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As the elderly population is rapidly growing in our society, robot walking helpers are receiving more attention these days. To be practical and safe for use in daily life, an important issue is whether these robot walking helpers can be effectively maneuvered and provide guidance to the users. These concerns become even more important for a passive robot walking helper, as it relies mainly on the user's applied forces to move. In this paper, we propose a motion guidance system for a passive robot walking helper. More specifically, we develop a system to identify user's intentions from applied grip forces. This system consists of a pair of force-sensing grips attached to the handles of the robot walking helper and a learning scheme for the mapping between the measured grip forces and the driving force/torque imposed on the helper. The learning scheme, combined with an assistive strategy extended from our previous work, provides motion guidance to the elders during walking. The feasibility of the proposed system is demonstrated via a series of experiments involving motion assistance with i-Go, a passive robot walking helper developed in our laboratory.

With increasing populations of the elderly in our society, robot 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 from the human to the walker, while the controller modulates 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 brief is how to modulate these proportional gains over time for the two wheels so that the walker can perform point-to-point motions. The unique contribution of this brief 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 forces are not known a priori , the trajectory of the braking gain is computed iteratively during the motion. Simulation and experimental results show that the walk-assist robot, along with the structure of this proposed control scheme, can guide the user to reach the goal.