A Self-Coordinating Controller with Balance-Guiding Ability for Lower-Limb Rehabilitation Exoskeleton Robot

Area of Science:

• Robotics
• Biomechanics
• Rehabilitation Engineering

Background:

• Human-exoskeleton interaction (HEI) controllers can compromise patient balance due to restricted posture and compliance.
• Falls and loss of balance are significant risks during lower-limb exoskeleton-assisted rehabilitation.

Purpose of the Study:

• To develop a self-coordinated velocity vector (SCVV) double-layer controller with balance-guiding ability for lower-limb rehabilitation exoskeleton robots (LLRER).
• To enhance patient safety and stability during rehabilitation by preventing falls.

Main Methods:

• An adaptive trajectory generator was used in the outer loop to follow the gait cycle and create a hip-knee reference trajectory.
• Velocity control was implemented in the inner loop, coordinating desired velocity vectors based on the L2 norm between reference and current configurations.
• An electromechanical coupling model was used for simulations, and experiments were conducted with a developed exoskeleton device.

Main Results:

• The SCVV controller demonstrated effective balance-guiding capabilities.
• Simulations and experiments confirmed the controller's ability to self-coordinate velocity vectors for encouragement and correction.
• The developed controller enhanced stability during human-exoskeleton interaction.

Conclusions:

• The SCVV double-layer controller is effective for LLRERs, improving balance and safety.
• This controller offers a promising solution for more stable and effective lower-limb exoskeleton-assisted rehabilitation.
• The findings validate the controller's performance in both simulated and experimental settings.