Hostname: page-component-7b7567c8c-kwt9d Total loading time: 0 Render date: 2026-11-14T07:14:06.947Z Has data issue: false hasContentIssue false

A new kinetostatic model for humanoid robots using screw theory

Published online by Cambridge University Press:  22 January 2018

Gustavo S. Toscano
Affiliation:
Department of Automation and Systems Engineering (DAS), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil. E-mails: gustavotoscano@gmail.com, eugenio.castelan@ufsc.br
Henrique Simas
Affiliation:
Department of Mechanical Engineering (EMC), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil. E-mails: henrique.simas@ufsc.br, daniel.martins@ufsc.br
Eugênio B. Castelan
Affiliation:
Department of Automation and Systems Engineering (DAS), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil. E-mails: gustavotoscano@gmail.com, eugenio.castelan@ufsc.br
Daniel Martins
Affiliation:
Department of Mechanical Engineering (EMC), Federal University of Santa Catarina (UFSC), Florianópolis, Brazil. E-mails: henrique.simas@ufsc.br, daniel.martins@ufsc.br
Rights & Permissions [Opens in a new window]

Summary

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

This study presents a new kinetostatic model for humanoid robots (HRs). Screw theory, together with Assur virtual chains and Davies' method, provides the required tools for the proposal of both the kinematic and static parts of the kinetostatic model. Our kinetostatic model is able to estimate the forces and couples generated at the axes of each joint of the robot, as well as one unknown contact condition between the robot and the environment around it. The proposed model is also very versatile and free of fixed coordinates and, therefore, it allows for an estimate of a great amount of information on the HR. Some results, obtained from computer simulation, are presented to validate the versatility of the proposed technique.

Information

Type
Articles
Copyright
Copyright © Cambridge University Press 2018