[Trajectory planning and tracking control for upper limb traction rehabilitation training]

Area of Science:

• Robotics
• Control Systems Engineering
• Rehabilitation Medicine

Context:

• Rehabilitation robots face challenges with restricted interaction spaces and singular configurations during upper limb training.
• Existing methods may compromise patient safety and training efficacy due to these limitations.

Purpose:

• To propose a trajectory planning and tracking control scheme for rehabilitation robots that addresses safety concerns.
• To ensure safe human-robot interaction and avoid singular configurations in upper limb rehabilitation training.

Summary:

• A safe human-robot interaction space was defined using kinematics and rehabilitation theory.
• A trajectory planning method based on occupational therapy principles was developed.
• Singular configurations were avoided using an exponential adaptive damped least square method.
• A nonlinear controller utilizing backstepping and a radial basis function neural network for model-free control was designed.
• Controller stability was validated using Lyapunov stability theory.

Impact:

• The proposed control scheme enhances the safety and effectiveness of upper limb rehabilitation robot training.
• It demonstrates superior performance compared to existing methods in experimental evaluations.
• This advancement contributes to improved patient recovery and therapeutic outcomes.