Force Control Law Selection for Elastic Part Assembly from Human Data and Parameter Optimization

This paper proposes a novel force control design method used to assemble a ring-shaped elastic part to a cylinder's outer groove. To assemble a ring-shaped elastic part, forces acting on an elastic part should be made as small as possible. To cope with this problem, we propose a novel method in which the force control strategy itself is automatically determined based on the human characteristics while the parameters of the controller are determined by using a numerical optimization. First, the position data and the force data while a human demonstrates the assembly are measured. From the measured data, two control methods are derived by using the normalized cross-correlation (NCC). Then, we optimize the parameters included in the obtained controller by using the downhill simplex method. The objective function of optimization is the peak force during the assembly. We confirmed that the applied force is considerably reduced compared with conventional methods.