In the currently aging society, walk-assist robots can play an important role in improving the activities of daily living of the elderly. In this paper, we propose a robot walking helper with both passive and active control modes for guidance. From the perspective of human safety, the passive mode adopts a braking control law on the wheels to differentially steer the vehicle. However, if the user walks uphill in the outdoor environment, external forces need to be supplied to the human-walker system. In this paper, we add an active mode to guide the user in situations where the passive control mode alone with user-applied forces is not adequate for guidance. The theory of differential flatness is used to plan the trajectory of control gains within the proposed scheme of the controller. Since the user input force and slope angle of the path are not known a priori , the theory of model predictive control is used to periodically compute the trajectory of these control gains. The simulation and experiment results show that the walk-assist robot, along with the structure of this proposed control scheme, can guide the user to a goal on a slope effectively.
- Differential flatness
- model predictive control (MPC)
- slope guidance
- walk-assist robot