Cargando…

Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties

Quadrupeds and hexapods are known by their ability to adapt their locomotive patterns to their functions in the environment. Computational modeling of animal movement can help to better understand the emergence of locomotive patterns and their body dynamics. Although considerable progress has been m...

Descripción completa

Detalles Bibliográficos
Autores principales: Arroyave-Tobon, Santiago, Drapin, Jordan, Kaniewski, Anton, Linares, Jean-Marc, Moretto, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921731/
https://www.ncbi.nlm.nih.gov/pubmed/35299633
http://dx.doi.org/10.3389/fbioe.2022.767914
_version_ 1784669384676999168
author Arroyave-Tobon, Santiago
Drapin, Jordan
Kaniewski, Anton
Linares, Jean-Marc
Moretto, Pierre
author_facet Arroyave-Tobon, Santiago
Drapin, Jordan
Kaniewski, Anton
Linares, Jean-Marc
Moretto, Pierre
author_sort Arroyave-Tobon, Santiago
collection PubMed
description Quadrupeds and hexapods are known by their ability to adapt their locomotive patterns to their functions in the environment. Computational modeling of animal movement can help to better understand the emergence of locomotive patterns and their body dynamics. Although considerable progress has been made in this subject in recent years, the strengths and limitations of kinematic simulations at the scale of small moving animals are not well understood. In response to this, this work evaluated the effects of modeling uncertainties on kinematic simulations at small scale. In order to do so, a multibody model of a Messor barbarus ant was developed. The model was built from 3D scans coming from X-ray micro-computed tomography. Joint geometrical parameters were estimated from the articular surfaces of the exoskeleton. Kinematic data of a free walking ant was acquired using high-speed synchronized video cameras. Spatial coordinates of 49 virtual markers were used to run inverse kinematics simulations using the OpenSim software. The sensitivity of the model’s predictions to joint geometrical parameters and marker position uncertainties was evaluated by means of two Monte Carlo simulations. The developed model was four times more sensitive to perturbations on marker position than those of the joint geometrical parameters. These results are of interest for locomotion studies of small quadrupeds, octopods, and other multi-legged animals.
format Online
Article
Text
id pubmed-8921731
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-89217312022-03-16 Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties Arroyave-Tobon, Santiago Drapin, Jordan Kaniewski, Anton Linares, Jean-Marc Moretto, Pierre Front Bioeng Biotechnol Bioengineering and Biotechnology Quadrupeds and hexapods are known by their ability to adapt their locomotive patterns to their functions in the environment. Computational modeling of animal movement can help to better understand the emergence of locomotive patterns and their body dynamics. Although considerable progress has been made in this subject in recent years, the strengths and limitations of kinematic simulations at the scale of small moving animals are not well understood. In response to this, this work evaluated the effects of modeling uncertainties on kinematic simulations at small scale. In order to do so, a multibody model of a Messor barbarus ant was developed. The model was built from 3D scans coming from X-ray micro-computed tomography. Joint geometrical parameters were estimated from the articular surfaces of the exoskeleton. Kinematic data of a free walking ant was acquired using high-speed synchronized video cameras. Spatial coordinates of 49 virtual markers were used to run inverse kinematics simulations using the OpenSim software. The sensitivity of the model’s predictions to joint geometrical parameters and marker position uncertainties was evaluated by means of two Monte Carlo simulations. The developed model was four times more sensitive to perturbations on marker position than those of the joint geometrical parameters. These results are of interest for locomotion studies of small quadrupeds, octopods, and other multi-legged animals. Frontiers Media S.A. 2022-03-01 /pmc/articles/PMC8921731/ /pubmed/35299633 http://dx.doi.org/10.3389/fbioe.2022.767914 Text en Copyright © 2022 Arroyave-Tobon, Drapin, Kaniewski, Linares and Moretto. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Arroyave-Tobon, Santiago
Drapin, Jordan
Kaniewski, Anton
Linares, Jean-Marc
Moretto, Pierre
Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties
title Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties
title_full Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties
title_fullStr Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties
title_full_unstemmed Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties
title_short Kinematic Modeling at the Ant Scale: Propagation of Model Parameter Uncertainties
title_sort kinematic modeling at the ant scale: propagation of model parameter uncertainties
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8921731/
https://www.ncbi.nlm.nih.gov/pubmed/35299633
http://dx.doi.org/10.3389/fbioe.2022.767914
work_keys_str_mv AT arroyavetobonsantiago kinematicmodelingattheantscalepropagationofmodelparameteruncertainties
AT drapinjordan kinematicmodelingattheantscalepropagationofmodelparameteruncertainties
AT kaniewskianton kinematicmodelingattheantscalepropagationofmodelparameteruncertainties
AT linaresjeanmarc kinematicmodelingattheantscalepropagationofmodelparameteruncertainties
AT morettopierre kinematicmodelingattheantscalepropagationofmodelparameteruncertainties