We present a computationally efficient algorithm for using variations in the ambient magnetic field to compensate for position drift in integrated odometry measurements (dead-reckoning estimates) through simultaneous localization and mapping (SLAM). When the magnetic field map is represented with a reduced-rank Gaussian process (GP) using Laplace basis functions defined in a cubical domain, analytic expressions of the gradient of the learned magnetic field become available. An existing approach for magnetic field SLAM with reduced-rank GP regression uses a Rao-Blackwellized particle filter (RBPF). For each incoming measurement, training of the magnetic field map using an RBPF has a computational complexity per time step of $O\left(N_p{N}_m^2\right)$, where $N_p$ is the number of particles, and $N_m$ is the number of basis functions used to approximate the Gaussian process. Contrary to the existing particle filter-based approach, we propose applying an extended Kalman filter based on the gradients of our learned magnetic field map for simultaneous localization and mapping. Our proposed algorithm only requires training a single map. It, therefore, has a computational complexity at each time step of $O\left(N_m^2\right)$. We demonstrate the workings of the extended Kalman filter for magnetic field SLAM on an open-source data set from a foot-mounted sensor and magnetic field measurements collected onboard a model ship in an indoor pool. We observe that the drift compensating abilities of our algorithm are comparable to what has previously been demonstrated for magnetic field SLAM with an RBPF.

Over the past decade, deep-sea mining (DSM) has received renewed interest due to scarcity of raw materials. Deep-sea mining has been spurred by the need for critical resources to support growing populations, urbanization, high-tech applications and the development of a green energy economy. Nevertheless, an improved understanding of how mining activities will affect the deep-sea environment is required to obtain more accurate assessment of the potential environmental impact. In that regard, the sediment plumes that are generated by the mining activity have received the highest concern, as these plumes might travel for several kilometers distance from the mining activity. Various plume sources are identified, of which the most profound are those generated by the excavation and collection process of the seafloor mining tool and the discharge flow to be released from the surface operation vessel after initial dewatering of the ore. In this review, we explore the physical processes that govern plume dispersion phenomena (focusing in the main on benthic plumes), discuss the state of the art in plume dispersion analysis and highlight what lessons can be learned from shallow water applications, such as dredging, to better predict and reduce the spread and impact of deep-sea mining plumes.

To date, hydraulic collection is the most widely considered technology in polymetallic-nodule mining, since there is no direct contact between hydraulic collectors and ocean floor. To construct a hydraulic collector that results in the least sediment disturbance, it is critical to develop an insightful understanding of the interaction between the collector and sediment bed. To this end, we conducted a set of small-scale experiments in which several operational conditions were tested, delivering the first quantitative data for sediment erosion resulting from a hydraulic collector driving over a sand bed. This paper presents and discusses the experimental results and observations. It is found that the collector’s forward velocity is inversely proportional to the bed-sediment erosion depth, since the bed is exposed to the flow for a longer time when the collector drives slower and vice versa. In contrast, an increased jet velocity leads to a larger erosion depth. Furthermore, when the collector underside is nearer to the sediment bed, a larger sediment layer is exposed to the water flow, resulting in a larger erosion depth. Finally, the experimental results show that collector water jets strike the sediment bed under an inclined angle, destabilizing the upper sediment layer and consequently dragging sediment particles along toward the collection duct and behind the collector head. This study improves the predictability of sediment erosion created by Coandă-effect-based collectors, which is a crucial asset to optimize the collector design and decrease the extent of the associated sediment plumes.

The interest in polymetallic nodule mining has considerably increased in the last few decades. This has been largely driven by population growth and the need to move towards a green future, which requires strategic raw materials. Deep-Sea Mining (DSM) is a potential source of such key materials. While harvesting the ore from the deep sea by a Polymetallic Nodule Mining Tool (PNMT), some bed sediment is unavoidably collected. Within the PNMT, the ore is separated from the sediment, and the remaining sediment–water mixture is discharged behind the PNMT, forming an environmental concern. This paper begins with surveying the state-of-the-art knowledge of the evolution of the discharge from a PNMT, in which the discharge characteristics and generation of turbidity currents are discussed. Moreover, the existing water entrainment theories and coefficients are analyzed. It is shown how plumes and jets can be classified using the flux balance approach. Following that, the models of Lee et al. (2013) and Parker et al. (1986) are combined and utilized to study the evolution of both the generated sediment plume and the subsequent turbidity current. The results showed that a smaller sediment flux at the impingement point, where the plume is transformed into a turbidity current, results in a shorter run-out distance of the turbidity current, consequently being more favorable from an environmental point of view.