A Model-Based Method for Minimizing Reflected Motor Inertia in Off-board Actuation Systems: Applications in...

Area of Science:

• Robotics
• Biomechanics
• Mechanical Engineering

Background:

• Off-board actuation systems accelerate wearable robotic device development.
• High joint impedance in these systems hinders natural user movement.
• Minimizing reflected inertia is key to reducing undesirable joint impedance.

Purpose of the Study:

• To develop and validate a methodology for minimizing reflected inertia in off-board robotic actuation systems.
• To optimize motor and mechanical design parameters for reduced joint impedance in wearable robots.
• To enhance the backdrivability and user experience of exoskeletons.

Main Methods:

• Developed a grey-box model integrating biomechanics, human-device interface, Bowden cables, and motor dynamics.
• Utilized a constrained optimization routine with a library of 157 servo motors.
• Implemented the methodology in the design of an off-board knee exoskeleton case study.

Main Results:

• The optimization methodology successfully identified suitable motors and parameters for desired torque-velocity trajectories.
• The optimal configuration involved a specific large servo motor (Kollmorgen C133A) with optimized pulley and sheave sizes.
• The selected motor configuration met the torque and motion requirements for the knee exoskeleton.

Conclusions:

• The proposed methodology effectively minimizes reflected inertia, leading to reduced joint impedance in off-board actuation systems.
• This approach enables the design of more backdrivable exoskeletons, improving user interaction and experimental capabilities.
• The developed methodology and open-source code can be adopted by exoskeleton designers for future innovations.