Field-Based Human-Centred Control on SO(3) for Assist-as-Needed Robotic Rehabilitation

Assist-as-needed (AAN) control can effectively improve the participation of the patient. However, the current research on attitude control in a manifold and also a special orthogonal group, SO(3), adapted to three-dimensional (3D) gait training and three-degree-of-freedom joint training is insufficient. The controller drives the patients to follow a timed trajectory and have the disadvantage of imposing a defined timing of movement. The deviation between patient and robot is neglected and the actual movement of human is not considered. Therefore, this study proposes a human-centred control method on SO(3) for AAN robotic rehabilitation. First, a feedback-stabilized closest attitude tracking algorithm is proposed to establish the angular velocity field and moment field on SO(3). And the framework of the field-based double-loop control is realised. The posture information of the human limbs is fed back to the controller through the sensing system, and the motion state of the human body is sensed in real-time, which is used as the basis for adjusting the torque to realise human-centred control. The experimental results show that different levels of adjustment torque are generated based on attitude deviations between the human and robot to verify the effectiveness of the designed controller.