An optimized method for AUV trajectory model in benthonic hydrothermal area based on improved slime mold algorithm Article Swipe
Chunmeng Jiang
,
Yiming Tang
,
Jianguo Wang
,
Wenchao Zhang
,
Min Zhou
,
Jiaying Niu
,
Lei Wan
,
Guofang Chen
,
Gongxing Wu
,
Xide Cheng
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21278/brod75401
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.21278/brod75401
The optimization of the desired autonomous underwater vehicle (AUV) trajectory modeling and AUV trajectory tracking control in the benthonic hydrothermal area were studied. In the conventional trajectory tracking model construction methods, the time points were roughly combined with the position points of the planned path, making it difficult to produce a smooth trajectory. Although the spline interpolation method was an ideal option for smooth curves, a great number of points were needed for a complex desired trajectory mode. In response to the demanding requirements of AUV trajectory tracking control in the benthonic hydrothermal area, an under-actuated test platform was first established, and the cubic spline interpolation was adopted to process the preset path points for a smooth desired trajectory. An improved slime mold algorithm (SMA) was put forward to optimize the interpolating points used in the trajectory modeling. The Levy flight technology and the compactness technique to speed up the search process and increase the search accuracy. The simulation experiments were conducted in comparison with the artificial fish swarm algorithm (AFSA), the particle swarm optimization (PSO), and the compact cuckoo search (CCS). The results showed that the improved SMA shortened the search process, effectively avoided the local extreme values, and generated a high-precision desired trajectory model in a shorter time. The pool test also verified the feasibility and effectiveness of the proposed method. The method proposed in this study can satisfy the modeling of benthonic hydrothermal trajectory with a fewer number of nodes, faster search progress and search accuracy.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.21278/brod75401
- OA Status
- diamond
- Cited By
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400921592
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400921592Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21278/brod75401Digital Object Identifier
- Title
-
An optimized method for AUV trajectory model in benthonic hydrothermal area based on improved slime mold algorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-23Full publication date if available
- Authors
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Chunmeng Jiang, Yiming Tang, Jianguo Wang, Wenchao Zhang, Min Zhou, Jiaying Niu, Lei Wan, Guofang Chen, Gongxing Wu, Xide ChengList of authors in order
- Landing page
-
https://doi.org/10.21278/brod75401Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.21278/brod75401Direct OA link when available
- Concepts
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Trajectory, Hydrothermal circulation, Slime mold, Mold, Computer science, Algorithm, Marine engineering, Geology, Mathematical optimization, Engineering, Mathematics, Materials science, Physics, Composite material, Biology, Paleontology, Botany, AstronomyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.with | 37, 164, 237 |
| abstract_inverted_index.(AUV) | 8 |
| abstract_inverted_index.(SMA) | 124 |
| abstract_inverted_index.area, | 93 |
| abstract_inverted_index.cubic | 103 |
| abstract_inverted_index.fewer | 239 |
| abstract_inverted_index.first | 99 |
| abstract_inverted_index.great | 66 |
| abstract_inverted_index.ideal | 60 |
| abstract_inverted_index.local | 196 |
| abstract_inverted_index.mode. | 77 |
| abstract_inverted_index.model | 28, 205 |
| abstract_inverted_index.path, | 44 |
| abstract_inverted_index.slime | 121 |
| abstract_inverted_index.speed | 147 |
| abstract_inverted_index.study | 228 |
| abstract_inverted_index.swarm | 168, 173 |
| abstract_inverted_index.time. | 209 |
| abstract_inverted_index.(CCS). | 181 |
