A Multi-criteria design optimization framework for haptic interfaces

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 (modified 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.