Search Results (2,263)

Cable-driven minimally invasive surgical robots suffer from significant motion inaccuracies due to nonlinear transmission effects such as friction, elasticity, and hysteresis. These factors lead to strong nonlinear and direction-dependent behaviors, making accurate modeling and compensation challenging. To address this issue, this study investigates the error characteristics of a cable-driven surgical robot prototype based on its structural features. A kinematic model is first established, and geometric errors are corrected through Denavit–Hartenberg (DH) parameter identification using a least-squares method. To further characterize nonlinear effects, the LuGre friction model and equivalent stiffness theory are introduced to analyze friction and cable deformation behaviors. Since physics-based models alone cannot accurately capture the coupled nonlinear errors, a radial basis function (RBF) neural network is employed to approximate the residual errors. To enable real-time implementation, the predicted errors are further simplified using equivalent polynomial functions for efficient compensation. Experimental results demonstrate that the proposed method significantly improves the motion accuracy of the cable-driven system, effectively reducing both tracking error and hysteresis effects. By integrating mechanism-based modeling with data-driven compensation, this approach provides a practical and effective solution for precision enhancement in cable-driven surgical robotic systems. Full article

This current study aimed to determine the impact of Mitoquinone (MitoQ) on the quality of frozen–thawed donkey semen. Ejaculates were collected from six male donkeys (Equus asinus), and ejaculates were polled and aliquoted into 12 samples. Samples were diluted with TRIS–egg yolk glycerol extender that reached 200 million sperm/mL. After centrifugation, the pellet was diluted at 1:15 with TRIS–egg yolk glycerol extender and divided into the five main groups containing MitoQ with different concentrations: 0 nmol/mL (control; MitoQ0), 100 nmol/mL (MitoQ1), 150 nmol/mL (MitoQ2), 200 nmol/mL (MitoQ3), and 250 nmol/mL (MitoQ4). After thawing, semen quality was evaluated using CASA kinematic parameters, fluorescence microscopy, and biochemical markers such as alanine and aspartate aminotransferase levels (ALT and AST). Malondialdehyde (MDA) and catalase (CAT) levels were also measured. MitoQ1 with 100 nmol/mL significantly increased total motility (p = 0.04), progressive motility (p = 0.04), viability (p = 0.03), kinetic parameters (p = 0.04), linearity (p = 0.02), and straightness (p = 0.04). A significant decline in MDA (p = 0.02), ALT (p = 0.03), and AST (p = 0.03) levels in MitoQ1 with 100 nmol/mL was found, with an elevation of CAT levels (p = 0.02) compared to other concentrations and the control in TRIS–egg yolk glycerol extender. Different concentrations of MitoQ did not affect acrosome and DNA integrity. In conclusion, the addition of MitoQ during cryopreservation has a positive effect on sperm motility, viability, and kinetic parameters, especially at a concentration of 100 nmol/mL when used with a TRIS–egg yolk glycerol extender for frozen–thawed donkey sperm. Full article

The assessment of sperm quality is essential for improving reproductive efficiency in aquaculture species such as common carp (Cyprinus carpio). While sperm motility is widely used as a key functional indicator, the predictive value of oxidative protein markers for sperm performance remains unclear. In this study, sperm motility and kinematic parameters were assessed using computer-assisted sperm analysis (CASA). Markers of oxidative status, advanced oxidation protein products (AOPPs), ceruloplasmin (CP), and total protein concentration were quantified in samples. The results showed relatively high total motility (70.51%) and progressive motility (69.00%), indicating good sperm quality. No statistically significant correlations (p > 0.0.5) were found between AOPP or CP and sperm motility. Protein concentration was positively associated with motility parameters, including curvilinear velocity (VCL) and amplitude of lateral head displacement (ALH). A significant negative correlation was found between Fulton’s condition factor (FCF) and AOPP (r = −0.686; p < 0.05), indicating that individuals with higher body condition had lower oxidative protein damage. These findings suggest that oxidative protein markers may not directly reflect sperm motility, highlighting the potential value of including additional oxidative stress-related parameters in sperm quality assessment. Full article

A comprehensive numerical method was developed to ensure energy-efficient operating modes of a linear motion module powered by an induction motor. The proposed approach is based on minimizing inertial torque, accounting for the inertial properties of the drive components and the load carriage, followed by structural-parametric optimization and dynamic modeling. For the optimization of the drive system, comprising an intermediate gear stage and a primary ball screw mechanism, a normalization-based method combined with numerical parameter sweep was employed. The optimization process yielded optimal values of the screw lead and the number of gear teeth, which were further validated in terms of Pareto optimality. The carriage design was optimized with respect to mass, strength constraints, and dynamic stiffness using the finite element method. For the developed linear motion module, dynamic behavior was simulated by means of a system of nonlinear differential equations, taking into account the electromagnetic characteristics of the induction motor and the nonlinearities of the gear mesh. As a result of the comprehensive approach, the kinematic, force, and energy characteristics of the linear motion module, which was optimized at the design stage, were determined. Full article

