Search Results (250)

Visual body-tracking techniques have seen widespread adoption in applications such as motion analysis, human–machine interaction, tele-robotics and extended reality (XR). These systems typically provide 2D landmark coordinates corresponding to key limb positions. However, to construct a meaningful 3D kinematic model for body joint reconstruction, a mapping must be established between these visual landmarks and the underlying joint parameters of individual body parts. This paper presents a method for constructing a 3D kinematic model of the human hand using calibrated 2D landmark-tracking data augmented with depth information. The proposed approach builds a hierarchical model in which the palm serves as the root coordinate frame, and finger landmarks are used to compute both forward and inverse kinematic solutions. Through step-by-step examples, we demonstrate how measured hand landmark coordinates are used to define the palm reference frame and solve for joint angles for each finger. These solutions are then used in a visualization framework to qualitatively assess the accuracy of the reconstructed hand motion. As a future work, the proposed model offers a foundation for model-based hand kinematic estimation and has utility in scenarios involving occlusion or missing data. In such cases, the hierarchical structure and kinematic solutions can be used as generative priors in an optimization framework to estimate unobserved landmark positions and joint configurations. The novelty of this work lies in its model-based approach using real sensor data, without relying on wearable devices or synthetic assumptions. Although current validation is qualitative, the framework provides a foundation for future robust estimation under occlusion or sensor noise. It may also serve as a generative prior for optimization-based methods and be quantitatively compared with joint measurements from wearable motion-capture systems. Full article

Aiming at the problems of complex control processes, strong model dependence, and difficult engineering application when the existing active suspension control strategy is applied to multi-axle vehicles, an active suspension control strategy based on the inverse position solution of a parallel mechanism is proposed. First, the active suspension of the three-axle emergency rescue vehicle is grouped and interconnected within the group, and it is equivalently constructed into a 3-DOF parallel mechanism. Then, the displacement of each equivalent suspension actuating hydraulic cylinder is calculated by using the method of the inverse position solution of a parallel mechanism, and then the equivalent actuating hydraulic cylinder is reversely driven according to the displacement, thereby realizing the effective control of the attitude of the vehicle body. To verify the effectiveness of the proposed control strategy, a three-axis vehicle experimental platform integrating active suspension and hydro-pneumatic suspension was built, and a pulse road experiment and gravel pavement experiment were carried out and compared with hydro-pneumatic suspension. Both types of road experimental results show that compared to hydro-pneumatic suspension, the active suspension control strategy based on the inverse position solution of a parallel mechanism proposed in this paper exhibits different degrees of advantages in reducing the peak values of the vehicle vertical displacement, pitch angle, and roll angle changes, as well as suppressing various vibration accelerations, significantly improving the vehicle’s driving smoothness and handling stability. Full article

Cultural Heritage is a vital socioeconomic driver that must contend with works of art continuously exposed to degradation processes, which are further exacerbated by climate change. Aged coatings, varnishes, and soil can compromise the appearance of artworks, preventing their preservation and valorization. In response, soft matter and colloidal systems, such as nanostructured cleaning fluids (NCFs), have proved to be valuable solutions for safely and effectively cleaning works of art. Here, a novel cleaning system is proposed, for the first time employing microgels of poly(N-isopropylacrylamide) (PNIPAM) with surface chains of oligoethylene glycol methyl ether methacrylate (OEGMA) to favor shear deformation by lubrication. These microgels are loaded with NCFs featuring “green” solvents and different kinds of bio-derived or petroleum-based surfactants (non-ionic, zwitterionic). Rheological characterization of the combined systems highlighted a sharp transition from solid to liquid-like state in the 21–24 °C range when the zwitterionic surfactant dodecyldimethylamine oxide was used; the system displays a solid-like behavior at rest but flows easily at intermediate strains. At slightly higher temperature (>24 °C), an inversion of the G′, G″ values was observed, leading to a system that behaves as a liquid. Such control of rheological behavior is significant for feasible and complete removal of soiled polymer coatings from textured ceramic surfaces, which are difficult to clean with conventional gels, without leaving residues. These results position the PNIPAM-OEGMA microgels as promising cleaning materials for the conservation of Cultural Heritage, with possible applications also in fields where gelled systems are of interest (pharmaceutics, cosmetics, detergency, etc.). Full article

