An Optimization Approach Toward a Robust Design of Six Degrees of Freedom Haptic Devices

This work presents an optimization approach for the robust design of six degrees of freedom (DOF) haptic devices. Our objective is to find the optimal values for a set of design parameters that maximize the kinematic, dynamic, and kinetostatic performances of a 6-DOF haptic device while minimizing its sensitivity to variations in manufacturing tolerances. Because performance indices differ in magnitude, the formulation of an objective function for multicriteria performance requirements is complex. A new approach based on Monte Carlo simulation (MCS) was used to find the extreme values (minimum and maximum) of the performance indices to enable normalization of these indices. The optimization approach presented here is formulated as a methodology in which a hybrid design-optimization approach, combining genetic algorithm (GA) and MCS, is first used. This new approach can find the numerical values of the design parameters that are both optimal and robust (i.e., less sensitive to variation and thus to uncertainties in the design parameters). In the following step, with design optimization, a set of optimum tolerances is determined that minimizes manufacturing cost and also satisfies the allowed variations in the performance indices. The presented approach can thus enable the designer to evaluate trade-offs between allowed performance variations and tolerances cost.