Multimodal Human–Robot Interaction for Walker-Assisted Gait

Human mobility is affected by different types of pathologies and also decreases gradually with age. In this context, Smart Walkers may offer important benefits for human assisted-gait in rehabilitation and functional compensation scenarios. This paper proposes a new interaction strategy for human-walker cooperation. The presented strategy is based on the acquisition of human gait parameters by means of data fusion from inertial measurement units and a laser range finder. This paper includes the mathematical formulation of the controller, simulations, and practical experimentation of the interaction strategy, in order to show the performance of the control system, including the parameter detection methodology. In the experimental study, despite the continuous oscillation during the walking, the parameter estimation was suitable for assisted ambulation, showing an appropriate adaptive behavior with changes in human linear velocity. Finally, the controller keeps the walker continuously following in front of the human gait, and it is shown how the walker orientation follows the human orientation during the real experiments.