In-Hand Admittance Controller for a Robotic Assistive Walker Based on Tactile Grasping Feedback

An intelligent assistive robotic walker can be a tremendous help to patients with mobility disorders, e.g., hemiplegia patients. However, at the same time, a full-size assistive walker could be difficult to steer due to the reduced balancing ability of the patient. An intuitive interface can provide a promising solution to the low operability of such robotized assistive devices. Commonly developed gait assistance methodologies perform real-time adjustment of admittance model parameters in a forward direction. However, such a variable admittance model often accidentally affects the rotation behavior as well, which can lead to reducing the operability of the robotic device. To resolve such operational issues, we propose an in-Hand Admittance Controller (i-HAC) as a novel physical human-robot interaction interface for a robotic assistive walker. i-HAC is composed of multiple admittance models based on grasping feedback from sensitive robotic skin placed on both handlebars of a robotic assistive walker. This controller is formulated as a multiple-point-mass-damper system and can generate intuitive movement in both single and dual grasping situations. We conduct two experiments to demonstrate the benefits of i-HAC on a full-sized robotic walker in going forward with single grasping and rotating with dual grasping in comparison to the conventional admittance controller. Our experimental studies show that i-HAC potentially reduces the operation effort by 85% in the single grasping case and improves rotation consistency by 93% in the dual grasping case.