Estimating the relative position and velocity of micro aerial vehicles (MAVs) using visual signals is a critical issue in numerous tasks. However, traditional relative motion estimation algorithms suffer severely from non-Gaussian noise interference and have limited observability, making it difficult to meet the practical requirements of complex dynamic scenarios. To address this dilemma, this paper proposes a Multimodal Decoupled Spatiotemporal Adaptive Network (MDSAN). Designed for air-to-air scenarios, MDSAN achieves high-precision relative pose and velocity estimation of dynamic MAVs while overcoming the observability limitations of traditional algorithms. In detail, MDSAN is collaboratively composed of two core sub-modules: Modality-Specific Convolutional Normalization (MSCN) blocks and Spatiotemporal Adaptive State (STAS) blocks. Specifically, MSCN uses custom convolution kernels tailored to three modalities—visual, physical, and geometric—to separate their features. This prevents interference between modalities and reduces non-Gaussian noise. STAS, built on a state-space model, combines two key functions: it tracks long-term MAV motion trends over time and strengthens the synergy between different modal features across space. Adaptive weights balance these two functions, enabling stable estimation, even when traditional methods struggle with low observability. Furthermore, MDSAN adopts a full-vision multimodal fusion scheme, completely eliminating the dependence on wireless communication and reducing hardware costs. Extensive experimental results demonstrate that MDSAN achieves the best performance in all scenarios, significantly outperforming existing motion estimation algorithms. It provides a new technical path that balances high precision, high robustness, and cost-effectiveness for technologies such as MAV swarm perception.
To tackle compatibility issues arising from uneven phase shifts during phase extraction from spectral interferograms, this paper finds what we believe to be a novel approach and bridges the tilted phase-shifting method with spectrally resolved interferometry (SRI). A tilt phase-shifting iterative method based on the spectral interferogram reconstruction strategy is proposed, achieving high-quality phase extraction and overcoming the limitations of phase shifts. This method utilizes the interpolation reconstruction of spectral interferograms to make the phase shift exhibit a linear tilt, allowing the tilt phase-shifting iterative method to extract phase from at least three frames with random phase shifts. By evaluating the profile measurement, our method demonstrates higher accuracy than previous methods under high-noise conditions, with random phase shifts, and across varying heights.
Phase noise constitutes a pivotal performance parameter in microwave systems, and the evolution of microwave signal sources presents new demands on phase noise analyzers (PNAs) regarding sensitivity and bandwidth. Traditional electronics-based PNAs encounter significant limitations in meeting these advanced requirements. This paper provides an overview of recent progress in photonics-based microwave PNA research. Microwave photonic (MWP) PNAs are categorized into two main types: phase-detection-based and frequency-discrimination-based architectures. MWP phase-detection-based PNAs utilize ultra-short-pulse lasers or optical–electrical oscillators as reference sources to achieve superior sensitivity. On the other hand, MWP frequency-discrimination-based PNAs are further subdivided into photonic-substitution-type PNA and MWP quadrature-frequency-discrimination-based PNA. These systems leverage innovative MWP technologies to enhance overall performance, offering broader bandwidth and higher sensitivity compared to conventional approaches. Finally, the paper addresses the current challenges faced in phase noise measurement technologies and suggests potential future research directions aimed at improving measurement capabilities.
