A Novel Upper Limb Rehabilitation Framework Based on Dual-Arm Robotics for Therapist-Like Traction Training
Gao Lin, Fei Wang, Shuai Han
AI summary
Problem
Traditional therapist-led traction training is safe and compliant but suffers from low repeatability and high clinician workload, while existing end-effector and exoskeleton robots cannot simultaneously provide adaptability and precise joint control.
Approach
The proposed framework uses a dual-arm robot to learn therapist traction characteristics from a single demonstration via a potential field controller and leader-follower coordination, while an 8-DOF kinematic model enforces strict task and joint space safety constraints.
Key results
- Accurate 8-DOF upper limb kinematic model for workspace evaluation
- Non-redundant inverse kinematics solver with dual task/joint safety constraints
- Potential field control strategy emulating therapist traction from a single demonstration
- Integrated leader-follower control enabling compliant, therapist-like human-robot interaction
Why it matters
Enables scalable, safe, and personalized upper limb rehabilitation that bridges clinical therapist expertise with robotic consistency for both clinical and home settings.
Abstract
In this letter, we propose a novel upper limb rehabil- itation framework based on dual-arm robotics for therapist-like traction training. Prioritizing patient safety, an 8-DOF kinematic model of the upper limb is derived to evaluate the reachable workspace of the palm center and proximal forearm during interaction with a dual-arm robot. Leveraging the characteristics of dual-arm rehabilitation, a non-redundant inverse kinematics method is proposed to constrain joint angles, thereby establishing a safety mechanism under dual constraints. Secondly, considering the training science and compliance, a potential field control strategy is introduced to enable the robot to learn the therapist’s traction characteristics from a single demonstration. Combined with the leader-follower control, it reproduces the therapist’s assistance and allows for compliant interaction. Experimental results show that the proposed framework combines the strong adaptability and comfort of end-effector robots with the precise rehabilitation of exoskeleton robots. As dual-arm and humanoid robots become more widely adopted, the proposed scheme holds promise for delivering therapist-like safe, scientific, and compli- ant rehabilitation in clinical and home settings.