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Robot types机器人形态 › Underwater / marine水下 / 海洋

Underwater / marine水下 / 海洋

1 curated papers, code and datasets (0 with code) and 16 recent arXiv papers tagged “Underwater / marine”.1 个精选论文、代码与数据集(0 个附代码),以及 16 篇近期 arXiv 论文,均与「水下 / 海洋」相关。

Robot types are detected by keyword rules from titles, abstracts and tags, so a few papers may be misfiled.机器人形态由标题、摘要和标签中的关键词自动识别,个别论文可能归类有误。

Search by topic:按主题搜索: VLA & Robot Foundation ModelsVLA 与机器人基础模型 (3) · Manipulation & Dexterous Hands操作与灵巧手 (3) · Tactile & Visuotactile Sensing触觉与视触觉感知 (1) · Perception, SLAM & 3D Mapping感知、SLAM 与三维建图 (2) · Planning, Control & Safety规划、控制与安全 (2) · Robot Learning: RL & Imitation机器人学习:强化学习与模仿学习 (1) · Datasets & Benchmarks数据集与基准 (1)

Curated精选 (1)

Paper论文 2026 new新 2026-11-02

Embodied at Sea: Imitation Learning for Multi-Task Underwater Manipulation

Trains VLA models on 1,616 underwater episodes and grades 1,260 pool rollouts, best model 93.3% including partial successes. In a field case study at a WWII wreck, single-task ACT beat generalist SmolVLA 47.9% to 7.9%.用 1616 条水下数据训练 VLA,并在水池评估 1260 次,最佳模型成功率 93.3%(含部分成功)。在二战沉船实地案例中,单任务 ACT 以 47.9% 对 7.9% 明显胜过通用的 SmolVLA。

BibTeX
@misc{perezhaiek2026embodied,
  title = {{Embodied at Sea: Imitation Learning for Multi-Task Underwater Manipulation}},
  author = {Greta Perez-Haiek and Luca Macesanu and Kevin Angers and Mohammed Imam and Timothy Gambin and Christopher Clark},
  year = {2026},
  eprint = {2610.38199},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.38199},
}
VLA & Robot Foundation ModelsVLA 与机器人基础模型Underwater / marine水下 / 海洋underwaterfield-roboticsactreal

Recent arXiv papers近期 arXiv 论文 (Atom feedAtom 订阅)

arXiv cs.RO 2026-11-10

Reliability-Adaptive Multimodal Relative Pose Tracking for Underwater Leader-Follower Robots

Mingyang Yang, Zeyu Sha, Xiaorui Wang, Jun Wang et al.

Abstract摘要

Underwater leader-follower formation control requires continuous relative-pose estimation despite degraded sensing conditions and limited onboard computation. This paper presents a reliability-adaptive multimodal perception framework for six-degree-of-freedom relative-pose tracking between two moving underwater robots. The framework integrates complementary visual, acoustic-ranging, and hydrodynamic measurements while accounting for their distinct physical characteristics and time-varying reliability. It adaptively weights modality contributions and models temporal dependencies with linear …

BibTeX
@misc{yang2026reliability,
  title = {{Reliability-Adaptive Multimodal Relative Pose Tracking for Underwater Leader-Follower Robots}},
  author = {Mingyang Yang and Zeyu Sha and Xiaorui Wang and Jun Wang and David Chen Wang and Feitian Zhang},
  year = {2026},
  eprint = {2611.11940},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2611.11940},
}
arXiv cs.RO 2026-11-09

FATHOM: World-Model-Guided Diffusion Action-Trajectory Selection for Sparse-Marker AUV Tracking

Xiaorui Wang, Zeyu Sha, Mingyang Yang, David Chen Wang et al.

