Walk-assist robot: A novel approach to gain selection of a braking controller using differential flatness

With the growth of elderly population in our society, technology will play an important role in providing functional mobility to humans. From the perspective of human safety, it is desirable that controllers for walk-assist robots be dissipative, i.e., the energy is supplied by the human to the walker, while the controller modulates this energy, also the motion of the walker, while dissipating this energy. The simplest form of a dissipating controller is a brake, where resistive torques are applied to the wheels proportional to their speeds. The fundamental question that we ask in this paper is how to modulate these proportionality gains over time for the two wheels so that the walker can perform point-to-point motions in the state space. The unique contribution of this paper is a novel way in which the theory of differential flatness is used to plan the trajectory of these braking gains. Since the user input force is not known prior, the theory of model predictive control is used to periodically compute the trajectory of these braking gains. The simulation results show that the walking assist robot, along with the structure of this proposed control scheme, can guide the user to a goal accurately.