An efficient combined local and global search strategy for optimization of parallel kinematic mechanisms with joint limits and collision constraints

The optimization of parallel kinematic manipulators (PKM) involve several constraints that are difficult to formalize, thus making optimal synthesis problem highly challenging. presence passive joint limits as well the singularities and self-collisions lead a complicated relation between input output parameters. In this article, novel methodology is proposed by combining local search, Nelder–Mead algorithm, with global search methodologies such low discrepancy distribution for faster more efficient exploration space. effect dimension different discussed highlight complexities closed-loop chain optimization. work also presents approaches used consider boundaries avoid internal collisions in mechanisms. algorithm can optimize length prismatic actuators be added modular fashion, allowing understand impact given criteria on final result. application presented approach two PKMs degrees freedom.