A User- and Slope-Adaptive Control Framework for a Walking Aid Robot

Walking aid robots have been developed for elderly people or patients facing difficulties while walking. However, most of them are designed only for flat ground, must rely on handles, and have drawbacks such as oscillation and lack of stability. The primary goal of this research is to improve the transparency and safety of a walking aid robot, addressing both flat and sloping terrains. To achieve this goal, we propose a novel variable admittance control strategy for an omnidirectional mobile platform by combining human motion recognition and a slope-adaptive approach. We design a vision system with a wide-angle camera to capture skeletal whole-body information at a close distance to recognize the walking direction. Accordingly, the damping values of the admittance controller are varied. In addition, these parameters are varied with respect to the slope angle of the ground, which is detected by the platform. We validated the controller performance with eleven healthy subjects performing two experiments on both flat and sloping terrains. Three admittance controllers are compared, with fixed parameters, variable damping by Cartesian velocity, and variable damping by walking direction. Experimental results show the advantages of the variable admittance control based on walking direction, which ensures high transparency and smoothness on both flat and sloping terrains.