Marine Autonomous Systems for Ocean Observation, Conservation, and Renewable Energy

The ocean regulates Earth’s climate, supports immense biodiversity and sustains billions of livelihoods, yet it remains under-sampled across many regions and timescales. Climate change, pollution, habitat loss, and illegal fishing are reshaping marine systems faster than ship-based surveys and fixed platforms alone can monitor. Autonomous and robotic platforms — including AUVs, gliders, uncrewed surface vehicles (USVs), profiling floats, and low-cost sensor networks — now offer sustained, adaptive observation across remote, dynamic, and hard-to-sample environments. Coupled with miniaturized sensors, onboard AI, and real-time communications, these systems can improve understanding of physical, biogeochemical, and ecological processes while supporting marine conservation and offshore renewable-energy management.

This Research Topic welcomes studies that use autonomous systems to improve ocean observation, reduce measurement uncertainty, and translate observations into scientific, environmental, or management outcomes. We are particularly interested in work on multi-vehicle coordination, fleets and swarms, edge computing, adaptive sampling, real-time data fusion, and FAIR/interoperable data workflows. Key questions include: How can autonomous platforms improve event-driven sampling of blooms, fronts, pollution plumes, ecosystem change, or offshore renewable-energy sites? How can onboard AI and edge processing extend endurance and support better decisions at sea? How can autonomous monitoring strengthen marine protected areas, biodiversity and habitat assessment, pollution detection, and carbon or biogeochemical observation? How can calibration and validation protocols ensure comparability with ship-based, moored, satellite, and other reference observations? And how can these data feed operational forecasting, ocean digital twins, and policy or management decisions?

We welcome Original Research, Methods, Technology and Code, Reviews, Perspectives, and Policy and Practice contributions. Submissions should show how autonomous deployment addresses a clear oceanographic, environmental, conservation, or renewable-energy observation challenge. Papers focused solely on hardware design are outside scope unless they demonstrate a direct improvement in observation capability, process understanding, uncertainty reduction, or decision support. Themes include, but are not limited to:

• Autonomous and robotic platforms, including AUVs, gliders, USVs, floats, and low-cost sensing systems that improve the coverage and resolution of ocean observations.
• Multi-platform coordination, adaptive/event-driven sampling, and onboard AI for resolving dynamic ocean processes.
• Data interoperability, FAIR practices, and integration of autonomous observations into ocean digital twins and forecasting systems.
• Autonomous monitoring for marine protected areas, biodiversity, habitats, pollution, and biogeochemical/carbon processes.
• AI-based approaches for ocean science using autonomous observations.
• Met-ocean and environmental observation around offshore renewable-energy sites, where it contributes to understanding coastal and shelf-sea processes or supports responsible site management.
• Methodologies for uncertainty reduction and cross-calibration between autonomous sensor payloads and standard ship-based, satellite, or fixed-mooring reference measurements.
• Quantifying the observational value added by autonomous fleets compared with traditional oceanographic sampling designs.