Abstract摘要

Reliable relative tracking is fundamental to cooperative autonomous underwater vehicles (AUVs), yet remains challenging under nonlinear vehicle dynamics and degraded underwater visual conditions. Active light markers improve robustness to appearance variation, but provide deliberately sparse observations that can become incomplete or corrupted by occlusion, reflections, and detection noise during dynamic motion. To address the resulting partial-observation control problem, this paper proposes FATHOM, a world-model-guided diffusion action-trajectory selection framework for sparse-marker AUV …

BibTeX
@misc{wang2026fathom,
  title = {{FATHOM: World-Model-Guided Diffusion Action-Trajectory Selection for Sparse-Marker AUV Tracking}},
  author = {Xiaorui Wang and Zeyu Sha and Mingyang Yang and David Chen Wang and Feitian Zhang},
  year = {2026},
  eprint = {2611.08898},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2611.08898},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-11-05

Cognitive and Behavioural Effects of Haptic Feedback for ROV Teleoperation in Hazardous Environments

Joshua Brown, Ildar Farkhatdinov, Michael Jenkin

Abstract摘要

Teleoperating a Remotely Operated Vehicle (ROV) in complex underwater environments presents unique challenges. Dynamic, three dimensional obstacles and unseen water currents pose real risks to expensive robotic hardware in environments in which recovery can be next to impossible. This paper explores the cognitive effects of haptic feedback to improve vehicle safety in such environments. An in-water study is analysed with a ROV exposed to controlled cross-currents, with environmental information presented via a soft and vibrating haptic touchpad. Results demonstrate that while encountering an …

BibTeX
@misc{brown2026cognitive,
  title = {{Cognitive and Behavioural Effects of Haptic Feedback for ROV Teleoperation in Hazardous Environments}},
  author = {Joshua Brown and Ildar Farkhatdinov and Michael Jenkin},
  year = {2026},
  eprint = {2611.06689},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2611.06689},
}
arXiv cs.RO 2026-11-05

A Layered View of LLM Support in Underwater Robotics

Federico Celi, Leonardo Zacchini, Gabriele Ferri

Abstract摘要

This extended abstract discusses a specific and, in our experience, practically relevant role for large language models (LLMs) in underwater robotics. Our main premise is that, in underwater fielding missions, the immediate difficulty is often not the synthesis of new low-level control laws, but the operation of complex robotic systems under limited communications, partial observability, and expensive field time. In particular, a significant fraction of the effort during sea trials is devoted to fault diagnosis, telemetry interpretation, mission adjustment, and coordination across …

BibTeX
@misc{celi2026layered,
  title = {{A Layered View of LLM Support in Underwater Robotics}},
  author = {Federico Celi and Leonardo Zacchini and Gabriele Ferri},
  year = {2026},
  eprint = {2611.06162},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2611.06162},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-11-04

LLM-Assisted Planning with Distributed Onboard Behaviour Tree Execution for Multi-AUV Missions

Ehsan Khorrambakht, Cristiano Caissutti, Andrea Munafo, Andrea Caiti

Abstract摘要

Coordinating autonomous underwater vehicles requires translating operator intent into feasible assignments while preserving autonomous execution when communication is limited. We present a hierarchical framework that couples Large Language Model (LLM) interpretation of natural-language mission instructions with Mixed-Integer Linear Programming (MILP) and distributed Behaviour Tree (BT) execution. The LLM extracts assignment and ordering constraints, which the MILP optimizer combines with vehicle capabilities and temporal requirements. A BT-LLM Bridge distributes the resulting allocations to …

BibTeX
@misc{khorrambakht2026llm,
  title = {{LLM-Assisted Planning with Distributed Onboard Behaviour Tree Execution for Multi-AUV Missions}},
  author = {Ehsan Khorrambakht and Cristiano Caissutti and Andrea Munafo and Andrea Caiti},
  year = {2026},
  eprint = {2611.04518},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2611.04518},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-11-03

When appearance and motion disagree: evaluating class--motion consistency against disguised uncrewed surface vessels

Jon Reifschneider

Abstract摘要

Defense systems for maritime assets must distinguish approaching benign craft from uncrewed surface vessels (USVs) with sufficient warning to act. Shore cameras using computer vision can separate hostile vessels from benign traffic, but these systems may be attacked using an adversarial hull patch or physical disguise. We evaluate adversarial hull patches and find they suppress detection in up to 29% of attempts but never cause misclassification as benign. Physical disguise, however, can bypass both a camera check and a radar presence check. To evaluate defenses, we develop a hybrid replay …

