Wearable Robot Design Optimization Using Closed-Form Human-Robot Dynamic Interaction Model

Area of Science:

• Robotics
• Biomechanics
• Human-Robot Interaction

Background:

• Wearable robots offer solutions for mobility disorders.
• Current design methods involve complex, costly simulations.
• Virtual prototyping is essential but computationally intensive.

Purpose of the Study:

• To propose a computationally efficient framework for designing wearable robots.
• To simplify the simulation of human-robot dynamic interactions.
• To optimize the design of lower-limb wearable robots.

Main Methods:

• Developed a framework to make the human-robot link segment system statically determinate.
• Utilized closed-form inverse dynamics for direct simulation.
• Employed a novel technique to estimate walking ground reactions from kinematic data.

Main Results:

• The framework is computationally efficient, transparent, and interpretable.
• Eliminated the need for optimization, detailed musculoskeletal modeling, and ground reaction force measurement.
• Successfully optimized joint positions and actuator requirements for a lower-limb wearable robot.

Conclusions:

• The proposed framework significantly advances wearable robot design.
• Offers a more efficient and accurate approach to simulating human-robot dynamics.
• Facilitates the development of effective assistive devices for mobility impairments.