Upper limb exoskeleton rehabilitation robot inverse kinematics modeling and solution method based on multi-objective...

Area of Science:

• Robotics
• Biomechanics
• Rehabilitation Engineering

Background:

• The inverse kinematics of exoskeleton rehabilitation robots is complex due to the lack of standard analytical models.
• Redundant upper limb exoskeletons face challenges in adapting to human anatomy, hindering rehabilitation effectiveness.

Purpose of the Study:

• To propose a multi-objective optimization method for solving the inverse kinematics of upper limb exoskeleton robots.
• To enhance the adaptability and motion quality of redundant upper limb exoskeletons for rehabilitation.

Main Methods:

• Developed a multi-objective inverse kinematics model incorporating end-position, joint comfort, energy consumption, safety, and human-like constraints.
• Employed the Improved Equilibrium Optimization (IEO) algorithm to solve the inverse kinematics problem.
• Validated the method on a self-developed redundant upper limb exoskeleton rehabilitation robot system.

Main Results:

• The proposed method efficiently solves inverse kinematics for redundant upper limb exoskeletons.
• Incorporating joint comfort, energy consumption, and human-like constraints significantly improves the robot's motion shape.
• The IEO algorithm demonstrated superior solution accuracy and robustness compared to other algorithms.

Conclusions:

• Multi-objective optimization with the IEO algorithm provides an effective solution for upper limb exoskeleton inverse kinematics.
• This approach enhances the performance and human-like motion of rehabilitation robots.
• The method offers a robust and accurate solution for complex robotic rehabilitation systems.