Multi-criteria design optimization of parallel robots

This paper presents a framework for multi-criteria design optimization of parallel mechanisms. 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 hypersurface. The proposed framework is compared against sequential optimization and weighted sum approaches. Dimensional synthesis of a sample parallel mechanism (five-bar mechanism) is demonstrated through estimation of the relative weights of performance indices that are implicit in the Pareto plot. The framework is computational efficient, applicable to any set of performance indices, and extendable to include any number of design criteria that is required by the application.