Reducing the optimization problem for the efficient motion planning of kinematically redundant parallel robots

This paper presents an optimization procedure used to efficiently maximize the potentials of parallel manipulators with kinematic redundancy within real-time. The proposed approach consists of reducing the search space defined by the optimization problem beforehand, through minimizing the amount of optimization points necessary to induce the optimization problem. Furthermore, the computation time of the fitness function is reduced during run-time. Therefore, the relationship between the Cartesian path of the end-effector and the resulting optimization problem is studied and a procedure to minimize the given dependencies is presented. Exemplarily, a kinematically redundant 3(P)RRR parallel robot is considered to quantify the efficiency of the discussed procedure. The results demonstrate that the proposed approach is able to outperform existing procedures by one to two orders of magnitude.