Eddy current sensors are commonly used for defect detection; however, research on their application to offshore platforms remains limited. In this paper, we propose a flexible eddy current array sensor with a soft protective layer. A customized polyurethane material is introduced as the soft protective layer, enabling the sensor to conform to complex curved surfaces while extending its service life. Through COMSOL finite element simulation, the influence of sensor parameters on detection sensitivity was systematically analyzed, leading to the identification of optimal sensor structural parameters and the detection accuracy under ideal conditions. Experimental results demonstrate that the sensor successfully detected a crack with dimensions of 1 mm in length, 0.2 mm in width, and 1 mm in depth, providing an effective sensing technology solution for long-term and efficient health monitoring of offshore platform steel structures.

A soft underwater robot based on functional gradient material is designed to have a streamlined flat head structure and an ellipsoidal tail structure connected by a functional gradient material bulging out the membrane. The cavity inside the flat head expands after inflation, causing the gradient membrane to bulge out directionally, and the cavity in the tail compresses to form a water jet to drive the robot forward. Comparative analysis with the bulging effect of homogeneous membranes is conducted to determine the robot's optimal motion state. The optimal inflation and deflation times are designed as 3 and 1 s, respectively, with a driving pressure of 15 kPa. Under these conditions, the periodic motion process of the underwater soft robot is verified, achieving an optimal motion speed of 0.446 BL/s-similar to 79.83% improvement compared to the robot using a homogeneous bulging membrane.

During installation of deepwater drilling systems, unintended contact between the blowout preventer (BOP) and the subsea wellhead may occur due to platform motions, posing a critical threat to wellhead integrity. Accurate assessment of such transient impacts remains challenging because global riser-BOP dynamics and highly localized wellhead responses are strongly coupled across multiple scales. In this study, a coupled global-local dynamic method is proposed to investigate axial and lateral BOP-wellhead impact behavior under installation scenarios. A global platform-riser-BOP model is first used to obtain time-domain kinematic parameters, which are then transferred to a high-fidelity local finite element wellhead model to resolve transient impact responses. Based on impact simulations, the response mechanisms of axial and lateral collisions are clarified and critical safety criteria are identified. Results show that axial impact response is primarily governed by the impact velocity, with a critical threshold of 0.6 m/s, while the influence of acceleration is secondary. Lateral impacts remain within elastic limits under typical platform maneuvering velocities. By mapping local failure thresholds back to the global model, practical axial and lateral safety operation windows are established. The proposed method provides a quantitative basis for collision risk assessment and operational guidance during deepwater BOP installation.

The first carpometacarpal (CMC) joint endows the human thumb with exceptional dexterity and is a critical component in robotic hand design. However, due to the CMC joint's complex kinematics, it is difficult to replicate its multi-DoF motion while simultaneously ensuring a compact mechanism and simple control. Therefore, this study proposes a Helix-Coupled Spherical (HCS) joint driven by double-helix coupled trajectories, which accurately reproduces the complex three-DoF motion of the human thumb. The use of magnetic materials provides a constant attractive force for the HCS joint’s rotation, achieving high-strength anti-dislocation protection. Additionally, a tendon-driven dexterous hand that integrates this HCS joint was developed. Kinematic analysis of the joint angles, workspace volume, and fingertip trajectories shows that the hand not only covers the functional workspace of the human thumb but also exhibits highly anthropomorphic postures. Benefiting from the precise trajectory control of the HCS mechanism, the dexterous hand presents superior dexterity in tasks such as pinching thin objects, power grasping, in-hand manipulation, and dynamic interaction, successfully replicating human grasping strategies. The designed HCS joint effectively resolves the conflict between high anthropomorphism and system simplicity, providing a novel technical pathway for the design of next-generation bionic dexterous hands.

[Significance]Soft anthropomorphic dexterous hands,as a type of robot end effector composed of soft materi-als,are capable of achieving human-like grasping and manipulation abilities,and are characterized by high dexterity,outstanding environmental adaptability,and safety in the human-robot interaction.[Analysis]The performance of soft anthropomorphic dex-terous hands in terms of dexterity and grasping operation capabilities was reviewed,followed by a detailed introduction and anal-ysis of the research status of soft anthropomorphic dexterous hands in terms of driving methods,materials and manufacturing,flexible tactile sensing,modeling and control.Finally,the potential challenges and possible development directions faced by soft anthropomorphic dexterous hands were discussed,and emphasizing that improving their dexterity and tactile perception capabili-ties is a key focus of future research.