The solar-periodic system is a completely self-contained space, with no singularity or boundaries, which timelessly regenerates preserving its initial states (origins) and completely described by Euler’s complex theory of holomorphic (complex-smooth-recurrent) functions, ever discovered. This unified theory is the basis of eternal existence furnishing the building blocks of reality and the solution for long-standing problem of Cartesian dualism. It demonstrates precisely how mind generates relative/temporary matter in a metastable (phasing) equilibrium through the quantum dual isomorphism (e, p) of light, mutually regenerating matter. Physically it manifests as the quantum recurrence at the three levels/scales: quantum chemical elements (Mendeleev’s law, atomic frozen spiral), molecular thermistors (thermal molecular spiral) and astronomical gravitational rotating bodies (global/integrated solar system of planets and satellites). The periodical chemical elements are the first 94 known to occur naturally on Earth, of which 36 are primordial making up “the permafrost”. These are elements from the p-block (including hydrogen and helium) of the periodic table, where their atomic structure has completely filled subshells preserving initial states are daily and monthly (Krypton) regenerating (24 hours-one day) ≅1 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑚 𝑚𝑚𝑚𝑚𝑚𝑚 (𝑃𝑃𝑢𝑢)𝑔𝑔0 𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎 𝑛𝑛𝑛𝑛𝑛 𝑛𝑛𝑛𝑛𝑛𝑛 (𝑍𝑍). They genuinely have a dual character (two allotropes/states), owing to the primal quantum contact ((𝑒𝑒+𝑒𝑒2)1/4≡𝜋𝜋1/2). The molecular structures and astronomical body configurations, self-contained them, are regenerating after a year and respectively century following a binary gravitational rule, 𝑔𝑔02212=7 (𝑙𝑙𝑙𝑙𝑙𝑙𝑔 0=1), for critical mixtures, the so-called the relative peakedness or two soliton coherent distribution (phases). The solar regenerative system is a critical system in the sense that is “an autocatalytic thermomolecular reaction” regenerating its initial states only in strict conditions. In such a system the reaction products increase the rate of reaction and if the ratio of system surface to system volume is large, then the reaction products tend to escape at the boundaries of system. Contrary, if the surface to volume ratio is small then the rate of escape may be less than the rate of formation and the reaction rate may extinguish or re-ignite for a critical size where rate of production just equals the rate of removal. At such a critical size, given by Sobolev isoperimetric inequality (4𝜋𝜋𝜋𝜋 (𝑎𝑎𝑎𝑎𝑎𝑎𝑎𝑎)≤𝑃𝑃2 (𝑝𝑝𝑝 𝑝 𝑝𝑝𝑝 𝑝𝑝𝑝 )), the reaction is self-sustaining and is going on for so-long time the rate of regeneration does not exceed the rate of production. The bases of the Eulerian quantum dual isomorphism of light which explain close relationship between quantum automorphic wary light and the solar timelessly regenerative system, in a photostationary (or frozen) equilibrium, are considered.
The hybrid wing eVTOL motor beam is a key critical structure component，and the flight load is com plex during the conversion and reverse conversion flight stages. Therefore，studying its structure design is of great significance. This article studies the propeller lift loads and flight overload of the motor beam during vertical takeoff，transition，fixed-wing flight，reverse transition，vertical landing flight stages. Under this load，a motor arm structure with dual transmission paths is designed，and the structure optimization of the motor seat is carried out under the given constraint conditions. The motor beam structure design is calculated through simulation analysis，ensure that the stress level of the composite materials and metal parts on the motor arm is lower than the design allow able value. Finally，the experimental loading method is designed based on the structural form of the motor arm. The strain and deformation during the measurement experiment are compared and analyzed with the strength calculation results through static strength tests and flight tests. The accuracy of the motor beam structure design and calculation results are verified. Results show that the eVTOL motor beam designed in this paper can meet the stiffness，strength，fatigue design requirements.
Arianna Rigo, João Paulo Monteiro, Rodrigo Ventura
et al.
In this work, we evaluate the impact of numerical integration methods and perturbation models on the computational speed and position accuracy of orbit propagation techniques. With increasing numbers of satellites in orbit, space traffic management may require near real-time satellite operations, for which computational speed may play a more important part in orbit propagation than positional accuracy. The aim of this work is to identify the most suitable propagation parameters for different mission scenarios and outline the perturbations to be considered based on the target orbit characteristics. We analyze the impact of the integrators’ tolerance on accuracy and runtime, as well as quantify the dominant perturbations for each orbit type. We use a Starlink satellite as a reference case, propagating it across multiple orbital regimes. The results are presented in the form of Pareto fronts trading off runtime and positional accuracy. These Pareto fronts outline some important results, for instance, how gravitational models beyond <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>32</mn><mo>×</mo><mn>32</mn></mrow></semantics></math></inline-formula> yield no accuracy improvements while significantly increasing runtime. We also verify that drag is critical in VLEO, LEO, SSO, and HEO (Molniya), while third-body effects play a major role in HEO (Molniya and Tundra), GEO, and GSO, and solar radiation pressure becomes significant in HEO (Tundra), GEO, and GSO. These results can be incorporated into collision avoidance optimization strategies for real-time satellite operations, thereby contributing to more efficient space traffic management.
Francesco De Lellis, Maria Lombardi, Egidio De Benedetto
et al.
