Ground Contact Force and Moment Estimation for Human-Exoskeleton Systems Using Dynamic Decoupled Coordinate System...

Area of Science:

• Robotics
• Biomechanics
• Sensor Technology

Background:

• Estimating foot-ground contact forces and moments (CFMs) is crucial for exoskeleton joint moment calculation.
• Current CFM detection methods rely on expensive, uncomfortable, and difficult-to-manufacture sensors.
• The double-support phase presents numerous unknown CFM components, complicating precise estimation.

Purpose of the Study:

• To propose a novel, sensor-free method for estimating contact forces and moments (CFMs) between exoskeletons and the ground.
• To reduce the complexity and cost associated with CFM detection in exoskeleton development.
• To overcome the challenges posed by unknown CFM components during the double-support phase.

Main Methods:

• Development of a dynamic decoupled coordinate system (DDCS) to decompose CFMs.
• Application of the minimum energy hypothesis to optimize remaining unknown variables.
• Validation of the proposed method using a public dataset of human walking.

Main Results:

• The DDCS significantly reduces the number of unknown CFM components from twelve to two.
• The minimum energy hypothesis provides a reliable optimization target for the reduced unknowns.
• Validation confirms the method's capability in accurately estimating CFMs.

Conclusions:

• The proposed sensor-free method offers a practical solution for estimating under-sole CFMs.
• This approach reduces exoskeleton research and development costs by eliminating the need for plantar sensors.
• The method decreases reliance on high-precision, portable, and comfortable CFM detection sensors.