Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.
Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domai...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2017-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC5706726?pdf=render |
| _version_ | 1828346396692971520 |
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| author | Jianjun Li Rubo Zhang Yu Yang |
| author_facet | Jianjun Li Rubo Zhang Yu Yang |
| author_sort | Jianjun Li |
| collection | DOAJ |
| description | Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution. |
| first_indexed | 2024-04-14T00:25:31Z |
| format | Article |
| id | doaj.art-419c2142f11943b78e806cfcfdf2c135 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-04-14T00:25:31Z |
| publishDate | 2017-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-419c2142f11943b78e806cfcfdf2c1352022-12-22T02:22:45ZengPublic Library of Science (PLoS)PLoS ONE1932-62032017-01-011211e018829110.1371/journal.pone.0188291Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.Jianjun LiRubo ZhangYu YangResearch on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution.http://europepmc.org/articles/PMC5706726?pdf=render |
| spellingShingle | Jianjun Li Rubo Zhang Yu Yang Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment. PLoS ONE |
| title | Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment. |
| title_full | Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment. |
| title_fullStr | Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment. |
| title_full_unstemmed | Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment. |
| title_short | Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment. |
| title_sort | multi auv autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment |
| url | http://europepmc.org/articles/PMC5706726?pdf=render |
| work_keys_str_mv | AT jianjunli multiauvautonomoustaskplanningbasedonthescrolltimedomainquantumbeecolonyoptimizationalgorithminuncertainenvironment AT rubozhang multiauvautonomoustaskplanningbasedonthescrolltimedomainquantumbeecolonyoptimizationalgorithminuncertainenvironment AT yuyang multiauvautonomoustaskplanningbasedonthescrolltimedomainquantumbeecolonyoptimizationalgorithminuncertainenvironment |