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

5 Citations (Scopus)

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
CountryDenmark
CityOdense
Period8/27/128/30/12

Fingerprint

Synergy
Synthesis
Controllers
Muscle
Controller
Kinematics
Dimensionality
Linear Combination
Control Problem
Scenarios
Output

Keywords

  • development
  • motor control
  • motor primitives

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Alessandro, C., Carbajal, J. P., & D'Avella, A. (2012). Synthesis and adaptation of effective motor synergies for the solution of reaching tasks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7426 LNAI, pp. 33-43). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7426 LNAI). https://doi.org/10.1007/978-3-642-33093-3_4

Synthesis and adaptation of effective motor synergies for the solution of reaching tasks. / Alessandro, Cristiano; Carbajal, Juan Pablo; D'Avella, Andrea.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7426 LNAI 2012. p. 33-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7426 LNAI).

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

Alessandro, C, Carbajal, JP & D'Avella, A 2012, Synthesis and adaptation of effective motor synergies for the solution of reaching tasks. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7426 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7426 LNAI, pp. 33-43, 12th International Conference on Simulation of Adaptive Behavior, SAB 2012, Odense, Denmark, 8/27/12. https://doi.org/10.1007/978-3-642-33093-3_4
Alessandro C, Carbajal JP, D'Avella A. Synthesis and adaptation of effective motor synergies for the solution of reaching tasks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7426 LNAI. 2012. p. 33-43. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-33093-3_4
Alessandro, Cristiano ; Carbajal, Juan Pablo ; D'Avella, Andrea. / Synthesis and adaptation of effective motor synergies for the solution of reaching tasks. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7426 LNAI 2012. pp. 33-43 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{0b57ec4b670c4a538de6744138c6a396,
title = "Synthesis and adaptation of effective motor synergies for the solution of reaching tasks",
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.",
keywords = "development, motor control, motor primitives",
author = "Cristiano Alessandro and Carbajal, {Juan Pablo} and Andrea D'Avella",
year = "2012",
doi = "10.1007/978-3-642-33093-3_4",
language = "English",
isbn = "9783642330926",
volume = "7426 LNAI",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "33--43",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Synthesis and adaptation of effective motor synergies for the solution of reaching tasks

AU - Alessandro, Cristiano

AU - Carbajal, Juan Pablo

AU - D'Avella, Andrea

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

KW - development

KW - motor control

KW - motor primitives

UR - http://www.scopus.com/inward/record.url?scp=84866013345&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84866013345&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-33093-3_4

DO - 10.1007/978-3-642-33093-3_4

M3 - Conference contribution

SN - 9783642330926

VL - 7426 LNAI

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 33

EP - 43

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -