Synthesis and adaptation of effective motor synergies for the solution of reaching tasks

Cristiano Alessandro, Juan Pablo Carbajal, Andrea D'Avella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Taking inspiration from the hypothesis of muscle synergies, we propose a method to generate open loop controllers for an agent solving point-to-point reaching tasks. The controller output is defined as a linear combination of a small set of predefined actuations, termed synergies. The method can be interpreted from a developmental perspective, since it allows the agent to autonomously synthesize and adapt an effective set of synergies to new behavioral needs. This scheme greatly reduces the dimensionality of the control problem, while keeping a good performance level. The framework is evaluated in a planar kinematic chain, and the quality of the solutions is quantified in several scenarios.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages33-43
Number of pages11
Volume7426 LNAI
DOIs
Publication statusPublished - 2012
Event12th International Conference on Simulation of Adaptive Behavior, SAB 2012 - Odense, Denmark
Duration: Aug 27 2012Aug 30 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7426 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other12th International Conference on Simulation of Adaptive Behavior, SAB 2012
Country/TerritoryDenmark
CityOdense
Period8/27/128/30/12

Keywords

  • development
  • motor control
  • motor primitives

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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