A control-theoretic framework for autonomous avatar-guided rehabilitation in virtual reality, based on interpretable, adaptive motor guidance through optimal control, is presented. The framework faces critical challenges in motor rehabilitation due to accessibility, cost, and continuity of care, with over 50% of patients inability to attend regular clinic sessions. The system enables post-stroke patients to undergo personalized therapy in immersive virtual reality at home, while being monitored by clinicians. The core is a nonlinear, human-in-the-loop control strategy, where the avatar adapts in real time to the patient's performance. Balance between following the patient's movements and guiding them to ideal kinematic profiles based on the Hogan minimum-jerk model is achieved through multi-objective optimal control. A data-driven "ability index" uses smoothness metrics to dynamically adjust control gains according to the patient's progress. The system was validated through simulations and preliminary trials, and shows potential for delivering adaptive, engaging and scalable remote physiotherapy guided by interpretable control-theoretic principles.
Road vehicles contribute to significant levels of greenhouse gas (GHG) emissions. A potential strategy for improving their aerodynamic efficiency and reducing emissions is through active adaptation of their exterior shapes to the aerodynamic environment. In this study, we present a reduced-scale morphing vehicle prototype capable of actively interacting with the aerodynamic environment to enhance fuel economy. Morphing is accomplished by retrofitting a deformable structure actively actuated by built-in motors. The morphing vehicle prototype is integrated with an optimization algorithm that can autonomously identify the structural shape that minimizes aerodynamic drag. The performance of the morphing vehicle prototype is investigated through an extensive experimental campaign in a large-scale wind tunnel facility. The autonomous optimization algorithm identifies an optimal morphing shape that can elicit an 8.5% reduction in the mean drag force. Our experiments provide a comprehensive dataset that validates the efficiency of shape morphing, demonstrating a clear and consistent decrease in the drag force as the vehicle transitions from a suboptimal to the optimal shape. Insights gained from experiments on scaled-down models provide valuable guidelines for the design of full-size morphing vehicles, which could lead to appreciable energy savings and reductions in GHG emissions. This study highlights the feasibility and benefits of real-time shape morphing under conditions representative of realistic road environments, paving the way for the realization of full-scale morphing vehicles with enhanced aerodynamic efficiency and reduced GHG emissions.
To uncover the underlying fluid mechanisms, it is crucial to explore imaging techniques for high-resolution and large-scale three-dimensional (3D) measurements of the flow field. Plenoptic background-oriented schlieren (Plenoptic BOS), an emerging volumetric method in recent years, has demonstrated being able to resolve volumetric flow dynamics with a single plenoptic camera. The focus-stack-based plenoptic BOS system can qualitatively infer the position of the density gradient in 3D space based on the relative sharpness of the refocused BOS image. Plenoptic BOS systems based on tomography or specular enhancement techniques are realized for use in high-fidelity 3D flow measurements due to the increased number of acquisition views. Here, we first review the fundamentals of plenoptic BOS, and then discuss the system configuration and typical application of single-view and multi-view plenoptic BOS. We also discuss the related challenges and outlook on the potential development of plenoptic BOS in the future.
In contrast to rotorcraft, fixed-wing unmanned aerial vehicles (UAVs) encounter a unique challenge in path planning due to the necessity of accounting for the turning radius constraint. This research focuses on coverage path planning, aiming to determine optimal trajectories for fixed-wing UAVs to thoroughly explore designated areas of interest. To address this challenge, the Linear Programming—Fuzzy C-Means with Pigeon-Inspired Optimization algorithm (LP-FCMPIO) is proposed. Initially considering the turning radius constraint, a linear-programming-based model for fixed-wing UAV coverage path planning is established. Subsequently, to partition multiple areas effectively, an improved fuzzy clustering algorithm is introduced. Employing the pigeon-inspired optimization algorithm as the final step, an approximately optimal solution is sought. Simulation experiments demonstrate that the LP-FCMPIO, when compared to traditional FCM, achieves a more balanced clustering effect. Additionally, in contrast to traditional PIO, the planned flight paths display improved coverage of task areas, with an approximately 27.5% reduction in the number of large maneuvers. The experimental results provide validation for the effectiveness of the proposed algorithm.
Jose-Carlos Gamazo-Real, Victor Martinez-Martinez, Jaime Gomez-Gil
BLDC motor applications require precise position and speed measurements, traditionally obtained with sensors. This article presents a method for estimating those measurements without position sensors using terminal phase voltages with attenuated spurious, acquired with a FPGA that also operates a PWM-controlled inverter. Voltages are labelled with electrical and virtual rotor states using an encoder that provides training and testing data for two three-layer ANNs with perceptron-based cascade topology. The first ANN estimates the position from features of voltages with incremental timestamps, and the second ANN estimates the speed from features of position differentials considering timestamps in an acquisition window. Sensor-based training and sensorless testing at 125 to 1,500 rpm with a loaded 8-pole-pair motor obtained absolute errors of 0.8 electrical degrees and 22 rpm. Results conclude that the overall position estimation significantly improved conventional and advanced methods, and the speed estimation slightly improved conventional methods, but was worse than in advanced ones.
