Based on the investigation of the current development trends of deep-sea mining technologies, and in combination with the analysis of domestic and international literature and patent hotspots, three key technological fields of deep-sea mining were identified:collection, lifting, and surface support. Based on the systematic sorting of the core technologies in different fields, a review on the domestic and international research progress is presented in 10 core technologies, including ore crushing, ore collection, mining vehicle traveling, long-distance vertical pipeline transportation, anti-clogging and emergency escape for lifting pipelines, pump-free mineral transportation, underwater acoustic communication, mineral processing, launch and recovery, as well as heave compensation. A multi-dimensional quantitative assessment was conducted on China's advantages and disadvantages compared to the international level in the overall field of deep-sea mining and the three key technological fields of collection, lifting, and surface support. Comprehensive analysis indicates that at the current stage, the main shortcomings of China's deep-sea mining technologies include the low efficiency of core equipment, insufficient long-term reliability, inadequate understanding of deep-sea environmental disturbance mechanisms, and the lack of integrated coordinated operation in at-sea tests. The global challenges of deep-sea mining technology are mainly manifested in dynamic coordinated control under multi-field coupling, flow assurance and equipment reliability in long-distance vertical transportation, and environmental constraints and plume control. In the future, it is advisable for China to focus on breaking through core technologies, strengthening environmental impact assessment and monitoring, and conducting integrated system at-sea tests, so as to move toward the more systematical, smarter and eco-friendly technology, laying a foundation for China's future participation in deep-sea resource exploitation.

By reviewing the formulation process of the Draft Regulations on Exploitation of Mineral Resources in the Area (short for the "Exploitation Regulations") by the International Seabed Authority (ISA) and the US policies and legislations to unilaterally advance deep-sea mining in the international seabed area (short for the "Area"), this paper analyzes the game landscape of international legal regimes governing deep-sea mining from multiple perspectives, including core divergences over the Exploitation Regulations, differentiated interest demands of participating parties, and the impact of US unilateral practice. Based on the analysis results, some countermeasures are proposed, including promoting the ISA to optimize the review procedure of the Exploitation Regulations, petitioning the Seabed Disputes Chamber of the International Tribunal for the Law of the Sea to render an advisory opinion on the legality of US unilateral authorization of deep-sea mining in the Area, and actively applying for new exploration contract within the Area.

This paper reviews the research progress in numerical simulation of transport and dispersion of plumes generated during deep-sea mining. Based on the formation mechanisms of plumes, the differences between dynamics of collector plumes and midwater plumes are compared in terms of discharge, transport driven by buoyancy and passive advection. By comparing the advantages and disadvantages of widely used near-field and far-field numerical frameworks in terms of applicable scales, computational efficiency, and physical accuracy, the parameterization methods for key physical processes are illustrated. Aiming at the bottleneck of insufficient deep-sea environmental data, the limitations and core challenges in current laboratory flume experiments and in-situ observations for model verification are further analyzed. On this basis, a prospect for the development direction are finally offered, including integration of artificial intelligence and advanced data assimilation techniques with establishment of standardized model evaluation framework.

Based on the slope-climbing dynamic analysis of mining vehicles, models for traction, total resistance and sinkage were established with the characteristics of soft deep-sea sediment taken into consideration, and a passable slope threshold was also determined. An improved A^* path planning algorithm is proposed, which integrates multi-cost constraints to optimize the search efficiency and path quality, and employs a redundant node removal method and Bézier curve fitting for the post-processing smoothing of the path. Simulation results show that, compared with the traditional A^* algorithm, the proposed improved algorithm makes the total length of the path planned shortened by about 3% on average, reduces the travel time and energy consumption costs by over 60% on average, and decreases the total steering angle of the path by over 70% on average. It generates a global path with a lower comprehensive cost and smoother steering, effectively improving the safety and efficiency of deep-sea mining vehicle operations.

Based on sorting out all exploration contracts approved by the International Seabed Authority, progress in negotiations on exploitation regulations, and policy divergences among major countries, it is argued that controversies over deep-sea mining rules focus on environmental protection, benefit distribution, regulatory responsibilities and commercial feasibility. China has established a relatively complete resource layout in international seabed, and also solid technological foundation for deep-sea exploitation, yet still confronts with regulatory uncertainties, environmental pressure and constraints on commercialization. China shall actively participate in the formulation of international deep-sea mining rules, strengthen international cooperation, and coordinate resource security and ecological conservation, for promoting the commercial exploitation of deep-sea mineral resources.

