During the harvesting of polymetallic nodules on the seabed, the sediment plume due to disturbance on the seabed impacts the benthic ecosystem. A numerical simulation based on the SPH (smooth particle hydrodynamics) method is used to estimate the time and length scale of the plume impact near the seabed during a small-scale harvesting process. The simulation result considerably agrees with the one from the lab-scale water-channel experiment. It is found that, in the sediment plume, the traced sub-plume with iso-surface of lower sediment concentration travels a longer distance, and spends a longer time to achieve the stable state. Moreover, with the increase of the releasing rate of the disturbed sediment, the sub-plume spreads over greater distance, which also needs more time to achieve the stable state.

Subsea stratum is rich in natural gas hydrate. The subsea resources are gradually becoming the focus of exploration and development. Deep-sea stratum drilling robot is an emerging exploration equipment in the field of resources exploration in the subsea stratum. Deep-sea stratum drilling robot is characterized by low disturbance and high mobility, and it can enter the interior of the strata for in-situ exploration. Precise positioning information is a prerequisite for the controlled movement of the robot within the stratum. This paper proposes a positioning sensor cable that connects the robot to the subsea base station. The MEMS-IMU nodes are equidistantly and linearly arranged on the positioning sensor cable, and the reconstruction of the positioning sensor cable is realized by monitoring the change information of each section of the cable. The positioning of the robot in the stratum is achieved with the assistance of the positioning sensor cable. The experimental setup is built to verify the design principle of the positioning sensor cable and the reconstruction theory. The accuracy of the positioning sensor cable in the trajectory experiment meets the actual working conditions of deep-sea stratum drilling robot.

To enhance the sampling and exploration of the gas hydrate resources and other seafloor mineral resources within the seafloor sediment stratum, a deep-sea stratum drilling robot inspired by the earthworm’s peristaltic movement was developed in this paper. The support anchor unit is a part of this new type of robot. When the robot moves forward, it must rely on the support anchor unit to provide enough supporting force to counteract the various resistance forces on the front body units. In this paper, the maximum anchoring force of the support anchor unit, also known as the pullout force, is determined by theoretical calculation. The soil failure area during the pulling-out was obtained by simulation for visualization. The maximum anchoring force of the unit in the soil of different properties with different speeds was also obtained by tests to verify the theoretical calculations. And the effect of the support plates’ unfolding action on the maximum anchoring force was further analyzed in this research. The test results provide a helpful research basis for subsequent analysis of the robot’s movement pattern in soil and the effect of movement at different speeds.

As the exploitation of natural gas hydrates intensifies, there is a growing imperative to enhance the monitoring of extraction and storage areas. However, existing monitoring methods, such as seismic detection and seabed drilling technology, exhibit inherent limitations. These shortcomings primarily stem from challenges associated with conducting prolonged, in situ monitoring and the constrained scope of exploration. Addressing these shortcomings necessitates the development of innovative exploration methods or devices. This article introduces Stratloong, a novel underwater exploration robot designed specifically for drilling in seabed stratum. Comprising a drill bit, front and rear support units, and a propulsion unit, Stratloong emulates the peristaltic motion of an earthworm to achieve efficient drilling. In this research, kinematic and dynamic models of the robot are formulated, and a task-based control method based on inverse kinematic control is presented. In addition, a generic motion control framework is proposed to realize the drilling motion. Straight drilling tests are conducted in prepared seabed clay under different static settlement times to assess Stratloong's performance. Data collected include rotational speed, displacement, and axial force during motion. The robot maintained over 90% motion efficiency in the prepared seabed clay. Furthermore, outdoor tests confirmed the robot's ability to drill into soil without external thrust. The robot advanced 2230 mm with 89% motion efficiency. The comprehensive evaluation of Stratloong's drilling capabilities, conducted through a series of laboratory and field tests, yields valuable data and experiences for its potential application in seabed strata exploration.

Accurate and robust positioning of drilling robots within subsea strata is a critical prerequisite for deep-sea resource exploration and geological monitoring. However, conventional underwater and underground positioning methods are often ineffective due to severe signal attenuation in sediment. This paper proposes a novel fused positioning method specifically for subsea stratum drilling robots, which integrates a magnetic beacon system with a MEMS-IMUs array cable. A Piecewise Constant Curvature (PCC) kinematic model is established to reconstruct the spatial morphology of the array cable, providing a continuous position estimate free from temporal integration drift. This estimate is then fused with absolute position and orientation data derived from a magnetic dipole model of the beacon. To handle the high nonlinearity of the magnetic measurements and the complementary error characteristics of the two subsystems, we develop a tightly-coupled sensor fusion framework based on an Iterated Extended Kalman Filter with Leven-berg-Marquardt optimization (IEKF-LM). Simulation and experimental results demonstrate that the proposed system effectively overcomes the limitations of individual sensors. The array cable excels in near-field accuracy, while the magnetic beacon provides superior far-field performance. The IEKF-LM fusion algorithm successfully combines their strengths, achieving high-precision and robust localization in both static and dynamic scenarios simulating in-stratum conditions. The results indicate that the proposed fusion method effectively mitigates the limitations of individual sensor modalities, offering a viable positioning solution for subsea exploration robots.

Smart contracts, which are fundamental to DeFi financial systems, are vulnerable to exploitable bugs that can cause substantial monetary losses. A recent study shows that over 80% of these exploitable bugs, primarily functional bugs, evade detection by existing tools. Automatically identifying functional bugs in smart contracts is challenging from multiple perspectives. The primary issue is the significant gap between understanding the high-level logic of the business model and checking the low-level implementations in smart contracts. Furthermore, identifying deeply rooted functional bugs in smart contracts requires the automated generation of effective detection oracles based on various bug features. To address these challenges, we design PromFuzz++, an automated and scalable system for detecting functional bugs in smart contracts. In PromFuzz++, we first propose a dual-agent framework to identify potentially vulnerable functions for further analysis. We then implement a dual-stage coupling approach that generates invariant checkers using logic information extracted from these functions, enhancing bug-oriented fuzzing on target contracts. Our evaluation shows that PromFuzz++ achieves 86.96% recall and a 93.02% F1-score, improving both metrics by at least 50% over state-of-the-art methods. An in-depth analysis of 10 real-world DeFi projects uncovered 30 zero-day bugs, 24 of which have been assigned CVE IDs.