Feature Transformation from Configuration of Open-Loop Mechanisms into Linkages with a Case Study

Abstract

This chapter proposes a method for feature synthesis of mechanisms and manipulators from user specifications based on a hybrid approach employing both neural network and optimization techniques. The typical mechanism design modeling problem with the lack of solution convergence observed in optimization is addressed by using a neural network method to generate reliable initial solutions. This chapter also discusses a module by which the validation of prescribed precision configuration points is evaluated.