The velocity of pigging robots constitutes a critical determinant of their functional performance. The conventional mechanical bypass regulation mechanisms suffer from elevated fabrication costs, structural complexity prone to malfunction, and potential secondary pipeline damage caused by detached rigid components. This study proposes a heart valve-inspired soft bypass that demonstrates lower manufacturing costs, rapid response characteristics, and damage containment properties. This investigation employs the Coupled Eulerian–Lagrangian (CEL) method to develop a fluid–structure interaction (FSI) model, simulating both the hydrodynamic deformation of soft bypass and the dynamic behavior of the pigging robot equipped with soft bypass. Through analysis of the maximum stress and opening percentage during soft bypass deformation, the geometric parameters of the soft bypass were optimized. The motion characteristics of pigging robots with soft bypass were investigated. An air pushing experiment was performed on the soft bypass, employing the soft sensor for deformation measurement. Experimental results demonstrated differential response characteristics: the front bypass exhibited partial opening under air pushing, while the posterior bypass showed distinct closure behavior. This study presents a heart valve-inspired soft bypass. Providing a novel approach for velocity modulation in pigging robots.

Flexible pressure sensors are indispensable in various applications, such as intelligent soft robots and wearable devices. However, developing low-cost, facile, flexible pressure sensors with high sensitivity and a wide detection range remains a great challenge. Here, we propose a simple and cost-effective flexible piezoresistive pressure sensor with a hybrid structure to obtain high sensitivity and a wide detection range. The hybrid structure is composed of micro cilia induced by a magnetic field and a porous polydimethylsiloxane (PDMS) structure using NaCl as a porogen. In contrast, multi-walled carbon nanotubes (MWCNTs) were used as a conductive coating. The synergistic effect of micro cilia and porous structure in the sensor achieved a maximum sensitivity of 13.16 kPa(-1) (approximately 21 times higher than that of the porous structure alone), a wide detection range (0-100 kPa), a rapid response time (similar to 118 ms), a low limit of detection (0.49 Pa), and long-term durability (>10000 cycles). The sensor also exhibits remarkable stability after 1500 cycles in 90 % RH environments. Moreover, the practical application of the sensor in detecting complex human motions and health monitoring is demonstrated, validating its potential for applications in wearable devices.

Pipelines serve as the primary method for offshore natural gas transportation, where pigging operations are essential for maintaining pipeline efficiency and safety. To enable pigging robot launching and receiving between offshore platforms and subsea manifolds through a single pipeline, subsea automatic pigging robot launchers are typically employed, with the offshore platform functioning as the receiving terminal. This approach facilitates pigging operations without interrupting production, thus enhancing economic benefits. This study used finite element simulation to investigate the mechanical behaviour of an monoethylene glycol (MEG) fluid-driven pigging robot as it traverses a T-type tee without interrupting production. A Coupled Eulerian-Lagrangian (CEL) method was used to develop a fluid-structure interaction (FSI) simulation model, analysing the motion of the pigging robot in natural gas production pipelines as they traverse T-type tee under MEG driving conditions. The mechanical behaviour of hyperelastic polyurethane was simulated using the third-order Ogden model, while the fluid response was characterized by the Mie-Gr & uuml;neisen equation of state in a linear Us-Up form. The results demonstrate that the pigging robot's average velocity increases significantly with rising inlet pressure within the 0.15-0.25 MPa range. A distinct reduction in frictional resistance occurs when the inlet pressure reaches 0.3 MPa. This study established a FSI simulation model using the CEL method to evaluate the effects of different launching pressures on pigging robot movement through tee junctions. The findings provide references for pigging operations in natural gas pipelines.

Pipeline inspection gauge (PIG) is often blocked in the ageing pipelines of stacked objects. A novel pneumatically controlled sealing disc has been designed to address the issue of PIG’s blockage. Compared to traditional passive-controlled sealing discs, the new sealing disc incorporates a multi-jointed pneumatic webbed foot that enables active control. It provides both single execution mode and multiple execution mode capabilities, allowing it to achieve partial bending through the inflation of a single foot and thereby enhancing sealing performance during active control. A finite element method (FEM) was introduced and effectively validated by comparing simulation results with experimental results of the inflatable bending experiments of a single foot. Then the performance of the sealing disc with single execution mode and multiple execution mode was compared using the FEM, and the results show that they have good consistency. Next, the effects of four kinds of materials and five structural parameters on the performance of the sealing disc were studied using the FEM. The results show that the multi-material structure has better performance compared to the same materials and the Ecoflex series demonstrates greater responsiveness in inflation experiments. As the air pressure grows, the position parameter of the joint has little effect on the bending angle as well as the expansion ratio, and the bottom disc thickness has also slightly influence on the expansion ratio. Meanwhile, the thicker the webbed foot thickness, the smaller the slope angle and the thinner, the larger the bending angle; the smaller the slope angle, the thicker the webbed foot thickness, the larger the expansion ratio. The conclusions obtained in this paper are beneficial for the design and optimization of PIG sealing discs for actively controlling. The research results provide theoretical reference for the study of intelligent and efficient pipeline pigging technology.

