Search Results (520)

This work presents a microwave attitude sensing method and device based on localized perturbation of a split-ring resonator (SRR). The sensor comprises a planar SRR, parallel microstrip feed lines and a metallic disk that can move along a circular trajectory. When the sensor’s orientation is modified in a plane perpendicular to the ground, the metallic disk moves within the constrained structure under the influence of gravity and changes its position relative to the SRR, modulating the local near field and the microstrip coupling state. Consequently, variations in angle are observed across multiple S-parameter channels. The mechanism is validated through simulation and experimental measurements. The measured S-parameters are used to construct a circular residual mixture-of-experts Gaussian process regression (MoE-GPR) model, which is developed for 360° angle reconstruction. In leave-one-angle-out (LOAO) validation on data sampled at 2.5° intervals, the proposed reconstruction method achieves a mean absolute error (MAE) of 0.700°. When trained on data sampled at 10° intervals and tested on a dataset sampled at 2.5° intervals, the proposed method achieves an MAE of 1.125°, demonstrating its generalization across different angular sampling conditions. As no active electronics are required at the moving sensing element, the proposed configuration has potential for integration with RF sensing and communication platforms, as well as for inclination sensing referenced to gravity, orientation detection and structural health monitoring. Full article

High-speed airborne platforms impose stringent aerodynamic constraints that restrict traditional planar antenna designs. Concurrently, multi-component echoes from extended targets and complex propagation environments induce strong signal coherence, severely degrading spatial angle estimation. To address these dual challenges, this paper proposes a straight-curved hybrid L-shaped asymmetric conformal array hardware topology tailored for cylindrical radomes. Building upon this, a millimeter-wave radar 3D point cloud imaging framework is developed for coherent targets. An orthogonal virtual manifold transformation is first devised to effectively compensate for the non-linear phase distortion induced by the conformal topology. Subsequently, a cascaded Forward-Backward Spatial Smoothing (FBSS) and Root-MUSIC framework is used for efficient signal decoherence. To resolve angle mismatches, a global cost function based on the cross-covariance Frobenius norm is formulated, which pairs independent angles and significantly suppresses spatial ghost targets. Systematic evaluations using 3D computer vision metrics demonstrate that the proposed method achieves accurate geometric restoration of aircraft targets with coherent signals. In the representative simulation, the method obtains a median point-wise localization error of 0.3986 m, a Chamfer Distance (CD) of 0.9695 m², an Earth Mover’s Distance (EMD) of 1.9504 m, and a spatial angular resolution of 1.0° under the stated test conditions. Under the stated simulation assumptions, boundary analyses indicate stable reconstruction around a post-pulse-compression SNR of −8.0 dB and a conformal curvature of 12.50 m⁻¹ ($r=0.08$ m), providing simulation-based design references for conformal radar 3D imaging. Full article

Linear dichroism (LD) optical absorption spectroscopy historically has found substantial yet still limited application in broad areas of science. In particular, full-dipole-tensor reconstruction has been onerous, usually requiring tedious and difficult measurements on single crystals at many orientations using a four-circle goniometer. As a consequence, it is very seldom done. Here, we propose, and test by numerical simulation, a simpler, faster, novel method of determining the full dipole optical absorption tensor of homogeneous planar films in real time as a function of energy (or wavelength), while requiring only minimal additional time and instrumentation. The goal of this paper is to explain the theory and to demonstrate the effectiveness and stability of the procedure using synthetic data sets. Experimental implementation and testing is deferred to future work and publications. The full-tensor spectrum, after construction from the experimental data, allows one to instantly calculate the absorption for any selected polarization direction, even those that are physically inaccessible to experimental measurement. Although our specific application in this paper is X-ray Absorption Fine Structure (XAFS) Spectroscopy, the method should be applicable to UV–Vis, IR, THz, microwave, and other wavelengths. A strength of this measurement modality is that full-tensor data can be acquired using essentially the same sort of scanning geometry that is normally used for XAFS, with only a discrete shift in the spin axis orientation between groups of scans. The additional instrumentation needed to determine the five Fourier components of the signal at each energy is minimal; two angles gives ten parameters, while six are strictly needed. Robust inversion from data to tensor elements is demonstrated, implemented via simple matrix multiplication. Outside of XAFS, FTMAPS is also expected to be applicable to diverse scientific and technological areas such as oriented bio-molecular films, semiconductor and materials physics, and process control of thin-film photovoltaics and semiconductors. Full article