| abstract_inverted_index.(PSO), | 175 |
| abstract_inverted_index.cuckoo | 179 |
| abstract_inverted_index.faster | 243 |
| abstract_inverted_index.flight | 140 |
| abstract_inverted_index.making | 45 |
| abstract_inverted_index.method | 57, 224 |
| abstract_inverted_index.needed | 71 |
| abstract_inverted_index.nodes, | 242 |
| abstract_inverted_index.number | 67, 240 |
| abstract_inverted_index.option | 61 |
| abstract_inverted_index.points | 33, 40, 69, 113, 132 |
| abstract_inverted_index.preset | 111 |
| abstract_inverted_index.search | 150, 155, 180, 191, 244, 247 |
| abstract_inverted_index.showed | 184 |
| abstract_inverted_index.smooth | 51, 63, 116 |
| abstract_inverted_index.spline | 55, 104 |
| abstract_inverted_index.(AFSA), | 170 |
| abstract_inverted_index.adopted | 107 |
| abstract_inverted_index.avoided | 194 |
| abstract_inverted_index.compact | 178 |
| abstract_inverted_index.complex | 74 |
| abstract_inverted_index.control | 15, 88 |
| abstract_inverted_index.curves, | 64 |
| abstract_inverted_index.desired | 4, 75, 117, 203 |
| abstract_inverted_index.extreme | 197 |
| abstract_inverted_index.forward | 127 |
| abstract_inverted_index.method. | 222 |
| abstract_inverted_index.planned | 43 |
| abstract_inverted_index.process | 109, 151 |
| abstract_inverted_index.produce | 49 |
| abstract_inverted_index.results | 183 |
| abstract_inverted_index.roughly | 35 |
| abstract_inverted_index.satisfy | 230 |
| abstract_inverted_index.shorter | 208 |
| abstract_inverted_index.values, | 198 |
| abstract_inverted_index.vehicle | 7 |
| abstract_inverted_index.Although | 53 |
| abstract_inverted_index.combined | 36 |
| abstract_inverted_index.improved | 120, 187 |
| abstract_inverted_index.increase | 153 |
| abstract_inverted_index.methods, | 30 |
| abstract_inverted_index.modeling | 10, 232 |
| abstract_inverted_index.optimize | 129 |
| abstract_inverted_index.particle | 172 |
| abstract_inverted_index.platform | 97 |
| abstract_inverted_index.position | 39 |
| abstract_inverted_index.process, | 192 |
| abstract_inverted_index.progress | 245 |
| abstract_inverted_index.proposed | 221, 225 |
| abstract_inverted_index.response | 79 |
| abstract_inverted_index.studied. | 22 |
| abstract_inverted_index.tracking | 14, 27, 87 |
| abstract_inverted_index.verified | 214 |
| abstract_inverted_index.accuracy. | 156, 248 |
| abstract_inverted_index.algorithm | 123, 169 |
| abstract_inverted_index.benthonic | 18, 91, 234 |
| abstract_inverted_index.conducted | 161 |
| abstract_inverted_index.demanding | 82 |
| abstract_inverted_index.difficult | 47 |
| abstract_inverted_index.generated | 200 |
| abstract_inverted_index.modeling. | 137 |
| abstract_inverted_index.shortened | 189 |
| abstract_inverted_index.technique | 145 |
| abstract_inverted_index.artificial | 166 |
| abstract_inverted_index.autonomous | 5 |
| abstract_inverted_index.comparison | 163 |
| abstract_inverted_index.simulation | 158 |
| abstract_inverted_index.technology | 141 |
| abstract_inverted_index.trajectory | 9, 13, 26, 76, 86, 136, 204, 236 |
| abstract_inverted_index.underwater | 6 |
| abstract_inverted_index.compactness | 144 |
| abstract_inverted_index.effectively | 193 |
| abstract_inverted_index.experiments | 159 |
| abstract_inverted_index.feasibility | 216 |
| abstract_inverted_index.trajectory. | 52, 118 |
| abstract_inverted_index.construction | 29 |
| abstract_inverted_index.conventional | 25 |
| abstract_inverted_index.established, | 100 |
| abstract_inverted_index.hydrothermal | 19, 92, 235 |
| abstract_inverted_index.optimization | 1, 174 |
| abstract_inverted_index.requirements | 83 |
| abstract_inverted_index.effectiveness | 218 |
| abstract_inverted_index.interpolating | 131 |
| abstract_inverted_index.interpolation | 56, 105 |
| abstract_inverted_index.high-precision | 202 |
| abstract_inverted_index.under-actuated | 95 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 10 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.8600000143051147 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile.value | 0.61597461 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |