006, Robotics Auton. Syst..

[7]  Jungwon Yoon,et al.  Design, fabrication, and evaluation of a new haptic device using a parallel mechanism , 2001 .

[8]  S. McGhee,et al.  Probability-based weighting of performance criteria for a redundant manipulator , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[9]  Il Hong Suh,et al.  Design of a new 6-DOF parallel haptic device , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[10]  Bruce E. Stuckman,et al.  A comparison of Bayesian/sampling global optimization techniques , 1992, IEEE Trans. Syst. Man Cybern..

[11]  L. Qi,et al.  On Extreme Singular Values of Matrix Valued Functions , 1996 .

[12]  Septimiu E. Salcudean,et al.  Fast constrained global minimax optimization of robot parameters , 1998, Robotica.

[13]  Clément Gosselin,et al.  A Global Performance Index for the Kinematic Optimization of Robotic Manipulators , 1991 .

[14]  Zexiang Li,et al.  Randomized Optimal Design of Parallel Manipulators , 2008, IEEE Transactions on Automation Science and Engineering.

[15]  Jürgen Hesselbach,et al.  Elastodynamic optimization of parallel kinematics , 2005, IEEE International Conference on Automation Science and Engineering, 2005..

[16]  Tsuneo Yoshikawa,et al.  Dynamic Manipulability of Robot Manipulators , 1985 .

[17]  Bijan Shirinzadeh,et al.  Optimum synthesis of planar parallel manipulators based on kinematic isotropy and force balancing , 2004, Robotica.

[18]  Carlos A. Coello Coello,et al.  An updated survey of GA-based multiobjective optimization techniques , 2000, CSUR.

[19]  Vincent Hayward,et al.  Design and multi-objective opti-mization of a link a for a haptic interface , 1994 .

[20]  Lothar Thiele,et al.  Comparison of Multiobjective Evolutionary Algorithms: Empirical Results , 2000, Evolutionary Computation.

[21]  Hisao Ishibuchi,et al.  Comparison of evolutionary multiobjective optimization with rference solution-based single-objective approach , 2005, GECCO '05.

[22]  Sung-Uk Lee,et al.  Analysis and Optimal Design of a New 6 DOF Parallel Type Haptic Device , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[23]  Peter J. Fleming,et al.  Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.

[24]  Enrico Rigoni,et al.  NBI and MOGA-II, two complementary algorithms for Multi-Objective optimizations , 2005, Practical Approaches to Multi-Objective Optimization.

[25]  John J. Craig,et al.  Articulated hands: Force control and kinematic issues , 1981 .

[26]  Xin-Jun Liu,et al.  A new methodology for optimal kinematic design of parallel mechanisms , 2007 .

[27]  Gerald W. Evans,et al.  Comparison of global search methods for design optimization using simulation , 1991, 1991 Winter Simulation Conference Proceedings..

[28]  H. Asada,et al.  A Geometrical Representation of Manipulator Dynamics and Its Application to Arm Design , 1983 .

[29]  Tsuneo Yoshikawa,et al.  Dynamic manipulability of robot manipulators , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[30]  Septimiu E. Salcudean,et al.  Robot design optimization with haptic interface applications , 2000 .

[31]  J. Angeles,et al.  The Kinetostatic Optimization of Robotic Manipulators: The Inverse and the Direct Problems , 2006 .

[32]  Antonio Frisoli,et al.  A two degrees-of-freedom planar haptic interface with high kinematic isotropy , 1999, 8th IEEE International Workshop on Robot and Human Interaction. RO-MAN '99 (Cat. No.99TH8483).

[33]  Sergiu-Dan Stan,et al.  Optimal Design of 2 DOF Parallel Kinematics Machines , 2006 .