Today's major concern in traffic management systems includes time-efficient emergency transports. The awareness of environment and vehicle information is necessary for the emergency vehicles as well as the surrounding commercial vehicles that might be driven by inexperienced drivers to act accordingly if they both interact. The information exchange should be quick and accurate along with how much interactive the alerting system is with the drivers. Therefore, technologies like V2X-based alert systems can deal with such emergency situations and hence prevent potential health or social hazards. An alerting system as a part of a smart-connected city is proposed in this paper. The Dedicated Short Range Communication (DSRC) based system has tried to cover the major domain of information about misbehaving vehicles, any pedestrians on the road, and information about the emergency vehicle itself. The commercial vehicle also will have a similar alert system as an application of V2V and V2I. Further in this paper, a realtime monitoring system was developed using grafana dashboard which will be installed in the area's base station to monitor the vehicles in that area.
Policies to reduce transport emissions often overlook the international flow of used vehicles. We quantify the rate at which used vehicles generated CO2 and pollution for all used vehicles exported from Great Britain; a globally leading used vehicle exporter across 2005-2021. Destined for low-middle-income countries, exported vehicles fail roadworthiness standards and, even under extremely optimistic functioning as new assumptions, generate at least 13-53 percent more emissions than scrapped or on-road vehicles.
The modeling of the beating of cilia and flagella in fluids is a particularly active field of study, given the biological relevance of these organelles. Various mathematical models have been proposed to represent the nonlinear dynamics of flagella, whose motion is powered by the work of molecular motors attached to filaments composing the axoneme. Here, we formulate and solve a nonlinear model of activation based on the sliding feedback mechanism, capturing the chemical and configurational changes of molecular motors driving axonemal motion. This multiscale model bridges microscopic motor dynamics with macroscopic flagellar motion, providing insight into the emergence of oscillatory beating. We validate the framework through linear stability analysis and fully nonlinear numerical simulations, showing the onset of spontaneous oscillations. To make the analysis more comprehensive, we compare our approach with two established sliding feedback models.
The forced sweat cooling of porous media is an effective way to solve the problem of thermal protection of the leading edge of hypersonic vehicles. The pore structure and performance of porous media have a significant impact on its cooling effect and reliability. Therefore，it is very important to prepare porous materials that meet the requirements of forced sweat cooling. Herein，Ti6Al4V pre-alloyed powders were used as raw materials，and porous Ti6Al4V samples with different open porosity were prepared by compression molding combined with high-temperature sintering. The effect of the sintering temperature and holding time on the microstructures，phase compositions and mechanical properties of the samples were investigated. The results show that increasing the sintering temperature and prolonging the holding time will reduce the open porosity of the material. When the open porosity is high，the pores in the material are connected and the seepage rate is high，while the sample strength is low. When the open porosity is low，large pores in the sample are reduced and the seepage rate decreases，but the strength becomes higher. The porous Ti6Al4V sample with an open porosity of 21.8% shows the best comprehensive performance. When the porous Ti6Al4V sample is used as active thermal protection material，it can withstand flame ablation with an average heat flux of 2.5 MW/m2.
The buckling failure of the afterburner cylinder is a serious safety concern for aero-engines. To tackle this issue, the buckling simulation analysis of the afterburner cylinder was carried out by using finite element method (FEM) software to obtain the buckling mode and critical buckling loads. It was found that the afterburner cylinder was susceptible to buckling when subjected to differential pressure or the compressive force of the rear flange. Buckling would occur when the differential pressure reached 0.4 times the atmospheric pressure or when the axial compressive force on the rear flange reached 222.8 kN. Buckling was also found at the front of the cylinder under the auxiliary mount load. Additionally, under various loads on the rear flange, buckling occurred in the rear section, with the buckling mode being closely related to the load characteristics. Based on the simulation results and structural design requirements, two structural improvements were proposed, including the wall-thickening scheme and the grid reinforcement scheme. FEM simulation analysis results showed that both schemes would improve the rigidity and stability of the afterburner cylinder. For the 0.3 mm increase in the wall thickness scheme, the critical buckling load increased by 17.86% to 66.4%; for the grid reinforcement scheme, the critical buckling load increased by 169% to 619%. Therefore, the grid reinforcement scheme had a stronger anti-buckling ability and was deemed the optimal solution. The findings of this paper could provide technical support for the structural design of large-sized and thin-walled components of aero-engines.