Kinematic sensitivity and workspace optimization of planar parallel mechanisms using evolutionary techniques

This paper presents the results of a comprehensive study on the efficiency of planar parallel mechanisms, considering their kinetostatic performance and also, their workspace. This aim is approached upon proceeding single- and multi-objective optimization procedures. Kinetostatic performance of ten different architectures is analyzed, by resorting to a recent index, kinematic sensitivity. The mathematical framework adopted for the optimization problem is based on genetic algorithm. The results of multi-objective optimization are based on the sets of Pareto points, offering the most reliable decisions to reconciliate between some conflicting objectives. To this end, the ten mechanisms are sorted into two sets based on their type of actuator, namely, five with prismatic actuators and the other ones with revolute actuators. Finally, a comparison between performances of these mechanisms, according to the obtained results, is carried out.