In the area of microstrip filter design and optimization, deep learning (DL) algorithms have become much more attractive and powerful in recent years. Here, we propose a method to realize the inverse design of passive microstrip filters, applying generative adversarial networks (GANs). The proposed DL-assisted framework is composed of three components, including a compositional pattern-producing network GAN-based graphic generator, a convolution neural network (CNN)-based electromagnetic (EM) response predictor, and a genetic algorithm optimizer. The filter adopts a square patch resonator structure with an irregular-graphic slot and corner-cuts introduced at diagonal positions. By constructing a hybrid model of pixelated patterns in the filter structures and the corresponding EM response S-parameters, we can obtain customized filter solutions with wideband and dual-band magnitude responses in the 3–8 GHz and 1–6 GHz frequency range, respectively. For each inverse design, it cost 3.6 min for executing 1000 iterations, on average. Numerical simulations and experimental results show that the S-parameters of the generated filters are in excellent agreement with the self-defined targets. Full article

In addressing the optimal motion planning issue for multi-arm rock drilling robots, this paper introduces a high-precision motion planning method based on Multi-Strategy Sampling RRT* (MSS-RRT*). A dual Jacobi iterative inverse solution method, coupled with a forward kinematics error compensation model, is introduced to dynamically correct target positions, improving end-effector positioning accuracy. A multi-strategy sampling mechanism is constructed by integrating DRL position sphere sampling, spatial random sampling, and goal-oriented sampling. This mechanism flexibly applies three sampling methods at different stages of path planning, significantly improving the adaptability and search efficiency of the RRT* algorithm. In particular, DRL position sphere sampling is prioritized during the initial phase, effectively reducing the number of invalid sampling points. For training a three-arm DRL model with the twin delayed deep deterministic policy gradient algorithm (TD3), the Hindsight Experience Replay-Obstacle Arm Transfer (HER-OAT) method is used for data replay. The cylindrical bounding box method effectively prevents collisions between arms. The experimental results show that the proposed method improves motion planning accuracy by 94.15% compared to a single Jacobi iteration. MSS-RRT* can plan a superior path in a shorter duration, with the planning time under optimal path conditions being only 20.71% of that required by Informed-RRT*, and with the path length reduced by 21.58% compared to Quick-RRT* under the same time constraints. Full article

This study proposes a force–position hybrid control method for quadruped robots based on the Model Predictive Control (MPC) algorithm, aiming to address the challenges of stability and adaptability in complex terrain environments. Traditional control methods for quadruped robots are often based on simplified models, neglecting the impact of complex terrains and unstructured environments on control performance. To enhance the real-world performance of quadruped robots, this paper employs the MPC algorithm to integrate force and position control to achieve precise force–position hybrid regulation. By transforming foot-end forces into joint torques and optimizing them using kinematic inverse solutions, the robot’s stability and motion accuracy in challenging terrains is further enhanced. In this study, a Kalman filter-based state estimation method is adopted to estimate the robot’s state in real time, enabling closed-loop control through the MPC framework, combined with kinematic inverse solutions for hybrid control. The experimental results demonstrate that the proposed MPC algorithm significantly improves the robot’s adaptability and control accuracy across various terrains. In particular, it exhibits superior performance and robustness in multi-contact and uneven terrain scenarios. This research provides a novel approach for deploying quadruped robots in dynamic and complex environments and offers strong support for further optimization of motion control strategies. Full article

