A groundbreaking milestone in ocean and storm science has been achieved with the first successful collection of in-situ data from inside a Category 5 hurricane by autonomous ocean robots developed by the UK-based company Oshen. These four-foot long, wind- and solar-powered unmanned surface vehicles (called C-Stars) were deployed in coordination with the National Oceanic and Atmospheric Administration (NOAA) and the University of Southern Mississippi during Hurricane Humberto. Multiple C-Stars penetrated the eyewall of the storm, transmitting high-resolution, real-time measurements of wind speed, air pressure, sea surface temperature, and humidity back to forecasters. One of the units recorded a minimum sea-level pressure of 955 millibars and wind gusts exceeding 150 miles per hour, providing critical surface-level data that was referenced in NOAA’s official hurricane forecast discussions. The success of these missions not only represents a world first for uncrewed ocean data collection in extreme conditions but also points toward a future where low-cost autonomous sensors could routinely supplement traditional hurricane observation systems and improve forecasting accuracy. Source reporting confirms Oshen’s expanding contracts with government agencies to deploy the technology in future research and defense applications, suggesting this innovation could reshape how scientists gather environmental data in hostile environments.
Sources:
https://techcrunch.com/2026/01/17/oshen-built-the-first-ocean-robot-to-collect-data-in-a-category-5-hurricane/
https://www.aoml.noaa.gov/mini-ocean-robot-collects-data-in-category-5-hurricane/
https://interestingengineering.com/innovation/tiny-ocean-robot-hurricane-data
Key Takeaways
- Oshen’s C-Star autonomous robots have become the first unmanned ocean vehicles to collect real-time data from inside a Category 5 hurricane, advancing oceanic and storm research capabilities.
- Partnership between Oshen, NOAA, and academic institutions enabled deployment of these robots during Hurricane Humberto, yielding critical environmental measurements used in official forecasting.
- Success in extreme storm conditions signals potential for future routine integration of autonomous ocean sensors to improve hurricane forecasting and climate research.
In-Depth
In a significant leap forward for environmental science and weather forecasting, autonomous ocean robots have now succeeded in collecting critical surface-level data from inside a Category 5 hurricane—an achievement that until recently was considered out of reach due to the sheer force and unpredictability of such storms. The robots, known as C-Stars, are developed by Oshen, a UK-based marine robotics startup founded in 2022. Designed to be low-cost, resilient, and capable of extended deployments at sea, these four-foot long unmanned surface vehicles (USVs) combine wind-powered propulsion with solar-powered sensors to gather and transmit meteorological and oceanographic information in real time.
The milestone mission took place during Hurricane Humberto, one of the most powerful storms of the 2025 Atlantic hurricane season. Oshen’s C-Stars were deployed as part of a collaborative effort with the U.S. National Oceanic and Atmospheric Administration (NOAA) and the University of Southern Mississippi, among others. Positioned in the projected path of Humberto near the U.S. Virgin Islands, the robots entered the storm in intervals over a period of hours. Unlike traditional observation platforms such as buoys or aircraft, which either cannot endure the extreme conditions of a Category 5 hurricane or can only capture fleeting snapshots from above, the C-Stars are engineered to weather the storm and maintain continuous contact with satellite networks. During the mission, one of the C-Stars recorded a minimum air pressure reading of 955 millibars and sustained hurricane-force winds exceeding 150 miles per hour, data points that were directly referenced in NOAA’s National Hurricane Center forecast discussions. This real-time surface information, transmitted every couple of minutes, offers forecasters a granular view of storm dynamics that was previously unavailable.
The success of these missions underscores a shift in how hurricane data can be collected and used. Traditional hurricane reconnaissance has relied heavily on aircraft flying into storms and remote sensing from satellites, both of which have limitations in terms of risk, cost, and the type of data they can gather. C-Stars bridge a critical gap by providing in-situ measurements—surface conditions that have historically been challenging to observe during the most violent phases of a storm. By transmitting data continuously from within the eyewall and surrounding regions, these robots enhance scientific understanding of storm structure and intensification, which in turn can improve forecast models and public warnings.
Beyond the immediate scientific impact, the broader implications of this technology are substantial. Oshen’s approach demonstrates how scalable and repeatable deployments of autonomous systems can provide persistent observation capabilities across vast and otherwise inaccessible ocean regions. The robots’ ability to operate for up to 100 days before retrieval means that they can gather long durations of data across multiple weather events, offering a far richer dataset than what has traditionally been possible. Moreover, the success of these missions has already spurred expanded contracts with government agencies, suggesting that the technology is transitioning from experimental to operational use in environmental monitoring and potentially national defense applications.
The evolution of these autonomous marine platforms dovetails with a wider trend toward unmanned systems augmenting human efforts in data collection and environmental monitoring. As global climate dynamics continue to produce stronger and more frequent extreme weather events, the demand for high-resolution, real-time data will only grow. The capability of C-Stars to survive and report from within the heart of the most destructive storms marks a pivotal development in our ability to understand and respond to nature’s most formidable forces. In a future where predictive accuracy can save lives and protect infrastructure, innovations like these ocean robots are not just engineering feats—they are practical tools for resilience.