In the field of 3D reconstruction for photovoltaic scenes, current texture mapping techniques frequently encounter significant texture segmentation and apparent joins in uniform plane regions, such as solar panels, because they lack geometric structural assumptions. To tackle these challenges, we introduce a new texture-mapping strategy for 3D solar panel scene reconstruction that focuses on planar structure awareness. We term the proposed method PSATM. Initially, we suggest a global constraint and a local refinement process to incorporate clear geometric structure details. This process automatically detects and labels planar regions through a region-growing approach. Next, we integrate a planar structure-aware module into the smoothness term of the Markov Random Field (MRF) energy function. This module uses dihedral angles and plane membership to adjust label transition costs, enhancing texture coherence within planar regions and maintaining smooth transitions at genuine geometric breaks. Furthermore, we establish a boundary treatment technique relying on local geometric support. This method combines area-based weighting and normal consistency to modify erroneous labels, successfully removing small remnants and smoothing texture edges. We tested the proposed PSATM with texture patch counts and visual quality measures on actual solar panel scenes. The results indicate that the proposed PSATM considerably reduces texture segmentation errors and improves texture flow and overall visual quality compared to the existing method. Full article

Broadband Capon direction-of-arrival estimation is computationally demanding because covariance processing, spatial spectrum evaluation, and steering-vector construction are repeatedly performed over multiple frequency bins and candidate directions. This study presents an efficient framework for horizontal-plane sound source azimuth estimation by combining pairwise Capon processing with recursive steering-vector generation. The array is partitioned into ordered two-microphone pairs, enabling independent $2\times 2$ covariance processing. Each pair estimates a local angle relative to its directed baseline, and the resulting constraints are fused according to the array geometry. In the implemented orthogonal cross array, both pairs lie in the horizontal plane and provide complementary components of the planar source direction. A general fusion formulation is also provided for non-orthogonal baselines and non-coincident pair midpoints. The frequency-linear phase structure of the pairwise steering vector is exploited to replace repeated trigonometric evaluations across DFT bins with recursive complex rotations. Across 80 single-source trials, the proposed method achieved an MAE of $1.88°$, an RMSE of $3.54°$, and 100% of estimates within $\pm 10°$. The steering-vector generation time decreased from 165.69 ms to 66.77 ms, while the total measured component time decreased from 172.14 ms to 70.92 ms. Additional evaluations of multi-source resolution, reverberation, moving sources, numerical stability, and irregular arrays demonstrate a practical trade-off between computational efficiency and localization robustness. Full article

Marker-based motion capture systems are widely used to estimate joint kinematics, yet their accuracy depends strongly on how anatomical segments and coordinate systems are defined. This proof-of-concept study aimed to describe and technically evaluate a structured and reproducible framework for upper-limb segment definition and joint-angle computation. Reflective markers were placed on anatomical landmarks of the trunk and upper limbs, and joint angles were computed using custom-developed MATLAB R2022b (MathWorks, Natick, MA, USA) routines. Baseline-corrected model-derived joint angles were compared with composite reference measurements obtained using a universal manual goniometer and a twin-axis biosignalsplux goniometer under predefined static conditions in two adult participants. Side-specific mean absolute error values ranged from 0.80° to 5.24°, while root mean square error values ranged from 0.86° to 5.24°. The largest discrepancies were observed during maximum wrist extension and left maximum radial deviation. The evaluated static observations showed close correspondence in several joint positions, although larger discrepancies occurred in selected end-range wrist positions. Given the limited sample, single recordings, and controlled static conditions, these findings should be interpreted as an initial demonstration of technical feasibility rather than evidence of generalisable validity or repeatability. The explicit framework provides a basis for further evaluation using larger samples, repeated marker applications, repeated trials, and dynamic multi-planar upper-limb tasks. Full article

Spray pretreatment is a key step in short-process textile cleaning, and spray deposition uniformity on the target plane directly determines the quality consistency of subsequent dyeing and finishing, with nozzle layout exerting a direct influence on this uniformity. However, the existing non-submerged free jet model suffers from physical distortions in planar flow projection, namely multi-valued flow at the origin and non-convergent far-field flow. To address this, the proportionality coefficient of the Gaussian distribution is redefined to establish a corrected planar flow distribution function with a unique origin flow and natural far-field convergence. Treating continuous fabric motion as equivalent nozzle translation, a cumulative flow superposition model for moving planes is constructed, and a collaborative optimization model for nozzle spacing, mounting height, and attitude angle is established using the Particle Swarm Optimization (PSO) algorithm, with adjacent nozzle pairs as the periodic unit. Experimental calibration shows that relative errors between theoretical and measured flow rates remain within 10%. Nozzle rotation about the local z-axis is identified as the most effective attitude variable for uniformity tuning; a 0.1 m increase in nozzle spacing reduces peak overlap flow by about 30% and overlap width by about 40%. For a dual-nozzle system on a 0.66 m-wide target plane, numerical simulation results show that the calculated cumulative flow variance decreases from 5.9193 to 1.1588, corresponding to an 80.4% reduction in the numerical uniformity index. This numerical optimization framework provides a quantitative reference for nozzle layout design in textile spraying processes. Full article

