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Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids
Motion planning for humanoid robots is one of the critical issues due to the high redundancy and theoretical and technical considerations e.g. stability, motion feasibility and collision avoidance. The strategies which central nervous system employs to plan, signal and control the human movements ar...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer International Publishing
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848286/ https://www.ncbi.nlm.nih.gov/pubmed/27186507 http://dx.doi.org/10.1186/s40064-016-2175-8 |
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author | Leylavi Shoushtari, Ali |
author_facet | Leylavi Shoushtari, Ali |
author_sort | Leylavi Shoushtari, Ali |
collection | PubMed |
description | Motion planning for humanoid robots is one of the critical issues due to the high redundancy and theoretical and technical considerations e.g. stability, motion feasibility and collision avoidance. The strategies which central nervous system employs to plan, signal and control the human movements are a source of inspiration to deal with the mentioned problems. Self-modeling is a concept inspired by body self-awareness in human. In this research it is integrated in an optimal motion planning framework in order to detect and avoid collision of the manipulated object with the humanoid body during performing a dynamic task. Twelve parametric functions are designed as self-models to determine the boundary of humanoid’s body. Later, the boundaries which mathematically defined by the self-models are employed to calculate the safe region for box to avoid the collision with the robot. Four different objective functions are employed in motion simulation to validate the robustness of algorithm under different dynamics. The results also confirm the collision avoidance, reality and stability of the predicted motion. |
format | Online Article Text |
id | pubmed-4848286 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-48482862016-05-16 Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids Leylavi Shoushtari, Ali Springerplus Research Motion planning for humanoid robots is one of the critical issues due to the high redundancy and theoretical and technical considerations e.g. stability, motion feasibility and collision avoidance. The strategies which central nervous system employs to plan, signal and control the human movements are a source of inspiration to deal with the mentioned problems. Self-modeling is a concept inspired by body self-awareness in human. In this research it is integrated in an optimal motion planning framework in order to detect and avoid collision of the manipulated object with the humanoid body during performing a dynamic task. Twelve parametric functions are designed as self-models to determine the boundary of humanoid’s body. Later, the boundaries which mathematically defined by the self-models are employed to calculate the safe region for box to avoid the collision with the robot. Four different objective functions are employed in motion simulation to validate the robustness of algorithm under different dynamics. The results also confirm the collision avoidance, reality and stability of the predicted motion. Springer International Publishing 2016-04-27 /pmc/articles/PMC4848286/ /pubmed/27186507 http://dx.doi.org/10.1186/s40064-016-2175-8 Text en © Leylavi Shoushtari. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Leylavi Shoushtari, Ali Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids |
title | Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids |
title_full | Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids |
title_fullStr | Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids |
title_full_unstemmed | Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids |
title_short | Robot body self-modeling algorithm: a collision-free motion planning approach for humanoids |
title_sort | robot body self-modeling algorithm: a collision-free motion planning approach for humanoids |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4848286/ https://www.ncbi.nlm.nih.gov/pubmed/27186507 http://dx.doi.org/10.1186/s40064-016-2175-8 |
work_keys_str_mv | AT leylavishoushtariali robotbodyselfmodelingalgorithmacollisionfreemotionplanningapproachforhumanoids |