BibTeX
@misc{reifschneider2026when,
  title = {{When appearance and motion disagree: evaluating class--motion consistency against disguised uncrewed surface vessels}},
  author = {Jon Reifschneider},
  year = {2026},
  eprint = {2611.00367},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2611.00367},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-11-02

Interaction-Aware Sampling-Based Motion Planning for Autonomous Surface Vessels in Urban Waterways

Elia Trevisan, Alejandro Gonzalez-Garcia, Jan Swevers, Javier Alonso-Mora

Abstract摘要

Autonomous surface vessels operating in urban waterways must coordinate with other vessels in confined spaces while complying with traffic regulations, often without knowing their intentions. We present a decentralized motion planner based on model predictive path integral control, a sampling-based model predictive control scheme. The planner jointly computes a trajectory for the ego vessel and a prediction of the trajectories of the other vessels, and therefore accounts for their interaction. Traffic regulations are encoded as discontinuous costs, which the sampling-based formulation admits …

BibTeX
@misc{trevisan2026interaction,
  title = {{Interaction-Aware Sampling-Based Motion Planning for Autonomous Surface Vessels in Urban Waterways}},
  author = {Elia Trevisan and Alejandro Gonzalez-Garcia and Jan Swevers and Javier Alonso-Mora},
  year = {2026},
  eprint = {2610.41676},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.41676},
}
Planning, Control & Safety规划、控制与安全Underwater / marine水下 / 海洋
arXiv cs.RO 2026-11-02

AquaProbe: Efficient Adaptation of Frozen Vision Models for Underwater Images

Md Shihabul Islam Shovo, Nishi Kanta Paul, Trung Dong, Xiaomin Lin

Abstract摘要

Reliable visual perception is essential for safe autonomous underwater exploration. Yet vision models pretrained on terrestrial images become less reliable underwater, where turbidity, backscatter, and wavelength-dependent attenuation alter scene appearance. Existing adaptation methods either spread adapters equally across the encoder depth or select layers using the divergence between two fixed domains. In this paper, we introduce AquaProbe for measuring how the location of the domain gap changes with water type and imaging range. AquaProbe separates newly introduced divergence from that …

BibTeX
@misc{shovo2026aquaprobe,
  title = {{AquaProbe: Efficient Adaptation of Frozen Vision Models for Underwater Images}},
  author = {Md Shihabul Islam Shovo and Nishi Kanta Paul and Trung Dong and Xiaomin Lin},
  year = {2026},
  eprint = {2610.40900},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.40900},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-10-30

Embodied at Sea: Imitation Learning for Multi-Task Underwater Manipulation

Greta Perez-Haiek (New York University), Luca Macesanu (New York University), Kevin Angers (New York University), Mohammed Imam (New York University) et al.

Abstract摘要

Behavior Cloning has demonstrated promising generalization capabilities for robotic manipulation in terrestrial environments. However, marine visual distortions and dynamic currents create a severe domain shift that remains a key bottleneck in adapting generalist architectures to underwater field manipulation. To address this, 1616 episodes of underwater manipulation data were collected in calm and turbulent waters and were used to train 14 generalist Vision-Language-Action (VLA) models (DynamicVLA) with varying proprioception observation configurations. Across three tasks on 1260 gradable …

BibTeX
@misc{university2026embodied,
  title = {{Embodied at Sea: Imitation Learning for Multi-Task Underwater Manipulation}},
  author = {Greta Perez-Haiek (New York University) and Luca Macesanu (New York University) and Kevin Angers (New York University) and Mohammed Imam (New York University) and Timothy Gambin (University of Malta) and Christopher Clark (New York University)},
  year = {2026},
  eprint = {2610.38199},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.38199},
}
arXiv cs.RO 2026-10-28 code IROS 2026

SVIn+: Multi-Modal Framework for Robust Underwater State Estimation using 3D Sonar, Visual-Inertial, Water-Pressure, and DVL

Chinmay Burgul, Xiaoming Zhao, Yewei Huang, Michalis Chatzispyrou et al.

