Probabilistic Particle Filter Anchoring (PPFA): A Novel Perspective in Semantic World Modeling for Autonomous Underwater Vehicles With Acoustic and Optical Exteroceptive Sensors
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| Název: | Probabilistic Particle Filter Anchoring (PPFA): A Novel Perspective in Semantic World Modeling for Autonomous Underwater Vehicles With Acoustic and Optical Exteroceptive Sensors |
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| Autoři: | Alberto Topini, Alessandro Ridolfi |
| Zdroj: | IEEE Journal of Oceanic Engineering. 50:1065-1086 |
| Informace o vydavateli: | Institute of Electrical and Electronics Engineers (IEEE), 2025. |
| Rok vydání: | 2025 |
| Témata: | Automatic target recognition (ATR), autonomous underwater vehicles (AUVs), marine robotics, semantic underwater world modeling (WM) |
| Popis: | Creating an accurate world model of the scenario where an autonomous underwater vehicle is navigating can be considered a crucial stage for understanding the surrounding environment. As a result, the targets detected by an automatic target recognition (ATR) architecture alongside their localized positions, must be handled, selected, and filtered to get a symbolic representation of the underwater context. Even though the specific world modeling (WM) architecture may vary, current WM methodologies usually rely on the 3-D localization knowledge of the detected target by introducing a nonnegligible constraint. Motivated by the aforementioned considerations, a novel probabilistic particle filter anchoring (PPFA) approach has been developed. Starting from ATR 2-D results, the PPFA methodology aims at providing a semantic 3-D representation of the subsea environment by merging the upsides of both data association and object tracking, handled by a custom designed particle filter with resampling. |
| Druh dokumentu: | Article |
| Popis souboru: | application/pdf |
| ISSN: | 2373-7786 0364-9059 |
| DOI: | 10.1109/joe.2024.3492537 |
| Přístupová URL adresa: | https://hdl.handle.net/2158/1412792 https://ieeexplore.ieee.org/document/10839132 https://doi.org/10.1109/joe.2024.3492537 |
| Rights: | CC BY NC ND |
| Přístupové číslo: | edsair.doi.dedup.....f2461fcdc9318c8bad614acfec506a70 |
| Databáze: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstrakt: | Creating an accurate world model of the scenario where an autonomous underwater vehicle is navigating can be considered a crucial stage for understanding the surrounding environment. As a result, the targets detected by an automatic target recognition (ATR) architecture alongside their localized positions, must be handled, selected, and filtered to get a symbolic representation of the underwater context. Even though the specific world modeling (WM) architecture may vary, current WM methodologies usually rely on the 3-D localization knowledge of the detected target by introducing a nonnegligible constraint. Motivated by the aforementioned considerations, a novel probabilistic particle filter anchoring (PPFA) approach has been developed. Starting from ATR 2-D results, the PPFA methodology aims at providing a semantic 3-D representation of the subsea environment by merging the upsides of both data association and object tracking, handled by a custom designed particle filter with resampling. |
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| ISSN: | 23737786 03649059 |
| DOI: | 10.1109/joe.2024.3492537 |