AMP2026: A Multi-Platform Marine Robotics Dataset for Tracking and Mapping
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , |
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| Format: | Preprint |
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2026
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| author | Meriaux, Edwin Wen, Shuo Widhalm, David Wang, Zhizun Shi, Junming Guzmán, Mariana Sosa Jakkala, Kalvik Carley, Bennett Sokolova, Elias Girdhar, Yogesh Roznere, Monika O'Kane, Jason Sattar, Junaed Dudek, Gregory |
| author_facet | Meriaux, Edwin Wen, Shuo Widhalm, David Wang, Zhizun Shi, Junming Guzmán, Mariana Sosa Jakkala, Kalvik Carley, Bennett Sokolova, Elias Girdhar, Yogesh Roznere, Monika O'Kane, Jason Sattar, Junaed Dudek, Gregory |
| contents | Marine environments present significant challenges for perception and autonomy due to dynamic surfaces, limited visibility, and complex interactions between aerial, surface, and submerged sensing modalities. This paper introduces the Aerial Marine Perception Dataset (AMP2026), a multi-platform marine robotics dataset collected across multiple field deployments designed to support research in two primary areas: multi-view tracking and marine environment mapping. The dataset includes synchronized data from aerial drones, boat-mounted cameras, and submerged robotic platforms, along with associated localization and telemetry information. The goal of this work is to provide a publicly available dataset enabling research in marine perception and multi-robot observation scenarios. This paper describes the data collection methodology, sensor configurations, dataset organization, and intended research tasks supported by the dataset. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_04225 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | AMP2026: A Multi-Platform Marine Robotics Dataset for Tracking and Mapping Meriaux, Edwin Wen, Shuo Widhalm, David Wang, Zhizun Shi, Junming Guzmán, Mariana Sosa Jakkala, Kalvik Carley, Bennett Sokolova, Elias Girdhar, Yogesh Roznere, Monika O'Kane, Jason Sattar, Junaed Dudek, Gregory Robotics Marine environments present significant challenges for perception and autonomy due to dynamic surfaces, limited visibility, and complex interactions between aerial, surface, and submerged sensing modalities. This paper introduces the Aerial Marine Perception Dataset (AMP2026), a multi-platform marine robotics dataset collected across multiple field deployments designed to support research in two primary areas: multi-view tracking and marine environment mapping. The dataset includes synchronized data from aerial drones, boat-mounted cameras, and submerged robotic platforms, along with associated localization and telemetry information. The goal of this work is to provide a publicly available dataset enabling research in marine perception and multi-robot observation scenarios. This paper describes the data collection methodology, sensor configurations, dataset organization, and intended research tasks supported by the dataset. |
| title | AMP2026: A Multi-Platform Marine Robotics Dataset for Tracking and Mapping |
| topic | Robotics |
| url | https://arxiv.org/abs/2603.04225 |