Abstract摘要

As expansion and scalability in underwater oper- ations becomes more important and challenging, autonomous underwater vehicles (AUVs) become more relevant and the necessity for reliable autonomy more critical. A fundamental challenge in any autonomous underwater operation, from control to safe navigation and mapping, is state estimation; a notorious hard problem to address, especially in low visibility conditions. In this paper, we tackle this problem, by presenting SVIn+, a multi-sensor framework for robust state estimation of AUVs equipped with an IMU, cameras, a water-pressure sensor, a …

BibTeX
@misc{burgul2026svin,
  title = {{SVIn+: Multi-Modal Framework for Robust Underwater State Estimation using 3D Sonar, Visual-Inertial, Water-Pressure, and DVL}},
  author = {Chinmay Burgul and Xiaoming Zhao and Yewei Huang and Michalis Chatzispyrou and Marios Xanthidis and Ioannis Rekleitis and Alberto Quattrini Li},
  year = {2026},
  eprint = {2610.36454},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.36454},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-10-20

A GPU-Resident Pipeline for Multi-Robot 3D Inspection with Limited Perception

Kry\v{s}tof P\v{s}eni\v{c}ka, Stefan Edelkamp

Abstract摘要

We present a complete, GPU-resident pipeline for multi-robot 3D inspection of underwater structures. Given a triangle mesh and a fleet of $K$ robots, each carrying a short-range, limited field-of-view camera, the pipeline computes 6-DOF trajectories that jointly cover a target fraction of the surface while minimizing a linearly interpolated makespan/total-cost objective. The joint problem is NP-hard, so we decompose it into five core stages - candidate viewpoint generation, visibility computation, set cover, min-max vehicle routing solved as a mixed integer program (MIP) with lifted …

BibTeX
@misc{pvsenivcka2026gpu,
  title = {{A GPU-Resident Pipeline for Multi-Robot 3D Inspection with Limited Perception}},
  author = {Kry\v{s}tof P\v{s}eni\v{c}ka and Stefan Edelkamp},
  year = {2026},
  eprint = {2610.26106},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.26106},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-10-20

AQUAACT: A Joystick-Level Underwater Teleoperation Dataset and Closed-Loop Benchmark

Zhenqi Wu, Trung Tien Dong, Aditya Penumarti, Mohamed A. Fouad et al.

Abstract摘要

Underwater robots support a growing range of work, from inspecting offshore structures and pipelines to surveying reefs and accompanying divers. Most of these tasks, however, are still flown by hand by a pilot, which raises the question of whether they can be carried out autonomously instead. On land, vision-language-action (VLA) models already let robots carry out tasks autonomously from language instructions, which makes them a natural candidate for taking the pilot's place. Underwater, however, there is little data to train such models. We take inspiration from how these tasks are flown …

BibTeX
@misc{wu2026aquaact,
  title = {{AQUAACT: A Joystick-Level Underwater Teleoperation Dataset and Closed-Loop Benchmark}},
  author = {Zhenqi Wu and Trung Tien Dong and Aditya Penumarti and Mohamed A. Fouad and Menna A. Fouad and Mingyang Mao and Jane Jaejeong Shin and Xiaomin Lin},
  year = {2026},
  eprint = {2610.25534},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.25534},
}
arXiv cs.RO 2026-10-20

Context-Aware RGB-Thermal-Radar Obstacle Perception for Resource-Constrained ASVs

Pranav Kedia, Edwin Redhead, Heiko Hamann

Abstract摘要

Reliable obstacle perception is challenging for small autonomous surface vessels (ASVs): reflections and glare confound visible-light cameras, vessel motion shifts the apparent waterline, and darkness removes the dominant sensing modality altogether. Rather than treating multimodal fusion as a static accuracy gain, we propose a context-aware architecture that combines RGB and long-wave infrared (LWIR) imagery, frequency-modulated continuous-wave (FMCW) mmWave radar, and inertial context. A bearing-sector interface provides the navigation controller with calibrated obstacle probabilities, …

BibTeX
@misc{kedia2026context,
  title = {{Context-Aware RGB-Thermal-Radar Obstacle Perception for Resource-Constrained ASVs}},
  author = {Pranav Kedia and Edwin Redhead and Heiko Hamann},
  year = {2026},
  eprint = {2610.23873},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.23873},
}
Underwater / marine水下 / 海洋
arXiv cs.RO 2026-10-14

Adaptive Prescribed Performance Trajectory Tracking for Uncertain Autonomous Underwater Vehicles With Input Saturation

Athanasios K. Gkesoulis, Christos Vlachos, George K. Fourlas, Charalampos P. Bechlioulis et al.

