A remote operations center framework for heterogeneous robotic zooplankton sampling: System design and field case study

Le résumé fourni par la source

Autonomous and heterogeneous marine robotic networks offer new possibilities for observing dynamic ocean phenomena beyond the limits of ship-centered and single-platform operations. Their scientific and operational value depends on coordinated system use: remote supervision, communication across constrained links, and onboard or near-real-time processing that converts raw sensor streams into compact information for live decision-making. This paper presents an evidence-based system framework for heterogeneous robotic operations in marine research coordinated through a Remote Operations Center (ROC). Zooplankton sampling is used as the motivating case because its patchy, dynamic biological structure is difficult to characterize efficiently with conventional ship-based approaches alone. The framework covers remote operation, edge processing and data quality, communication design, and targeted sampling with heterogeneous fleets. It is tested through a field case study conducted in Mausund, Norway, in 2024, where an autonomous underwater vehicle, two autonomous surface vehicles, and a support vessel were coordinated from a shore-based ROC approximately 100 km away. The results show that the ROC redistributed supervision, interpretation, and coordination from the field site to a shared shore-based environment, allowing these activities to continue in parallel with local launch, recovery, and support tasks. Compact edge-derived products made payload data more usable during operations, while layered communication design helped preserve command, coordination, and science-relevant information across links with varying capacity, latency, and reliability. The case study also showed how complementary platform roles supported broad-scale reconnaissance, local refinement, and targeted sampling. The findings indicate that the value of ROC-centered heterogeneous marine robotics lies in the combined observational capability of the system, linking platform roles, sensing, communication, coordination, and mission logic into one operational workflow.

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