Cryopreservation of gametes is crucial for conserving genetic diversity in livestock and endangered species, but the process can significantly impair sperm quality due to oxidative stress. Our aim was to evaluate the impacts of coenzyme Q10 (CoQ10) supplementation on the in vitro quality of cooled and cryopreserved goat semen. Semen samples collected from six mature Saanen bucks were pooled then diluted with AndroMed^® semen extender to a final concentration of 800 × 10⁶ sperm/mL. Diluted semen was supplemented with 0, 1, 2, 5, 10, and 20 µM CoQ10. Extended semen was either cooled at 4 °C for 72 h or cryopreserved using a Styrofoam box in which the straws were arranged on the freezing rack and placed 4 cm over the liquid nitrogen (LN₂) for 10 min then stored in a LN₂ tank for one-week before being thawed at 37 °C for 30 sec. Sperm quality, including total and progressive motility, sperm kinematics, live sperm %, and sperm membrane integrity, was assessed at 0 h (fresh semen), and 24, 48, and 72 h post-cooling. For post-thaw sperm, we evaluated the same parameters plus acrosome integrity, mitochondrial activity, lipid peroxidation, and sperm ultrastructural changes using scanning electron microscopy (SEM). The pooled semen sample was considered the experimental unit for all treatments. Cooled semen data were analyzed using a General Linear Model (GLM) with univariate analysis, followed by Tukey’s test for multiple comparisons. In contrast, data from frozen–thawed semen were analyzed using one-way analysis of variance (ANOVA) followed by Tukey’s test. CoQ10 supplementation at 10 and 20 µM significantly (p < 0.05) improved sperm motility, viability, and membrane integrity in cooled and frozen–thawed semen in comparison with the control group (0 µM CoQ10). Moreover, the same concentrations significantly (p < 0.05) enhanced acrosome integrity, mitochondrial activity, and reduced the percentages of sperm with lipid peroxidation in frozen–thawed semen. Furthermore, 10 and 20 µM CoQ10 significantly mitigated the ultrastructural defects in frozen–thawed spermatozoa. In conclusion, CoQ10 supplementation during the cooling and cryopreservation of dairy goat semen significantly improved sperm quality. Among the tested concentrations, 10 and 20 µM exhibited the most favorable outcomes. Full article

Robotics optimization is essential for improving the performance, efficiency, and reliability of robotic systems, especially when dealing with complex engineering problems involving multiple conflicting objectives. Algorithm-specific parameter-free metaheuristic algorithms have gained attention in such applications because they eliminate the need for problem-specific parameter tuning. However, their performance can be further enhanced by improving convergence and maintaining solution diversity in multi-objective optimization. This paper proposes three multi-objective variants—archive, opposition, and self-adaptive multi-population (SAMP)—for the algorithm-specific parameter-free BxR algorithms such as Best–Mean–Random (BMR), Best–Worst–Random (BWR), and Best–Mean–Worst–Random (BMWR). The proposed variants are evaluated on five robotic optimization problems spanning two to six objectives, including Autonomous Underwater Vehicle shape optimization, power line inspection robot design, inverse kinematics of a 4-DOF manipulator, wall-building robot trajectory planning, and optimization of a reconfigurable parallel cutting and grinding mechanism. Their performance is compared with several established multi-objective algorithms using metrics such as GD, IGD, SPC, and HV, supported by rigorous statistical testing involving Friedman tests, Conover post hoc analysis with Holm correction, and Vargha–Delaney A₁₂ effect sizes over 30 independent runs. The results show that archive variants achieve the best IGD rank in four of the five case studies and the best HV rank in three of them, with the five-objective trajectory planning problem being the sole exception where SAMP and base BxR variants show improved IGD performance. The base BxR algorithms prove to be strong competitors, consistently outperforming established parameter-dependent methods on IGD across all five problems. The opposition variants do not provide consistent improvement; however, they also do not cause catastrophic degradation, suggesting that refined opposition strategies warrant further investigation. The study demonstrates the effectiveness of the proposed algorithms as practical optimization tools for complex robotic optimization problems. Full article