Abstract摘要

Accurate trajectory tracking is essential for autonomous underwater vehicles operating with uncertain hydrodynamics and limited thruster authority. This paper develops a low-complexity adaptive prescribed performance controller for uncertain underwater vehicle dynamics with coupled and saturated inputs. The proposed method adapts the performance functions directly through the mismatch between the requested and saturated control inputs, enlarging the performance funnels only when the available actuation cannot meet the nominal specifications. A coupled invariant-set analysis establishes …

BibTeX
@misc{gkesoulis2026adaptive,
  title = {{Adaptive Prescribed Performance Trajectory Tracking for Uncertain Autonomous Underwater Vehicles With Input Saturation}},
  author = {Athanasios K. Gkesoulis and Christos Vlachos and George K. Fourlas and Charalampos P. Bechlioulis and George C. Karras},
  year = {2026},
  eprint = {2610.20957},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.20957},
}
Planning, Control & Safety规划、控制与安全Underwater / marine水下 / 海洋
arXiv cs.RO 2026-10-14

Clarity-Driven Adaptive Mission Planning for a Solar-Powered Autonomous Surface Vessel

Kavin M. Govindarajan, Kaleb Ben Naveed, David Li, Devansh R. Agrawal et al.

Abstract摘要

This paper presents a comprehensive methodology, backed by simulation and experimental results, for an adaptive mission planning strategy that is mathematically grounded in the maximization of the information-driven quantity of clarity. In particular, the methodology introduced in this work addresses the use of sustainably powered autonomous surface vessels (ASVs) to perform scientific missions that prioritize locations of maximum interest. Because these locations of maximum interest are not known a priori but are rather identified based on in-situ measurements, online adaptation is essential …

BibTeX
@misc{govindarajan2026clarity,
  title = {{Clarity-Driven Adaptive Mission Planning for a Solar-Powered Autonomous Surface Vessel}},
  author = {Kavin M. Govindarajan and Kaleb Ben Naveed and David Li and Devansh R. Agrawal and Mary Maceda and Matthew Bryant and Dimitra Panagou and Chris Vermillion},
  year = {2026},
  eprint = {2610.20871},
  archivePrefix = {arXiv},
  primaryClass = {cs.RO},
  url = {https://arxiv.org/abs/2610.20871},
}
Underwater / marine水下 / 海洋
arXiv cs.CV 2026-10-14

Why 3D Reconstruction Breaks Down on Under-Ice AUV Video, and How to Predict It

Ana-Ştefania Kogălniceanu, Klára Orbán, Ashwin Nedungadi, Stefan Lüdtke et al.

Abstract摘要

Reconstruction of 3D structures using under-ice AUV video footage has been inaccurate, although it is not certain whether this is due to shortcomings in the methods or an inherent deficiency of the capture system. We test four different models for reconstruction on the same Antarctic under-ice AUV video (Icefin, Kamb Ice Stream): classical feature matching SfM, differentiable photometric splatting, volumetric depth fusion, and a pose-free feed-forward foundation model. All four fail, each in a distinct way: near-total registration yielding almost no structure, geometrically broken output …

BibTeX
@misc{kogalniceanu2026why,
  title = {{Why 3D Reconstruction Breaks Down on Under-Ice AUV Video, and How to Predict It}},
  author = {Ana-Ştefania Kogălniceanu and Klára Orbán and Ashwin Nedungadi and Stefan Lüdtke and Kuderna-Iulian Benţa},
  year = {2026},
  eprint = {2610.19993},
  archivePrefix = {arXiv},
  primaryClass = {cs.CV},
  url = {https://arxiv.org/abs/2610.19993},
}