Tamaki Ura’s research while affiliated with The University of Tokyo and other places

This article describes a multiyear survey of cobalt-rich manganese crust (Mn-crust) deposits using multiple underwater robots. Using two autonomous underwater vehicles and one remotely operated vehicle, mounted with camera systems, multibeam sonar, and subbottom sensors, large areas were surveyed by incorporating the advantages of each robot to create a comprehensive database of Mn-crust distribution estimates. The robots clocked in a total of 438 hours of seafloor observation, surveying about 589 km of seafloor in different locations. Specific use cases of the survey methodology and example results showing how each sensor contributes to the understanding of Mn-crust distribution are shown. The results from this survey can be combined with ship base multibeam data for seamount-scale estimates of Mn-crust volumetric distribution with high accuracy.

A major advantage of Autonomous Underwater Vehicles (AUVs) is that it is possible to operate a greater number of them simultaneously thanks to their autonomous and cable-less characteristics. However, the more AUVs are operating at the same time, the more difficult it becomes to control them. One of the solutions to this problem is to use an Autonomous Surface Vehicle (ASV) and this allows the mother ship to focus on ASV operations and emergency response. In 2017, National Maritime Research Institute (NMRI) developed an ASV for AUV control and operated it with multiple AUVs for a seafloor resources survey. In this operation, the ASV collected data on the AUV's status and transmitted it in radio communication, making it possible the mother ship to focus on launch and recovery operations. In this paper, we introduce the results of the ASV operation to control the AUVs along with the development and sea trials of the ASV.

Cesium-enriched particles released from the Fukushima Daiich Nuclear Power Plant (NPP1) exist in the Fukushima coastal waters and offshore, and they possibly affect the wide-area distribution of the radioactive cesium measured by the towed spectrometer. Therefore, the distribution of them in marine sediment was measured near NPP1 in November, 2016. We scanned the seafloor using a remotely operated vehicle (ROV) equipped with a NaI(Tl) scintillation detector. The sediment samples were obtained on the survey line by the ROV’s suction-type sampler. Five cesium particles, with diameters of approximately 400 μ m, were isolated from the samples. The radioactivity of 137 C s was less than 360 Bq, and no nuclides other than 134 C s , 137 C s , and natural radioactive ones were found from gamma-ray spectroscopy. In the particles, titanium and calcium were commonly detected by energy-dispersive X-ray spectrometry. We also estimated the particles’ presence from the change in the total counting rate of the scintillation detector. The average particle density is found to be 3.45 × 10 − 2 m − 1 at most. The average increase in the counting rate directly above the cesium-enriched particles in the sediment was less than double. Therefore, the effect of such particles on the distribution of radioactive cesium is limited.

Manganese crusts (Mn-crusts) are a type of mineral deposit that exists on the surface of seamounts and guyots at depths of >800 m. We have developed a method to efficiently map their distribution using data collected by autonomous underwater vehicles and remotely operated vehicles. Volumetric measurements of Mn-crusts are made using a high-frequency subsurface sonar and a 3-D visual mapping instrument mounted on these vehicles. We developed an algorithm to estimate Mn-crust distribution by combining continuous subsurface thickness measurements with the exposed surface area identified in 3-D maps. This is applied to data collected from three expeditions at Takuyo Daigo seamount at depths of ∼1400 m. The transects add to ∼11 km in length with 12 510 m2 mapped. The results show that 52% of the surveyed area is covered by Mn-crusts with a mean thickness of 69.6 mm. The mean Mn-crust occurrence is 69.6 kg/m2 with a maximum of 204 kg/m2 in the mapped region. The results are consistent with estimates made from samples retrieved from the area, showing more detailed distribution patterns and having significantly lower uncertainty bounds for regional-scale Mn-crust inventory estimation.

Autonomous underwater vehicles (AUVs) have become promising tools for marine geological surveys to collect information such as the topography of the seafloor and the location of hydrothermal plumes. Visual surveys and sampling are mainly conducted using human‐occupied vehicles or remotely operated vehicles. To obtain detailed visual data more efficiently, a hovering‐type AUV (Hobalin), which has the novel ability to autonomously navigate within a vent field, was developed to explore hydrothermal deposits. This vehicle was deployed in an active hydrothermal vent field located in the western offshore of Kumejima Island at a depth of approximately 1,400 m. Visual observations were performed with submillimeter image resolution via low‐altitude navigation using still cameras. Moreover, a height estimation method for chimney structures was proposed utilizing an obstacle avoidance system composed of a sheet laser and a forward‐looking camera with hovering maneuver capability. It was determined that hovering‐type AUVs can facilitate the effective survey of hydrothermal vents and the acquired data can be utilized for subsequent sampling by human‐occupied vehicles and remotely operated vehicles.

The ability to land on the seafloor expands the envelope of tasks that underwater vehicles can carry out during survey and inspection. However, even though remotely operated vehicles routinely land during their operations, autonomous underwater vehicles (AUVs) lack the sensing and data processing capabilities needed to identify safe, stable landing sites. Here, an algorithm is developed that uses millimeter-resolution (mm-resolution) bathymetry to detect regions where an AUV of known geometry can safely and stably land on the seafloor. The algorithm uses physical models that consider vehicle geometry, seafloor slope, roughness, friction, and currents. It can identify the most suitable of multiple candidate sites based on a landing cost function. The performance of the algorithm is evaluated using seafloor bathymetry data that was obtained using an AUV equipped with a high-resolution laser mapping system on the slopes of the Takuyo Daigo seamount in the Northwest Pacific. The algorithm successfully identified multiple landing sites along a 500-m transect on the slopes of the surveyed seamount. The study demonstrates that safe, reliable AUV landing operation is feasible in actual seafloor environments.

Measurement techniques using a towed gamma ray spectrometer allows to map the continuous distribution of 137Cs on the seafloor within 30 km of the F1NPP. This study has revealed that the temporal change in the 137Cs concentration does not show a constant rate of decrease. Furthermore, the local 137Cs anomalies, with concentrations of 137Cs one or two order of magnitude higher than the surrounding seafloors, is influenced by local features of the bathymetric feature.<br/