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Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm
With the development of aerospace engineering, the space on-orbit servicing has been brought more attention to many scholars. Obstacle avoidance planning of space manipulator end-effector also attracts increasing attention. This problem is complex due to the existence of obstacles. Therefore, it is...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4842205/ https://www.ncbi.nlm.nih.gov/pubmed/27186473 http://dx.doi.org/10.1186/s40064-016-2157-x |
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author | Zhou, Dongsheng Wang, Lan Zhang, Qiang |
author_facet | Zhou, Dongsheng Wang, Lan Zhang, Qiang |
author_sort | Zhou, Dongsheng |
collection | PubMed |
description | With the development of aerospace engineering, the space on-orbit servicing has been brought more attention to many scholars. Obstacle avoidance planning of space manipulator end-effector also attracts increasing attention. This problem is complex due to the existence of obstacles. Therefore, it is essential to avoid obstacles in order to improve planning of space manipulator end-effector. In this paper, we proposed an improved ant colony algorithm to solve this problem, which is effective and simple. Firstly, the models were established respectively, including the kinematic model of space manipulator and expression of valid path in space environment. Secondly, we described an improved ant colony algorithm in detail, which can avoid trapping into local optimum. The search strategy, transfer rules, and pheromone update methods were all adjusted. Finally, the improved ant colony algorithm was compared with the classic ant colony algorithm through the experiments. The simulation results verify the correctness and effectiveness of the proposed algorithm. |
format | Online Article Text |
id | pubmed-4842205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-48422052016-05-16 Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm Zhou, Dongsheng Wang, Lan Zhang, Qiang Springerplus Research With the development of aerospace engineering, the space on-orbit servicing has been brought more attention to many scholars. Obstacle avoidance planning of space manipulator end-effector also attracts increasing attention. This problem is complex due to the existence of obstacles. Therefore, it is essential to avoid obstacles in order to improve planning of space manipulator end-effector. In this paper, we proposed an improved ant colony algorithm to solve this problem, which is effective and simple. Firstly, the models were established respectively, including the kinematic model of space manipulator and expression of valid path in space environment. Secondly, we described an improved ant colony algorithm in detail, which can avoid trapping into local optimum. The search strategy, transfer rules, and pheromone update methods were all adjusted. Finally, the improved ant colony algorithm was compared with the classic ant colony algorithm through the experiments. The simulation results verify the correctness and effectiveness of the proposed algorithm. Springer International Publishing 2016-04-23 /pmc/articles/PMC4842205/ /pubmed/27186473 http://dx.doi.org/10.1186/s40064-016-2157-x Text en © Zhou et al. 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 Zhou, Dongsheng Wang, Lan Zhang, Qiang Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm |
title | Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm |
title_full | Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm |
title_fullStr | Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm |
title_full_unstemmed | Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm |
title_short | Obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm |
title_sort | obstacle avoidance planning of space manipulator end-effector based on improved ant colony algorithm |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4842205/ https://www.ncbi.nlm.nih.gov/pubmed/27186473 http://dx.doi.org/10.1186/s40064-016-2157-x |
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