Abstract

In this work, we propose an intuitive and real-time model of the human arm active endpoint stiffness. In our model, the symmetric and positive-definite stiffness matrix is constructed through the eigendecomposition , where is an orthonormal matrix whose columns are the normalized eigenvectors of , and is a diagonal matrix whose entries are the eigenvalues of . In this formulation, we propose to construct and directly by exploiting the geometric information from a reduced human arm skeleton structure in 3D and from the assumption that human arm muscles work synergistically when co-contracted. Through the perturbation experiments across multiple subjects under different arm configurations and muscle activation states, we identified the model parameters and examined the modeling accuracy. In comparison to our previous models for predicting human active arm endpoint stiffness, the new model offers significant advantages such as fast identification and personalization due to its principled simplicity. The proposed model is suitable for applications such as teleoperation, human–robot interaction and collaboration, and human ergonomic assessments, where a personalizable and real-time human kinodynamic model is a crucial requirement.

Highlights

  • The current generation of robotic manipulators has triggered new application scenarios in which robots can enter into direct interactions with unknown environments or humans to perform complex tasks [1]

  • The average (AVG), standard deviation (SD) and coefficient of variation (CV) of the parameters were calculated across subjects

  • The reason behind is that α1 and α2 are closely related to the arm skeleton dimensions and which do not have much difference within the subjects in our experiment. c1 and c2 are closely related to the strength of the muscles, which may have large difference across the subjects

Read more

Summary

Introduction

The current generation of robotic manipulators has triggered new application scenarios in which robots can enter into direct interactions with unknown environments or humans to perform complex tasks [1]. The online human impedance estimation techniques were first proposed under the concept of teleimpedance control [22], for real-time transferring of human arm stiffness to teleoperated robots To extend this model to a larger arm workspace, the theory of the common mode stiffness (CMS) and configuration dependent stiffness (CDS) was proposed in [23]. As a continuation of our developments in this direction, in this work, we proposed a new, principally simplified, and intuitive online model of the human arm endpoint stiffness which significantly reduces the total unknown parameters to 4 and without computation of above Jacobians. The accuracy of the proposed model K c was evaluated by using the collected stiffness samples for evaluation K eval

Evaluation
Formulation
Identification of Model Parameters
Experiment Setup
Experiment Protocols
Data Processing
Results
Discussion and Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call