Tacit adaptability of a mechanically adjustable compliance and controllable equilibrium position actuator, a preliminary study

Guillermo Asín-Prieto*, Shingo Shimoda, José González, M. Carmen Sánchez-Villamañán, Jose L Pons, Juan C. Moreno

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Current powered exoskeleton (exo) control algorithms for locomotion assistance and rehabilitation are based on assistive, resistive and error augmentation paradigms. Within the assistive controller’s family, assist-as-needed consists in applying a corrective force proportional to the error (actual limb position versus reference pattern). Our final goal is to implement a fully adaptable control mechanism to allow a full lower limb exo to dynamically adapt the gait pattern to each patient. We propose to use a modified version of tacit learning algorithm in combination with a variable stiffness actuator to explore the improvement of the adaptability in comparison to stiff actuators. The preliminary results show that using this concept on a compliant actuator it is possible to modulate a fixed trajectory to adapt to the position limits that are induced by user’s movement capabilities.

Original languageEnglish (US)
Title of host publicationBiosystems and Biorobotics
PublisherSpringer International Publishing
Pages267-271
Number of pages5
DOIs
StatePublished - 2017

Publication series

NameBiosystems and Biorobotics
Volume16
ISSN (Print)2195-3562
ISSN (Electronic)2195-3570

ASJC Scopus subject areas

  • Biomedical Engineering
  • Mechanical Engineering
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Tacit adaptability of a mechanically adjustable compliance and controllable equilibrium position actuator, a preliminary study'. Together they form a unique fingerprint.

Cite this