Kinematic optimization and adaptive compliant synchronization control of a neck-shoulder massage robot
Traditional neck-shoulder rehabilitation devices exhibit limited interaction fidelity due to rigid mechanical structures and imprecise multi-axis synchronization when interfacing with nonlinear human soft tissue. This study aims to develop a dual-motor neck-shoulder massage robot featuring kinematic optimization and a hierarchical adaptive control architecture to achieve compliant force tracking and high-precision motion coordination. A crank-rocker mechanism, synthesized via kinematic optimization, generates biomimetic trajectories, complemented by a scissor-lift module for active depth adjustment. Within the control framework, an extended Kalman filter fuses multi-modal sensor data for real-time contact state estimation. An incremental Fuzzy PID controller accommodates the nonlinear stiffness of muscle tissue to ensure active compliance. Concurrently, a Robust Adaptive Cross-Coupling Synchronization (RACCS) algorithm regulates dual-motor coordination under variable loads. Validation with 45 subjects demonstrates a 30% tracking error reduction compared to open-loop baselines on the same hardware. Compliant force control precision is maintained within a 0.2 N margin, yielding over 90% target area coverage across the cervical and shoulder regions. Stability analysis confirms the robustness of the RACCS algorithm against heterogeneous load disturbances. This study contributes a kinematically optimized crank rocker and scissor lift mechanism together with a hierarchical adaptive control architecture for distributed dual motor systems. The integrated design manages nonlinear soft tissue impedance and offers a scalable platform for precise cervical fatigue relief in healthy subjects.