A Following Control Method for Lower Limb Rehabilitation Robots Using MPC and Fiducial Marker System

Abstract

This study introduces a follow-control method for lower limb rehabilitation robots, leveraging model predictive control (MPC) and a Fiducial Marker system. As stroke incidence rises, leading to significant motor dysfunction, effective rehabilitation techniques have become crucial. The proposed method employs ARTag markers to accurately capture target positioning and posture information, while MPC ensures precise follow-control of the robotic system. Experimental validation confirms that this control strategy effectively maintains tracking accuracy within predefined error constraints, providing a safe and comfortable rehabilitation experience for patients. This approach underscores the potential of rehabilitation robots to improve recovery outcomes for individuals with lower limb impairments.