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In a three-dimensional system, multiple forces can act on an object. These forces can be combined into a single equivalent force, known as the resultant force. Similarly, the moments generated by these forces can be combined into a single equivalent moment, the resultant couple moment. In certain situations, these two entities may not be mutually perpendicular, meaning they do not have a 90-degree angle between them. This unique condition requires a deeper understanding of the interplay between...
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Ground Contact Force and Moment Estimation for Human-Exoskeleton Systems Using Dynamic Decoupled Coordinate System

Hongwu Li1, Haotian Ju1, Junchen Liu1

  • 1State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China.

Biomimetics (Basel, Switzerland)
|December 22, 2023
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Summary
This summary is machine-generated.

This study presents a novel sensor-free method to estimate exoskeleton foot-ground contact forces and moments (CFMs). The approach significantly reduces unknowns, enabling accurate CFM estimation and lowering development costs for exoskeletons.

Keywords:
dynamic decoupled coordinate systemexoskeletonground contact force and moment estimationminimum energy hypothesis

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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.