In contemporary warehouse logistics, the demand for efficient and precise inventory management is increasingly critical, yet traditional Radio Frequency Identification (RFID)-based systems often falter due to static antenna configurations that limit tag detection efficacy in complex environments with diverse object arrangements. Addressing this challenge, we introduce an advanced RFID-based inventory robot that integrates a 3-degree-of-freedom (3DOF) manipulator with vision-assisted dynamic antenna positioning to optimize tag detection performance. This autonomous system leverages a pretrained You Only Look Once (YOLO) model to detect objects in real time, employing forward and inverse kinematics to dynamically orient the RFID antenna toward identified items. The manipulator subsequently executes a tailored circular scanning motion, ensuring comprehensive coverage of each object’s surface and maximizing RFID tag readability. To evaluate the system’s efficacy, we conducted a comparative analysis of three scanning strategies: (1) a conventional fixed antenna approach, (2) a predefined path strategy with preprogrammed manipulator movements, and (3) our proposed vision-assisted dynamic positioning method. Experimental results, derived from controlled laboratory tests and Gazebo-based simulations, unequivocally demonstrate the superiority of the dynamic positioning approach. This method achieved detection rates of up to 98.0% across varied shelf heights and spatial distributions, significantly outperforming the fixed antenna (21.6%) and predefined path (88.5%) strategies, particularly in multitiered and cluttered settings. Furthermore, the approach balances energy efficiency, consuming 22.1 Wh per mission—marginally higher than the fixed antenna (18.2 Wh) but 9.8% less than predefined paths (24.5 Wh). By overcoming the limitations of static and preprogrammed systems, our robot offers a scalable, adaptable solution poised to elevate warehouse automation in the era of Industry 4.0. Full article

The increasing global demand for food caused by a growing world population has resulted in environmental problems, such as the destruction of ecologically significant biomes and pollution of ecosystems. At the same time, the intensification of crop production in modern agriculture has led to the extensive use of synthetic fertilizers to achieve higher yields. Although chemical fertilizers provide essential nutrients and accelerate crop growth, they also pose significant health and environmental risks, including pollution of groundwater and other bodies of water such as rivers and lakes. Soils that have been destabilized by indiscriminate clearing of vegetation undergo a desertification process that has profound effects on microbial ecological succession, impacting biogeochemical cycling and thus the foundation of the ecosystem. Tropical countries have positive aspects that can be utilized to their advantage, such as warmer climates, leading to increased primary productivity and, as a result, greater biodiversity. As an eco-friendly, cost-effective, and easy-to-apply alternative, biofertilizers have emerged as a solution to this issue. Biofertilizers consist of a diverse group of microorganisms that is able to promote plant growth and enhance soil health, even under challenging abiotic stress conditions. They can include plant growth-promoting rhizobacteria, arbuscular mycorrhizal fungi, and other beneficial microbial consortia. Bioremediators, on the other hand, are microorganisms that can reduce soil and water pollution or otherwise improve impacted environments. So, the use of microbial biotechnology relies on understanding the relationships among microorganisms and their environments, and, inversely, how abiotic factors influence microbial activity. The recent introduction of genetically modified microorganisms into the gamut of biofertilizers and bioremediators requires further studies to assess potential adverse effects in various ecosystems. This article reviews and discusses these two soil correcting/improving processes with the aim of stimulating their use in developing tropical countries. Full article

Ultra-wideband (UWB) technology is widely used for high-precision indoor positioning due to its adaptability to various environments. However, in long linear areas, such as tunnels or corridors, the near-linear deployment of base stations caused by structural constraints significantly degrades UWB localization accuracy, rendering conventional algorithms ineffective. To address this issue, this study proposes a high-precision UWB+TOA-R positioning algorithm that incorporates Ridge estimation as a constraint condition. The algorithm introduces equivalent weights to refine the iterative computation of Ridge estimation, establishing an iteratively computed TOA-RR solution model. Experiments were conducted in a long linear corridor to compare the performance of three UWB localization models: the TOA-Least Squares (TOA-LS) model, the TOA-Ridge estimation (TOA-R) model, and the proposed TOA-Ridge estimation iterative (TOA-RR) model. The results indicate that the TOA-LS model suffers from significant coordinate distortions due to abnormalities in the inverse matrix of the coefficient matrix, regardless of the initial tag coordinates. The TOA-R model demonstrates improved accuracy and stability, particularly in cases of significant initial deviations, but still exhibits residual errors. In contrast, the TOA-RR model achieves enhanced stability and accuracy, with a positioning error of approximately 0.5 m. This study resolves the challenge of inaccurate UWB localization in long linear areas, providing a robust solution for such environments. Full article

