Dynamic Target Hunting Under Autonomous Underwater Vehicle (AUV) Motion Planning Based on Improved Dynamic Window Approach (DWA) Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.3390/jmse13020221
A dynamic distributed target hunting method is proposed for the problem of distributed moving target hunting by multiple Autonomous Underwater Vehicles (AUVs). By integrating the improved Dynamic Window Approach (DWA) with the Rapidly-exploring Random Tree (RRT) algorithm and incorporating collision avoidance rules between AUVs into the evaluation system of the DWA, the collision avoidance rules are quantified, and corresponding evaluation functions are established. This allows for the selection of motion trajectories that comply with the collision avoidance rules from the predicted trajectory set, improving the obstacle avoidance capability during AUV motion planning and enhancing the reliability of the target hunting task. The introduction of a consistency algorithm maintains the consistency of the group task information and ensures that the hunting strategy can be adjusted promptly in the event of an AUV failure, allowing the target hunting task to continue. Polynomial regression algorithms are used to predict the moving target’s trajectory. Based on a polygonal hunting formation, the hunting potential points are dynamically allocated, and, finally, each AUV executes distributed motion planning towards the hunting potential points to form the hunting formation. Simulation results show that the proposed method achieves efficient multi-AUV-distributed dynamic target hunting.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/jmse13020221
- https://www.mdpi.com/2077-1312/13/2/221/pdf?version=1737727420
- OA Status
- gold
- Cited By
- 2
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4406799742
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4406799742Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/jmse13020221Digital Object Identifier
- Title
-
Dynamic Target Hunting Under Autonomous Underwater Vehicle (AUV) Motion Planning Based on Improved Dynamic Window Approach (DWA)Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-01-24Full publication date if available
- Authors
-
Juan Li, Huabing Lu, Honghan Zhang, Zihao ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/jmse13020221Publisher landing page
- PDF URL
-
https://www.mdpi.com/2077-1312/13/2/221/pdf?version=1737727420Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2077-1312/13/2/221/pdf?version=1737727420Direct OA link when available
- Concepts
-
Window (computing), Underwater, Computer science, Marine engineering, Motion (physics), Motion planning, Environmental science, Engineering, Artificial intelligence, Geology, Robot, Oceanography, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2Per-year citation counts (last 5 years)
- References (count)
-
27Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works_count | 27 |
| abstract_inverted_index.A | 0 |
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| abstract_inverted_index.target | 3, 14, 98, 134, 192 |
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| abstract_inverted_index.allocated, | 162 |
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| abstract_inverted_index.formation. | 180 |
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| abstract_inverted_index.information | 114 |
| abstract_inverted_index.integrating | 23 |
| abstract_inverted_index.quantified, | 56 |
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| abstract_inverted_index.incorporating | 38 |
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| citation_normalized_percentile.is_in_top_10_percent | True |