Multiobjective optimization of a linear Delta parallel robot

The dimensional synthesis remains a capital phase in the optimal design of the parallel robots. In this article, we propose a methodology of the dimensional synthesis where the problem is expressed in terms of multiobjective optimization by taking account simultaneously several criteria of performance. The proposed methodology can be structured as follows: 1/Geometric, kinematic and dynamic modeling of the chosen structure, 2/Evaluation of the criteria of performance (workspace, stiffness, kinematic and dynamic performances), 3/Definition of constraints related to the studied structure of the robot, 4/Mathematical formulation of the multiobjective optimization problem and 5/Application of genetic algorithm SPEA-II for the problem resolution. Finally, we present an illustrative application of the methodology developed for a linear Delta parallel robot with three degrees of freedom.

► We present an approach of dimensional synthesis for parallel robots.
► The problem will be defined as a multiobjective optimization.
► The method of genetic algorithms is used to solve this problem.
► Application to the linear Delta parallel robot.