Trajectory Formation of Arm Movement using Genetic Algorithm

In order to explain features of a point-to-point human arm movement, several models based on a minimization principle have been proposed. For example, there are the minimum hand jerk model, the minimum angle jerk model, the minimum commanded torque change model, the minimum-variance model and so on. For some models listed above; the minimum hand jerk model, the minimum angle jerk model and the minimum commanded torque change model, these established methods to obtain an optimal trajectory which satisfies corresponding criterion have already been reported. However it is difficult to obtain the optimal solutions of the minimum-variance model and of other some models. In this study, we propose a novel method to calculate optimal trajectories without depending on the employed criterion by using genetic algorithm. The proposed method has following two procedures; first, the objective trajectory is described by the sum of polynomial equations which satisfy the boundary conditions strictly, and second, the coefficients of the polynomial expressions are determined by using genetic algorithm. In this report, we have confirmed the effectiveness of our method in numerical experiments. First, in the minimum commanded torque change model, we show that the produced trajectory is in beautiful agreement with the optimal solution. Next, in the minimum-variance model, the obtained solution by using proposed method has better evaluated values than one of the quasi-optimal solution that is obtained by the conventional Simplex method