Millimeter-wave vehicular communication links are prone to blockage and suffer from severe path loss, and high mobility leads to rapidly time-varying channels. In addition, large-scale reconfigurable intelligent surface (RIS) arrays impose substantial channel-estimation overhead and phase-optimization complexity. To address these issues, a group-based and position-aided phase-optimization method is proposed for RIS-assisted millimeter-wave vehicular communications. First, an RIS-assisted uplink system is modeled with a multi-antenna base station (BS), an RIS configured as a uniform planar array (UPA) and a single-antenna vehicular terminal. Channel expressions are formulated for the direct vehicle–BS link, the vehicle–RIS link and the RIS–BS link. Rician fading, line-of-sight (LoS)-dominated millimeter-wave propagation, mobility-induced Doppler shifts and a standardized path-loss model for urban microcell street-canyon scenarios are incorporated to characterize the RIS-assisted vehicular cascaded channel. Based on this model, an optimization problem for the RIS phase-shift matrix is formulated under discrete phase-shift constraints to maximize the achievable rate per unit bandwidth. To avoid the exponential increase in complexity caused by conventional exhaustive search as the number of RIS reflecting elements increases, a successive refinement algorithm is introduced to derive an equivalent channel-gain expression. The original phase-optimization problem is then transformed into an element-wise iterative update process, thereby reducing the computational complexity of large-scale RIS phase configuration. To further reduce the reliance on full channel state information (CSI), two low-overhead phase-optimization schemes are designed. In the group-based scheme, the RIS reflecting elements are partitioned into several subgroups, with all elements in each subgroup constrained to share the same phase shift. This design reduces both the channel-estimation dimensionality and the number of optimization variables. In the position-aided scheme, the spatial coordinates of the BS, RIS and vehicle are used to derive the link distances and the associated angles of arrival and departure. Based on these geometric parameters, the vehicle–RIS–BS cascaded channel is reconstructed and a corresponding phase-alignment strategy is designed. The simulation results demonstrate that both proposed schemes achieve rates of approximately 6.5 bits ${\mathrm{s}}^{-1}{\mathrm{H}\mathrm{z}}^{-1}$ at a transmit power of 30 dBm and outperform existing phase-optimization techniques. When the successive refinement algorithm is applied, the computation time required for phase optimization with a 256-element RIS remains below 0.01 s. Under high-mobility conditions, both proposed schemes approach the performance upper bound achieved with perfect CSI, demonstrating strong robustness to channel variations. Full article

For sorting mechanisms that operate on a planar platform, the perception module may need to estimate object category, image-plane position, object extent and principal-axis orientation within the computing budget of a low-power device. This paper reports an oriented object detection workflow for a MaixCAM Pro (Shenzhen Sipeed Technology Co., Ltd., Shenzhen, China) waste-sorting prototype. The sensing output is represented by oriented bounding boxes (OBBs), which provide two-dimensional position, rectangular extent and principal-axis orientation for downstream sorting control. To adapt the detector to a small self-built dataset and INT8 deployment, class- and aspect-ratio-aware re-sampling (CAR-RS) repeats selected training images, while class- and aspect-ratio-aware calibration (CAR-Calib) selects a stratified calibration subset for post-training quantization. The YOLO11-OBB model is exported as a static ONNX graph, adapted by exposing the OBB head output tensors, compiled with TPU-MLIR and executed through native MaixPy OBB inference. On the original PC validation split, the baseline and CAR-RS models both obtain 0.995 mAP50, with mAP50–95 values of 0.935 and 0.932, respectively. CAR-RS reduces the angle mean absolute error from 3.403° to 3.201° for objects with aspect ratio greater than or equal to 1.3. On an additional 80-image cross-background test set that was not used for training or calibration, CAR-RS improves precision from 0.839 to 0.907, recall from 0.882 to 0.893 and mAP50 from 0.916 to 0.927, while mAP50–95 changes from 0.797 to 0.789. On a 100-image MaixCAM Pro validation set, the CAR-RS + CAR-Calib INT8 model achieves 0.961 precision, 0.994 recall, 0.977 F1-score and 0.980 mAP50. The deployed INT8 model occupies 11.85 MB and runs at 8.40 FPS. The results support the technical feasibility of executing an OBB detector on MaixCAM Pro, while also showing that independent-scene validation remains necessary for broader deployment. Full article