This study presents a novel mathematical model of a generalized magnetothermoelastic half-space based on the Green–Naghdi theorem, namely type-I and type-III. The half-space surface undergoes ramp-type heating and is positioned on a sturdy base to prevent movement. This research is novel as it employs Caputo’s definition of fractional derivatives within the context of Maxwell’s time-fractional equations. Laplace transform methods are used to obtain the solutions. Tzou’s iterative method has been used to calculate inversions of the Laplace transform. The findings include quantitative answers for temperature increase, strain, displacement, stress, induced magnetic field, and induced electric field distributions. The time-fraction parameter defined by Maxwell’s equation considerably influences all essential mechanical functions, but the thermal functions remain unchanged. In Maxwell’s equations, the time-fractional parameter functions augment the induced electric field inside the material, acting as a resistor to particle motion and the induced magnetic field, while concurrently facilitating the induced electric field. Moreover, the thermal, mechanical, and magnetoelectric waves of Green–Naghdi type-III propagate at a reduced velocity compared to type-I. The fundamental magnetic field substantially influences all examined functions. Full article

Quad-tilt-wing (QTW) Unpiloted Aerial Vehicles (UAVs) combine the vertical takeoff and landing capabilities of rotary-wing designs with the high-speed, long-range performance of fixed-wing aircraft, offering significant advantages in both civil and military applications. The unique configuration of QTW UAVs presents complex control challenges due to nonlinear dynamics, strong coupling between translational and rotational motions, and significant variations in aerodynamic characteristics during transitions between flight modes. To address these challenges, this study develops an optimal control framework tailored for real-time operations. A State-Dependent Riccati Equation (SDRE) approach is employed for attitude control, addressing nonlinearities, while a Linear Quadratic Regulator (LQR) is used for position and velocity control to achieve robustness and optimal performance. By integrating these strategies and utilizing the inverse dynamics approach, the proposed control system ensures stable and efficient operation. This work provides a solution to the optimal control complexities of QTW UAVs, advancing their applicability in demanding and dynamic operational environments. Full article

Thermoelectric technology, which converts heat and electricity into each other, has been attracting attention from the perspective of efficient energy utilization. Recently, eco-friendly and cost-effective Cu-based thermoelectric materials have been actively studied. In particular, efforts have been made to improve thermoelectric properties and enhance performance through the formation of solid solutions. This study examines the formation and thermoelectric properties of Cu-chalcogenide solid solutions between eskebornite (tetragonal CuFeSe₂) and chalcopyrite (tetragonal CuFeS₂), synthesized as CuFeSe_2−yS_y (y = 0–2) using solid-state synthesis. These compounds share similar crystal structures, which enable the formation of solid solutions that enhance phonon scattering and may potentially improve thermoelectric performance. As the S content (y) increased, the lattice parameters a and c decreased, attributed to the smaller ionic radius of S²⁻ compared to Se²⁻, as X-ray diffraction analysis identified single-phase regions for 0 ≤ y ≤ 0.4 and 1.6 ≤ y ≤ 2, respectively. However, for 0.8 ≤ y ≤ 1.2, a composite phase of eskebornite and chalcopyrite formed, indicating incomplete solid solution behavior in the intermediate range. Thermoelectric measurements showed a sharp increase in electrical conductivity with increasing S content, alongside a transition in the Seebeck coefficient from positive (p-type) to negative (n-type), attributed to the intrinsic semiconducting nature of the end-member compounds. Eskebornite behaves as a p-type semiconductor, whereas chalcopyrite is n-type, and their combination affects the carrier type and concentration. Despite these changes, the power factor did not show significant improvement due to the inverse relationship between electrical conductivity and the Seebeck coefficient. The thermal conductivity decreased significantly with solid solution formation, with CuFeSe_0.4S_1.6 exhibiting the lowest value of 0.97 Wm⁻¹K⁻¹ at 623 K, a result of enhanced phonon scattering at lattice imperfections and the mass fluctuation effect. This value is lower than the thermal conductivity values of single-phase eskebornite or chalcopyrite. However, the reduction in thermal conductivity was insufficient to compensate for the modest power factor, resulting in no substantial enhancement in the thermoelectric figure of merit. Full article

