A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge
In this paper, we present a novel method to predict human motion, seeking to combine the advantages of both data-based and knowledge-based motion prediction methods. Our method relies on a database of captured motions for reference and introduces knowledge in the prediction in the form of a motion c...
| Autores: | , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Universidad de Navarra |
| Repositorio: | Dadun. Depósito Académico Digital de la Universidad de Navarra |
| Idioma: | inglés |
| OAI Identifier: | oai:dadun.unav.edu:10171/68441 |
| Acceso en línea: | https://hdl.handle.net/10171/68441 |
| Access Level: | acceso abierto |
| Palabra clave: | Human motion prediction. Digital human modeling. Dynamic motion prediction. Data-based motion prediction. Knowledge-based motion prediction. |
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A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledgePasciuto, I. (Ilaria)|||/items/cf344005-02b7-4b06-ab0a-8a7240dd0094Ausejo-Muñoz, S. (Sergio)|||/items/cd194120-763f-4fea-b1eb-0ad4425199b7Celigüeta-Lizarza, J.T. (Juan Tomás)|||/items/8aba2c9e-1004-4bc1-96c7-b6ab99557cb5Suescun-Cruces, A. (Ángel)|||/items/0958796a-0767-4a70-a623-db3686d1474bCazón-Martín, A.(Aitor)|||/items/baf52694-9508-4123-8541-385c320ad0c9Human motion prediction.Digital human modeling.Dynamic motion prediction.Data-based motion prediction.Knowledge-based motion prediction.In this paper, we present a novel method to predict human motion, seeking to combine the advantages of both data-based and knowledge-based motion prediction methods. Our method relies on a database of captured motions for reference and introduces knowledge in the prediction in the form of a motion control law, which is followed while resembling the actually performed reference motion. The prediction is carried out by solving an optimization problem in which the following conditions are imposed to the motion: must fulfill the goals of the task; resemble the reference motion selected from the database; follow a knowledge-based dynamic motion control law; and ensure the dynamic equilibrium of the human model, considering its interactions with the environment. In this work, we apply the proposed method to a database of clutch pedal depression motions, and we present the results for three predictions. The method is validated by comparing the results of the prediction to motions actually performed in similar conditions. The predicted motions closely resemble the motions in the validation database and no significant differences have been noted either in the motion's kinematics or in the motion's dynamics.SpringerDadun. Depósito Académico Digital Universidad de Navarra20242024-01-1920142014-01-0120142014-01-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10171/68441reponame:Dadun. Depósito Académico Digital de la Universidad de Navarrainstname:Universidad de NavarraInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:dadun.unav.edu:10171/684412026-06-21T12:47:57Z |
| dc.title.none.fl_str_mv |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge |
| title |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge |
| spellingShingle |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge Pasciuto, I. (Ilaria)|||/items/cf344005-02b7-4b06-ab0a-8a7240dd0094 Human motion prediction. Digital human modeling. Dynamic motion prediction. Data-based motion prediction. Knowledge-based motion prediction. |
| title_short |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge |
| title_full |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge |
| title_fullStr |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge |
| title_full_unstemmed |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge |
| title_sort |
A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge |
| dc.creator.none.fl_str_mv |
Pasciuto, I. (Ilaria)|||/items/cf344005-02b7-4b06-ab0a-8a7240dd0094 Ausejo-Muñoz, S. (Sergio)|||/items/cd194120-763f-4fea-b1eb-0ad4425199b7 Celigüeta-Lizarza, J.T. (Juan Tomás)|||/items/8aba2c9e-1004-4bc1-96c7-b6ab99557cb5 Suescun-Cruces, A. (Ángel)|||/items/0958796a-0767-4a70-a623-db3686d1474b Cazón-Martín, A.(Aitor)|||/items/baf52694-9508-4123-8541-385c320ad0c9 |
| author |
Pasciuto, I. (Ilaria)|||/items/cf344005-02b7-4b06-ab0a-8a7240dd0094 |
| author_facet |
Pasciuto, I. (Ilaria)|||/items/cf344005-02b7-4b06-ab0a-8a7240dd0094 Ausejo-Muñoz, S. (Sergio)|||/items/cd194120-763f-4fea-b1eb-0ad4425199b7 Celigüeta-Lizarza, J.T. (Juan Tomás)|||/items/8aba2c9e-1004-4bc1-96c7-b6ab99557cb5 Suescun-Cruces, A. (Ángel)|||/items/0958796a-0767-4a70-a623-db3686d1474b Cazón-Martín, A.(Aitor)|||/items/baf52694-9508-4123-8541-385c320ad0c9 |
| author_role |
author |
| author2 |
Ausejo-Muñoz, S. (Sergio)|||/items/cd194120-763f-4fea-b1eb-0ad4425199b7 Celigüeta-Lizarza, J.T. (Juan Tomás)|||/items/8aba2c9e-1004-4bc1-96c7-b6ab99557cb5 Suescun-Cruces, A. (Ángel)|||/items/0958796a-0767-4a70-a623-db3686d1474b Cazón-Martín, A.(Aitor)|||/items/baf52694-9508-4123-8541-385c320ad0c9 |
| author2_role |
author author author author |
| dc.contributor.none.fl_str_mv |
Dadun. Depósito Académico Digital Universidad de Navarra |
| dc.subject.none.fl_str_mv |
Human motion prediction. Digital human modeling. Dynamic motion prediction. Data-based motion prediction. Knowledge-based motion prediction. |
| topic |
Human motion prediction. Digital human modeling. Dynamic motion prediction. Data-based motion prediction. Knowledge-based motion prediction. |
| description |
In this paper, we present a novel method to predict human motion, seeking to combine the advantages of both data-based and knowledge-based motion prediction methods. Our method relies on a database of captured motions for reference and introduces knowledge in the prediction in the form of a motion control law, which is followed while resembling the actually performed reference motion. The prediction is carried out by solving an optimization problem in which the following conditions are imposed to the motion: must fulfill the goals of the task; resemble the reference motion selected from the database; follow a knowledge-based dynamic motion control law; and ensure the dynamic equilibrium of the human model, considering its interactions with the environment. In this work, we apply the proposed method to a database of clutch pedal depression motions, and we present the results for three predictions. The method is validated by comparing the results of the prediction to motions actually performed in similar conditions. The predicted motions closely resemble the motions in the validation database and no significant differences have been noted either in the motion's kinematics or in the motion's dynamics. |
| publishDate |
2014 |
| dc.date.none.fl_str_mv |
2014 2014-01-01 2014 2014-01-01 2024 2024-01-19 |
| dc.type.none.fl_str_mv |
journal article http://purl.org/coar/resource_type/c_6501 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
https://hdl.handle.net/10171/68441 |
| url |
https://hdl.handle.net/10171/68441 |
| dc.language.none.fl_str_mv |
Inglés eng |
| language_invalid_str_mv |
Inglés |
| language |
eng |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
| dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
open access http://purl.org/coar/access_right/c_abf2 |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Springer |
| publisher.none.fl_str_mv |
Springer |
| dc.source.none.fl_str_mv |
reponame:Dadun. Depósito Académico Digital de la Universidad de Navarra instname:Universidad de Navarra |
| instname_str |
Universidad de Navarra |
| reponame_str |
Dadun. Depósito Académico Digital de la Universidad de Navarra |
| collection |
Dadun. Depósito Académico Digital de la Universidad de Navarra |
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1869425296469393408 |
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15,300719 |