Dimensional Optimization of Spherical 5R Parallel Mechanism with Maximum Transmission Workspace

The 2-degree-of-freedom spherical 5R parallel mechanism is taken as the research object， and teaching-learning-based optimization （TLBO） algorithm is applied to solve the optimization design problem of mechanism dimensional parameters. The expression of inverse positional analysis for the mechanism is derived by means of coordinate transformation. Consequently， the transmission angle is used as the evaluation index of motion/force transmission performance， and then the definition and numerical calculation method of good transmission workspace （GTW） are given. Taking the maximizing area of GTW as object， a constrained optimization model of dimensional parameters is established， and TLBO algorithm is employed to solve this problem. The results show that the presented model and algorithm are feasible and effective.