Geopolymer-based grouting materials often have a higher early strength, better durability, and lower environmental impact than those of traditional cement-based grouts. However, existing geopolymer grouts face common challenges such as rapid setting and low compatibility with treated substrates. This study develops a new grouting material using industrial byproducts to overcome these limitations while optimizing performance for reinforcing silty mudstone slopes. The base materials used were ground granulated blast furnace slag (GGBFS) and zeolite powder, with calcium lignosulphonate (CL) serving as the retarding agent and NaOH as the alkali activator. The investigation focused on the effects of the mix ratio and water–binder ratio on the setting time, flowability, bleeding rate, concretion rate, and compressive strength of the new grouting material. Scanning electron microscope (SEM) and X-ray diffraction (XRD) analyses were employed to examine the action mechanism of the material components in the slurry. The one-factor standard deviation method and Grey Relational Analysis (GRA) were used to assess the influence of each material component on the slurry performance indices and the correlation between each performance index and its optimal mix ratio. Subsequently, the optimal mix ratio of the new grouting material was ascertained. The results indicate that the setting time is positively correlated with the zeolite powder and CL dosages and the water–binder ratio, while it is inversely related to the NaOH dosage. The flowability is significantly enhanced with increasing zeolite powder and NaOH dosages, but decreases at a higher CL dosage and water–binder ratio. This insight is crucial for optimizing the workability of the grouting material under various conditions. The optimal ratio of the grout is zeolite powder:GGBFS:CL:NaOH = 30:70:5:7, with a water–binder ratio of 0.6. Compared to existing commercial grouting materials, the compressive strength of this new grout is comparable to that of silty mudstone. This significantly reduces the problem of stress concentration at the grout–rock interface due to strength differences, thus effectively reducing the risk of secondary cracking at the interface. These findings provide a new material solution for grouting and repairing fractured silty mudstone slopes. Full article

This paper offers a new perspective on the explanation of the poleward mass flux in the stratosphere. This mass flux represents the upper leg of the so-called Brewer–Dobson circulation. This new perspective is based on the following hypothesis. A positive potential vorticity anomaly, centered over the North Pole, exists in the stratosphere during the winter half-year. This positive potential vorticity anomaly is associated with a negative isentropic density anomaly, which forms due to cross-isentropic downwelling associated with radiative cooling. Isentropic potential vorticity mixing due to breaking planetary waves weakens this potential vorticity anomaly while zonal-mean thermal wind balance is maintained. This requires a weakening of the negative Polar cap isentropic density anomaly, which in turn requires a poleward isentropic mass flux. Support for this hypothesis is found in a case study of a major Sudden Stratospheric Warming event, as an example of intense potential vorticity mixing. It is shown that the stratosphere, both before and after this event, is very close to zonal-mean thermal wind balance, despite the disruptive potential vorticity mixing, while mass is shifted poleward during this event. Solutions of the potential vorticity-inversion equation, which is an expression of thermal wind balance, for zonal-mean potential vorticity distributions before and after the Sudden Stratospheric Warming, demonstrate that mass must shift poleward to maintain zonal-mean thermal wind balance when the positive potential vorticity anomaly is eliminated by mixing. This perspective on the reasons for the poleward stratospheric mass flux also explains the observed isobaric warming as well as the Polar cap zonal-mean zonal wind reversal during a major Sudden Stratospheric Warming. Full article

New analytical solutions for the inverse kinematics problem of a 6R manipulator are proposed. Based on the assumption that the rotation axes of the last three links intersect at a common point, the problem is divided into orientation and transition problems. The position of the common point and the rotation angles of the first three links are determined using the equations of motion of the output link. A matrix equation for the rotation angles of the last three links is formulated. Solutions to the inverse kinematics problem are obtained for three models. In the first two, the rotation axis of the fourth link may not intersect the vertical rotation axis of the first. In the third model, the rotation axis of the fourth link intersects neither the vertical rotation axis of the first link nor the intersection point of the axes of the last two links. For all models, an analytical solution in closed form is obtained from the geometry of the mechanism. The solution for the third requires a preliminary search for the root of the transcendental equation for the rotation angle of the fourth link. Illustrative examples of calculations for a specific manipulator are given. Full article