Graphene and molybdenum disulfide (MoS2) have been widely used as lubricating agents to reduce friction and wear in sliding contacts, however, their effects on the tribological properties of steel-steel contact under biodiesel lubrication have been rarely reported. In this study, we prepared steel surfaces with three types of physical coating, namely graphene, MoS(2)and a blend of graphene and MoS2, and investigated the tribological properties of these coatings under biodiesel lubrication conditions. Under lubrication of 20 vol% biodiesel, the wear track depth on the disk decreased by 10.3% and 20.5%, while the wear track width on the disk was reduced by 3.4% and 1.7%, respectively, with the graphene and MoS(2)absorption layers prepared on the steel disk surfaces. In terms of friction reduction behavior, the MoS(2)layer was found to reduce the coefficient of friction (COF) by 2.4%, whereas there was a 2.4% increase in the COF with the graphene layer. Nonetheless, neither the graphene coating nor the MoS(2)coating was found to be suitable for the condition of pure biodiesel lubrication, since a significant increase was observed in the wear on both the steel balls and the steel disks with the application of these absorption layers.

Flexible materials significantly influence the operation performance of soft robots. Commercial silicone rubber products limit capabilities of soft robots because of their unchangeable properties. In this study, we explored the impact of three inorganic fillers on the mechanical properties of silicone rubber. We created soft actuators with these fillers-embedded composite materials and assessed how the inclusion of inorganic fillers affects their bending, force output, and gripping abilities. Our results demonstrate that inorganic fillers, at appropriate concentrations, significantly enhance the elastic modulus, elongation, and fracture toughness of the silicone rubber. Incorporating inorganic fillers substantially improve the bending, output thrust, and gripping performance of the soft actuator.

With the development of soft robotics, soft robotic hands are increasingly attracting attention. Compared with their rigid counterparts, they are safer, more adaptive, and lower cost. However, most studies have focused on the soft fingers and actuators, while the significance of the palm is usually overlooked. In this study, a pneumatic fully soft anthropomorphic hand with an active soft palm is proposed. With 12 degrees of freedom (2 in the palm), the soft robotic hand can execute metacarpal and thumb opposition motions. The hand was made using the mold casting method, and the strain energy density function of the silicone rubber is employed in the Yeoh model to calculate the relationship between the air pressure and the bending angle. Next, we tested the bending angle of the fingers and the palm under different air pressure, and grasped objects with various sizes, shapes, and weights, demonstrating good grasping ability. This soft hand can further broaden the potential applications of robotic hands.

With the popularization of electric vehicles, early built parking lots cannot solve the charging problem of a large number of electric vehicles. Mobile charging robots have autonomous navigation and complete charging functions, which make up for this deficiency. However, there are static obstacles in the parking lot that are random and constantly changing their position, which requires a stable and fast iterative path planning method. The gray wolf optimization (GWO) algorithm is one of the optimization algorithms, which has the advantages of fast iteration speed and stability, but it has the drawback of easily falling into local optimization problems. This article first addresses this issue by improving the fitness function and position update of the GWO algorithm and then optimizing the convergence factor. Subsequently, the fitness function of the improved gray wolf optimization (IGWO) algorithm was further improved based on the minimum cost equation of the A* algorithm. The key coefficients AC 1 and AC 2 of two different fitness functions, Fitness 1 and Fitness 2 , were discussed. The improved gray wolf optimization algorithm integrating A* algorithm (A*-IGWO) has improved the number of iterations and path length compared to the GWO algorithm in parking lots path planning problems.

The aim of this paper is to review recent advances in the tribological characterization of biodiesel and various attempts to improve its lubricity by applying additives and optimizing its components. Lubricity of biodiesel or biodiesel contained blend in both metallic and nonmetallic contacts are presented. In biodiesel lubrication, properly selected nonmetallic surface is able to reduce friction and wear compared to metal-on-metal contact. The impact of the primary parameters, such as load, velocity, and temperature, on the tribological performance of biodiesel are described. Positive dependence of friction and wear on load and temperature and negative dependence on velocity are determined. Current challenges in application of biodiesel and future directions to potential solutions are summarized as well.

