# NTNU Underwater Multi-Camera Piloted underwater robot runs with five cameras and an inertial unit, as native `.mcap` episodes. Ariel, the NTNU Autonomous Robots Lab’s underwater robot built on the BlueROV2 Heavy configuration, is piloted through the Trondheim Fjord and the Marine Cybernetics Laboratory pool. An Alphasense rig records five monochrome cameras, a forward stereo pair and cameras looking up, left and right, with a 200 Hz inertial unit, while the vehicle’s autopilot logs a second inertial unit, a barometer, a downward rangefinder and the thruster outputs. Each run carries the authors’ ReAqROVIO reference trajectory and the rig’s calibration. 8 runs, 6 in the fjord and 2 in the pool, 63 minutes 19 seconds of recording, 379,896 camera frames and 759,943 inertial samples over 1,439 m of reference trajectory. **Details** - Dataset name: `ntnu-underwater-multicam` - Dataset source: [https://huggingface.co/datasets/Voxel51/NTNU-Underwater-Multicam](https://huggingface.co/datasets/Voxel51/NTNU-Underwater-Multicam) - Dataset size: 1.31 GB - Dataset license: BSD-3-Clause - Tags: `multimodal, mcap, underwater, robotics, slam` - Supported splits: `N/A` - ZooDataset class: [`NTNUUnderwaterMulticamDataset`](../../api/fiftyone.zoo.datasets.base.md#fiftyone.zoo.datasets.base.NTNUUnderwaterMulticamDataset) **Example usage** Python CLI ```python import fiftyone as fo import fiftyone.zoo as foz dataset = foz.load_zoo_dataset("ntnu-underwater-multicam") # The deepest dives view = dataset.sort_by("max_depth_m", reverse=True) session = fo.launch_app(dataset, view=view) ``` ```shell fiftyone zoo datasets load ntnu-underwater-multicam fiftyone app launch ntnu-underwater-multicam ```