Bio-inspired serpentine robots show strong potential for operation in unstructured environments, yet existing systems often lack reliable modular docking, adaptive grasping, and an effective balance between structural stiffness and motion dexterity. This study proposes a Modular Omnidirectional Serpentine Robot (MOSR) that integrates a DNA-inspired tendon-driven helical continuum unit, an underactuated omnidirectional spherical docking gripper, and adaptive gripper fingers within a single module. The helical continuum unit provides two-degree-of-freedom compliant bending while improving axial stiffness through interleaved helices and a central constraint structure. The spherical docking gripper adopts a linkage-spring-slider underactuated mechanism to accommodate effective-diameter variations and support stable one-to-one and one-to-many docking. Gripper kinematics are modeled using an improved Denavit–Hartenberg method, and the workspace is verified by MATLAB simulation. Equivalent torsional and bending stiffness models are established for the helical continuum unit and validated by finite element analysis, with mean relative errors of 11.57% and 17.95%, respectively. Docking-angle analysis based on the receiver polar angle (θ_rec) and engager azimuth angle (θ_eng) shows that 61.1% of the receiver surface lies within the feasible docking region at an opening distance of 5.7 mm. A 3D-printed Polyamide 1010 prototype achieves a locomotion speed of 15.3 mm/s on grass and demonstrates terrain traversal, planar steering, obstacle crossing, adaptive grasping, and stable straight and oblique docking. These results verify the feasibility of integrating locomotion, grasping, and modular reconfiguration within a single serpentine robot module. Full article

Amphibious robots must reconcile two distinct mechanical requirements within a compact locomotion architecture. Terrestrial operation requires limb structures with sufficient load-bearing capacity, contact stability, and bending resistance, whereas aquatic operation benefits from a larger projected area for drag-based thrust generation. Conventional amphibious platforms often address these requirements by combining separate land and water propulsion modules, which increases structural redundancy, system mass, and hydrodynamic resistance. To reduce this conflict at the structural level, this study proposes a bioinspired origami morphing limb based on a modified Yoshimura pattern. The limb transforms between a closed cylindrical configuration for terrestrial support and an unfolded planar configuration for aquatic paddling. A vertex-splitting topology and thick-panel geometric constraints are introduced to suppress the bifurcation instability associated with the zero-thickness Yoshimura vertex, thereby obtaining a deterministic single-degree-of-freedom folding path suitable for robotic actuation. A screw-theory-based kinematic model is established to relate the active driving angle to the passive folding angle, and geometric parameter analysis is used to connect the folding state with load-bearing and paddling morphologies. A quadruped amphibious robot prototype is fabricated using rigid polylactic acid panels and flexible thermoplastic polyurethane hinges. Prototype-level observations qualitatively demonstrate reversible transformation within the tested operating range and show walking, crawling, rolling, water-entry, and underwater locomotion modes. Full article

Background: Atrial functional mitral regurgitation (AFMR) results from left atrial (LA) remodeling and mitral annular dilation in patients with atrial fibrillation and preserved left ventricular function. While annular dilation is considered the primary mechanism, the role of leaflet morphology in determining regurgitation severity remains incompletely characterized. We hypothesized that leaflet morphology, rather than annular dilation alone, is more strongly correlated with AFMR severity. Methods: We prospectively studied 113 consecutive patients with persistent atrial fibrillation and AFMR who underwent comprehensive three-dimensional transesophageal echocardiography (3D TEE). Mitral valve geometry was analyzed using dedicated software (EchoPAC v.206, 3D MVQ Analysis). Patients were classified according to MR severity: non-significant (grade 0–1) versus moderate or severe (grade 2–3). Logistic regression identified predictors of moderate or severe AFMR. Results: Moderate or severe MR was present in 57 patients (50.4%). Compared with patients with non-significant MR, those with moderate or severe regurgitation exhibited larger annular dimensions (3D annular area 12.7 vs. 11.4 cm², p = 0.005), reduced non-planar angle (145° vs. 149°, p = 0.027), greater leaflet areas, and increased tethering parameters. Anterior leaflet length was markedly greater in the moderate/severe group (2.7 vs. 2.4 cm, p = 0.001). In different multivariable analyses models adjusting for age, sex, LA diameter, and 3D annular area, anterior leaflet length (OR 3.16 per SD, 95% CI 1.65–6.61, p = 0.001), anterior leaflet area (OR 3.42 per SD, 95% CI 1.48–8.74, p = 0.006), and posterior leaflet length (OR 0.39 per SD, 95% CI 0.15–0.86, p = 0.043) remained independently associated with moderate or severe AFMR. ROC analysis demonstrated good discriminative ability for anterior leaflet length (AUC 0.746, with an optimal threshold of 2.55 cm, sensitivity 75%, specificity 68%), and anterior leaflet area (AUC 0.680, and an optimal cut-off value of 5.75 cm², sensitivity 70.2%, specificity of 64.3%). Conclusions: In patients with AFMR, anterior leaflet dimensions assessed by 3D TEE are the strongest independent predictors of moderate or severe regurgitation, outperforming annular parameters. These measurements may represent practical tools for risk stratification and patient selection for intervention. Full article

