Towards ice core sampling by subsea robotic vehicles

Abstract. Ice coring has developed into one of the most frequently used sampling methods across cryospheric sciences. Sea ice, firn and glacial ice are sampled using a range of different coring systems. These systems can retrieve core samples with lengths ranging from several cm to tens of meters when operated by hand or drilling machines, while specialized coring systems have retrieved cores from Antarctica's ice caps with a length of over 3 km. In the last decade more robotic subsea vehicles like remotely operated vehicles (ROV) and autonomous underwater vehicles (AUV) have ventured into polar waters beneath sea ice and ice shelves, but retrieval of ice samples from the sub-ice environment has not been achieved on a regular basis. Other geophysical investigation methods such as push core sediment coring and rock drilling have been successfully adapted for subsea robotic vehicles. Hence the purpose of this work is to investigate the feasibility of adapting the techniques of retrieving short ice cores from sea ice and glacial research to the subsea environment. We successfully demonstrate the retrieval of an ice sample in a laboratory setting using traditional ice coring systems in conjunction with a subsea manipulator arm. We discuss challenges and further improvements to our experiments towards enabling reliable ice sampling in the subsea environment using generic tooling readily available on subsea vehicles. In conclusion, ice core sampling in the subsea environment seems feasible using industrial work class manipulators particularly when cartesian inverse-kinematic control is available.

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Publication Details

Journal
Geoscientific instrumentation, methods and data systems
Published
2025-11-10
DOI
https://doi.org/10.5194/gi-14-311-2025
Primary Topic
Arctic and Antarctic ice dynamics
Type
article
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article

Towards ice core sampling by subsea robotic vehicles

Christian Katlein
Geoscientific instrumentation, methods and data systems
Arctic and Antarctic ice dynamics
article

Towards ice core sampling by subsea robotic vehicles

Christian Katlein
article en

Abstract

Abstract. Ice coring has developed into one of the most frequently used sampling methods across cryospheric sciences. Sea ice, firn and glacial ice are sampled using a range of different coring systems. These systems can retrieve core samples with lengths ranging from several cm to tens of meters when operated by hand or drilling machines, while specialized coring systems have retrieved cores from Antarctica's ice caps with a length of over 3 km. In the last decade more robotic subsea vehicles like remotely operated vehicles (ROV) and autonomous underwater vehicles (AUV) have ventured into polar waters beneath sea ice and ice shelves, but retrieval of ice samples from the sub-ice environment has not been achieved on a regular basis. Other geophysical investigation methods such as push core sediment coring and rock drilling have been successfully adapted for subsea robotic vehicles. Hence the purpose of this work is to investigate the feasibility of adapting the techniques of retrieving short ice cores from sea ice and glacial research to the subsea environment. We successfully demonstrate the retrieval of an ice sample in a laboratory setting using traditional ice coring systems in conjunction with a subsea manipulator arm. We discuss challenges and further improvements to our experiments towards enabling reliable ice sampling in the subsea environment using generic tooling readily available on subsea vehicles. In conclusion, ice core sampling in the subsea environment seems feasible using industrial work class manipulators particularly when cartesian inverse-kinematic control is available.

Geoscientific instrumentation, methods and data systemsVol. 14(2)
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung (DE)
Openalex Percentile: Top 62%
Arctic and Antarctic ice dynamics
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Towards ice core sampling by subsea robotic vehicles — Christian Katlein · Geoscientific instrumentation, methods and data systems (2025) | TGRS Research Map | TGRS