Current upper-limb rehabilitation robots primarily focus on training tasks involving free movements or static interactions with rigid objects. These paradigms lack simulation of complex object manipulation tasks encountered in daily life, thereby limiting the training of patients’ high-level sensorimotor integration capabilities. To address this gap, this study proposes an innovative robotic rehabilitation training system designed for functional occupational therapy. Specifically, the task of transporting a water cup was abstracted into a cup–ball system integrated with a robotic arm. The ball was modeled as a point mass, and kinematic and dynamic analyses of the system were conducted. A visual tracking method was employed to monitor the ball’s motion and calculate its slosh angle. Owing to the impaired fine motor control in stroke patients, a sloshing suppression control strategy integrating exponential filtering, feedforward force compensation, and impedance control was proposed to prevent the ball from spilling. Experiments validated the effectiveness of the proposed method. The results indicated that with full compensation, the oscillation rate of the ball was significantly reduced, and the smoothness of the hand force was markedly improved. This study presents an effective method for addressing dynamic uncertainty in rehabilitation robot training, thus significantly improving the functional relevance of the training.
Bai et al. (Thu,) studied this question.