In order to address the issue of rapidly divergent positioning errors of a single-platform inertial navigation system (INS) in GNSS-denied environments, this paper proposes a cross-platform cooperative navigation method based on relative range and angle measurements. The observability of the cooperative navigation system under different motion strategies is investigated using Fisher information matrix (FIM) right null-space analysis combined with singular value decomposition (SVD). The results show that with relative range and angle measurement constraints, all inertial sensor biases can be effectively estimated by two strapdown inertial navigation systems (SINSs) moving along a simple trajectory, thereby improving the navigation accuracy. Experimental results demonstrate that compared to the autonomous navigation mode, the average positioning accuracy of the two SINSs improves by 77.4% and 68.4% respectively after 3 h of cooperative navigation along the prescribed trajectory. Using relative range and angle measurements, the proposed method requires only two SINSs and relatively simple planar motion, without the need for high-precision reference benchmarks, complex three-dimensional excitation trajectories, or turntable modulation. It reduces system complexity and motion requirements, providing an effective and easy-to-implement solution for ground vehicular positioning and orientation and other cross-platform cooperative navigation tasks in GNSS-denied environments. Full article

To mitigate the spatial variation in shot velocities induced by nozzle geometry during shot peening of an arced surface (a peening configuration that uses an arc-shaped emission surface to replicate the actual nozzle-induced scattering effect, as distinct from the peening of a curved workpiece surface), this study introduces an approach for assessing surface roughness and residual stress through an average energy density function that integrates both the particle scattering angle and energy distribution characteristics. The study introduces a novel approach by incorporating an equivalent emission arc surface into finite element simulations. This innovative model effectively captures the scattering phenomenon observed in real shot peening processes and identifies this factor as a critical optimization parameter within energy field theory. A discrete element method–finite element method (DEM–FEM) coupled model has been established to simulate the shot peening process across various scattering angles. Systematic investigations reveal the significant impact of the scattering angle on the integrity of AISI 9310 steel, particularly in terms of residual stress and surface roughness profiles. The simulation outcomes demonstrate that the maximum residual compressive stress exhibits a non-linear trend: initially decreasing before increasing as the scattering angle is elevated, with the average energy density attaining its peak at a scattering angle of approximately 8°. Compared to conventional planar shot peening, the arc shot peening technique induces more pronounced surface strengthening effects in critical areas. These insights offer valuable theoretical guidance for optimizing the shot peening of an arced surface parameters, thereby enhancing surface integrity and potential fatigue performance. Full article

Reliable estimation of vehicle states, tire cornering stiffness, and the tire-road adhesion coefficient are essential for vehicle lateral stability and intelligent chassis control. Under low adhesion, nonlinear tire operation, and weak excitation, lateral-force residuals are jointly affected by cornering-stiffness variation, adhesion-coefficient variation, and tire-force saturation, which may cause erroneous parameter adaptation. This paper proposes a reliability- and sensitivity-guided co-estimation method for vehicle states, tire cornering stiffness, and the tire-road adhesion coefficient. A hierarchical framework is developed based on a planar 3-DOF vehicle model and a Fiala-type nonlinear tire model. Front- and rear-axle lateral-force pseudo-measurements are reconstructed from lateral acceleration and yaw angular acceleration, without requiring additional tire-force sensors. Parameter-update reliability is evaluated by considering lateral excitation, longitudinal slip, adhesion utilization, and normalized lateral-force residual consistency. Normalized lateral-force sensitivities are then used to allocate the residual between the cornering-stiffness and adhesion-coefficient update channels. CarSim/Simulink co-simulations under high-, intermediate-, and low-adhesion double-lane-change maneuvers demonstrate that the proposed method improves sideslip-angle and lateral-velocity estimation accuracy, suppresses erroneous cornering-stiffness adaptation, and provides more stable estimates of the tire-road adhesion coefficient. Full article