A loosely coupled visual-inertial fusion positioning algorithm based on Extended Kalman Filter (EKF) is proposed, which adopts a visual algorithm for relative pose estimation. It takes a mining vehicle as an observation target to acquire low-frequency and high-precision global coordinates, and then fuses these data with high-frequency global coordinate information from the inertial navigation system (INS). Simulation results show that compared with the INS, the proposed fusion algorithm leads to the average position error reduced from 1.309 m to 0.026 m for rectangular trajectory and from 1.749 m to 0.028 m for serpentine trajectory, indicating a remarkable improvement. Further experiments have verified the feasibility of the proposed algorithm, which provides technical support for cooperative operation of robots under complex deep-sea working conditions.

To address the problems of high costs and significant risks associated with at-sea tests of a full-scale deep-sea tracked mining vehicle, as well as the difficulty of existing simulation platforms in balancing physical fidelity and computational real-time performance, a co-simulation platform was developed and validated based on Project Chrono and ROS 2. With Chrono as the physics solving core and ROS 2 as the communication framework, the platform integrates a soil contact model and the Morison hydrodynamic model. Validation results demonstrate that the error of the simulated initial sinkage relative to the theoretical value is 2.4%, and the tractive force-slip ratio curve yields a coefficient of determination (R²) of 0.98 when fitted with theoretical values. Under the optimal engineering mesh resolution, the Real-Time Factor (RTF) stabilizes between 1.2 and 1.5, meeting the requirements of hardware-in-the-loop testing. This platform is available foe secondary development and also boasts higher computational efficiency, making it superior to the mainstream commercial softwares such as Adams and RecurDyn. Featuring both engineering-level physical fidelity and open-source extensibility, this platform provides a reliable virtual testing environment for the iteration of control algorithms and prior dynamic analysis of deep-sea mining equipment.

In order to explore the motion and structural response of the hard riser for lifting in deep-sea mining under the combined effect of external marine environment and internal coarse-particle solid-liquid two-phase flow, a numerical model of two-way fluid-structure interaction between the internal and external fluids in the hard riser was established, and the displacement and stress characteristics of the riser were calculated. The numerical calculation results show that nodule size has minor effect on the maximum stress and maximum displacement of the hard riser. By contrast, conveying concentration and flow rate can significantly increase both parameters. In addition, compared with the working condition without vessel motion, the maximum stress of the riser can rise by 21.7%-52.1%, and the maximum displacement can increase by 182.1%-247.0% when vessel motion is taken into account, which indicates that vessel motion exerts a remarkable influence on the dynamic response of the hard riser.

The working principle and structural design method of the underwater feeder for deep-sea mining is presented in the paper. The discrete element method (DEM) is adopted to conduct a full-process simulation analysis of the dynamic feeding process of the feeder, which has been verified by land-based tests and water tank tests. It is found that at the rated rotational speed of 35 r/min, the actual feeding rate of the designed feeder reaches 11.1 t/h, which satisfies the design index of greater than 10 t/h; an eccentric feed inlet design can effectively reduce the resistance torque; and the error between the DEM simulation results and the land-based test results is controlled within 2%. A water tank test shows that the overall mineral collection rate exceeds 90%, which further verifies the reliability of the device under continuous underwater operation.

To improve the positioning accuracy and real-time performance of deep-sea mining equipment in complex nonlinear environments, a positioning data prediction algorithm was proposed based on Physics-Informed Neural Network (PINN). This method introduces the kinematic equations of deep-sea mining vehicle into the neural network structure, and achieves the synergistic fitting of sensor data and physical models by constructing a composite loss function integrating physical constraints. Furthermore, two test scenarios under different working conditions were constructed on the Gazebo simulation platform to systematically compare the prediction performance between the proposed PINN and a traditional Feedforward Neural Network (FNN). The results show that, compared with the FNN model, the PINN model reduces the mean absolute error (MAE) from 0.621 3 m to 0.128 3 m, the root mean square error (RMSE) from 0.674 0 m to 0.137 0 m, and the maximum error from 0.938 6 m to 0.196 2 m in working condition 1; while in working condition 2, the MAE is reduced from 0.823 9 m to 0.335 4 m, the RMSE from 0.935 2 m to 0.379 5 m, and the maximum error from 1.585 8 m to 0.640 2 m. PINN demonstrates significant advantages in extreme error control and robustness, exhibiting lower sensitivity to outliers under complex working conditions in particular.