An optimal Stewart platform for lower extremity robotic rehabilitation

In this paper, two algorithms are performed to find an optimum design of a six-degree-of-freedom Stewart platform to provide a desired pure rotational motion required in the robotic rehabilitation of the foot for patients with neuropathy. To accomplish this, first, we present the kinematic and the dynamic analysis of the Stewart platform. The dynamic equations are derived by using a customized Lagrange method. Then, physically meaningful objective variables are defined such as the size of the platform, the length of the six links, the maximum stroke of the six linear actuators, the maximum actuator force, and the reachable workspace. This is followed by using two optimization methods (Genetic Algorithm and Monte-Carlo method) to study the aforementioned objective variables, resulting in the optimal solution for the desired orientation motions. Then, the detailed investigation of the effect of changes in these objective variables on the variation of the platform design variables is studied. Finally, in a numerical example, the advantages and disadvantages of using the Genetic Algorithm and the Monte-Carlo method to find the optimal design variables for a custom cost function with weighted objective variables are revealed.