Over extended periods of operation, natural gas pipelines tend to accumulate significant amounts of black powder impurities along their inner walls. Many of these impurities exhibit corrosive properties, leading to pipeline degradation and posing a serious threat to the safety and reliability of energy transportation. The jet pigging robot also called as jet pig, a type of pigging robots, has been developed to address pipeline impurities. The conventional approach involves using a pigging robot to perform cleaning operations inside the pipeline. However, the speed of traditional pigging robots is difficult to control, often leading to safety risks such as blockages and reduced cleaning efficiency, as well as increased operational costs. In contrast, the jet pigging robot, equipped with a jet nozzle, emits a high-speed jet stream that effectively dislodges black powder particles, mitigating issues related to safety, efficiency, and cost. Therefore, optimizing the design of the jet pigging robot for black powder removal is of great significance. This study proposes a novel pigging robot jet structure and optimizes its dimensions using finite element simulation. The effects of key geometric parameters on flow velocity and turbulent kinetic energy are investigated. Simulation results indicate that a jet structure with a sealing disk hole inclination angle of 40 degrees and a baffle spacing of 18 mm demonstrates effective wall-cleaning performance. At a bypass ratio of 9%, the structure exhibits high cleaning efficiency, while at a bypass ratio of 12%, it enhances operational safety and reduces the risk of blockages.

Due to the compact parking of vehicles in parking lots, the working environment of electric vehicle charging robots is complex and narrow, which puts higher demands on the flexibility of robot manipulators. The workspace of manipulator reflects its working range, while the density of the workspace reflects the flexibility of all parts of the manipulator within its working range. According to the working range of the electric vehicle charging robot, adjusting the ratio of the number of manipulator joints and the length of the manipulator can improve its dexterity. This article uses MATLAB simulation to calculate the workspace density of manipulator with different joint numbers and length ratios, and draws workspace density cloud map, which can more intuitively judge the performance of the manipulator. The research provides guidance and inspiration for optimizing the geometric dimensions of the manipulator.

Underwater launchers are typically employed for the deployment of pigging robots in subsea pipelines for the purposes of cleaning and inspection. Throughout the launching process, challenges related to vibration, damage, and other issues must be addressed and resolved. In this study, the launching process of the pigging robot is numerically simulated using Abaqus 2020. Utilising the Coupled Eulerian-Lagrangian (CEL) method, the Fluid-Structure-Interaction (FSI) model of the launching process was constructed. And the variation of parameters such as velocity, friction force and tilt angle at different inlet flow rates were analysed. The findings indicate a positive correlation between the average velocity of the pigging robot and the inlet flow rate. The factors such as friction, tilt angle, and offset distance are related to the motion process of the pigging robot. Furthermore, during the pigging robot’s traversal through narrow pipe sections, the sealing discs undergo irregular deformation, generating a reaction force on the robot and inducing vibration. In conclusion, the analysis of the impact of inlet flow velocity on the motion behaviour of the pigging robot offers a theoretical foundation and reference for the successful launch of the robot.

>Motion performance, including movement speed, adaptability to various environments, and load-carrying capability, is crucial for soft crawling robots, tasked with field exploration and the transporting material in often complex and unstructured environments. A wide variety of soft crawling robots, which are driven by electricity [1], chemical power [2], and pressurized fluid [3] to move forward via cyclic deformation, have thus far been inspired by the mobile patterns of soft-bodied animals, such as worms [4],snake [5], octopus [6], etc. The performance of soft robots in terms of speed and load has developed impressively in recent years.

Humans possess dexterous hands that surpass those of other animals, enabling them to perform intricate, complex movements. Soft hands, known for their inherent flexibility, aim to replicate the functionality of human hands. This article provides an overview of the development processes and key directions in soft hand evolution. Starting from basic multi-finger grippers, these hands have made significant advancements in the field of robotics. By mimicking the shape, structure, and functionality of human hands, soft hands can partially replicate human-like movements, offering adaptability and operability during grasping tasks. In addition to mimicking human hand structure, advancements in flexible sensor technology enable soft hands to exhibit touch and perceptual capabilities similar to humans, enhancing their performance in complex tasks. Furthermore, integrating machine learning techniques has significantly promoted the advancement of soft hands, making it possible for them to intelligently adapt to a variety of environments and tasks. It is anticipated that these soft hands, designed to mimic human dexterity, will become a focal point in robotic hand development. They hold significant application potential for industrial flexible gripping solutions, medical rehabilitation, household services, and other domains, offering broad market prospects.