Force control with safety constraints via Iterative Feedback Tuning

This paper presents a new design method for force control, which aims to control the interaction force between a robot and a human by satisfying certain safety requirements. In this method, an optimization-based control algorithm, called Iterative Feedback Tuning (IFT), is used to employ safety requirements as constraints of an optimization problem, which is then solved using sequential quadratic programming (SQP). Therefore, this control method is applicable for safety-critical systems such as personal service robots. These robots are developed to provide assistance to patients or disabled people in their daily life by performing human-robot contact tasks such as wiping the face with a towel, scratching, etc. In addition, in IFT, a Newton search direction to update the controller parameters at each iteration is obtained on the basis of the closed-loop experimental data. Hence, IFT does not require explicit modeling of environment, in particular, human dynamics, otherwise in model-based approach it will be hard task to obtain a useful model. In the simulation and experiment, the effectiveness of the proposed method is examined by applying it to 1-DOF contact system.