Benthic AUVs (underwater quadruped robots) merge the cruising efficiency of submersibles with the bottom-crawling stability of legged robots for unstructured deep-sea exploration. However, the deliberate separation of the center of gravity and buoyancy—essential for static stability—generates a significant righting moment. When climbing steep slopes, this moment resists hull alignment. If the slope exceeds the robot’s maximum hydrostatic pitch limit, conventional inverse kinematics algorithms fail: the hind legs lose ground contact and propulsion is lost. To overcome this, this paper proposes a framework integrating optimal force distribution, adaptive trajectory probing, and admittance control. An analytical multi-point moment balance model derives the terrain-adaptive pitch boundaries. A Quadratic Program (QP) then distributes contact forces, tasking front legs with stabilizing the righting moment while hind legs provide thrust. During the swing phase, adaptive Bezier sequences prevent anterior slope collisions and ensure posterior ground contact. Furthermore, a Cartesian admittance controller provides active compliance to manage the nonlinear friction of dynamic waterproof seals. Validated via a high-fidelity physics-based simulation model calibrated against physical pool trials, the robot achieved robust traversal of $15°$ and $33°$ steep slopes. Statistical robustness is substantiated via a 30-trial Monte Carlo study, where postural stability remained remarkably consistent with a mean Pitch RMSE of $2.88°$ across a $\pm 10\%$ parameter uncertainty envelope. Compared to traditional baseline algorithms, the proposed method successfully suppressed torque chattering by $54.1\%$ in the high-frequency band (2–$50\mathrm{Hz}$) and improved energetic efficiency by up to $43\%$ on steep gradients. These findings offer a validated control architecture for heavy-duty deep-sea platforms navigating complex benthic topographies. Full article

This study presents a probabilistic seismic fragility assessment of a jointed rock slope by integrating field characterization, incremental dynamic analysis (IDA), and numerical modeling. Dominant joint sets are identified through field mapping, and key discontinuity parameters are estimated for the Barton–Bandis non-linear shear strength criterion. Dynamic simulations are performed using the distinct element method with the continuously yielding (C-Y) joint model to capture progressive shear degradation. Twenty real earthquake ground-motion records are scaled incrementally to perform IDA, with critical block displacement and cumulative joint slip adopted as engineering demand parameters (EDPs). A probabilistic seismic demand model (PSDM) is developed to correlate peak ground acceleration (PGA) with EDPs. Kinematic analysis indicates that planar failure along joint set 1 is the most likely failure mechanism (90% probability), followed by wedge failure along the intersection of joint sets 1 and 2 (52%). Fragility curves are derived for three displacement-based damage states: minor (1 cm), moderate (5 cm), and severe (15 cm). The results demonstrate that seismic deformation is strongly controlled by discontinuity geometry and progressive joint slip, with the slope exceeding the severe damage state at PGA levels as low as 0.4 g, indicating high seismic vulnerability. This highlights the importance of integrating field characterization with dynamic numerical modeling for reliable seismic stability assessment of such discontinuous rock mass. Future work should incorporate larger datasets, in situ testing, and 3D modeling to enhance assessment reliability. Full article

Brake-induced steering wheel shimmy is a critical nonlinear dynamic phenomenon that severely compromises vehicle handling stability and driving safety. While clearances in steering mechanism kinematic pairs are widely recognized as a primary cause of shimmy instability, the coupling effect of multiple concurrent clearances remains poorly characterized, particularly under transient braking conditions. In this work, a 5-degree-of-freedom non-autonomous dynamic model of brake-induced shimmy is developed using Lagrange’s equations. The model comprehensively incorporates the non-smooth contact behavior of multiple clearance joints, transient braking axle load transfer, and the longitudinal–lateral coupling nonlinearity of tires. The nonlinear dynamic evolution of the system is investigated through phase portraits, Poincaré sections, and continuous wavelet transform analysis. Numerical results demonstrate that multi-clearance coupling increases the peak shimmy angle by more than 40% compared to the single-clearance case. As the clearance magnitude increases from 0.05 mm to 0.40 mm, the system undergoes a transition from stable periodic motion to high-dimensional chaos, accompanied by a 67% reduction in vibration energy concentration at the 0.4 mm clearance level. This study elucidates the nonlinear mechanism underlying clearance-induced brake shimmy, providing a robust theoretical foundation for steering system parameter optimization and shimmy mitigation strategies. Full article

As a key component of sugarcane harvesting machinery, the spiral sugarcane lifter (SSL) enhances harvesting quality by lifting lodged sugarcane (LSC) into a posture suitable for stalk-base cutting and feeding. To improve the SSL’s lifting performance for LSC, this study developed a rigid–flexible coupling (RFC) simulation model of the sugarcane–SSL interaction and conducted kinematic and force analyses to identify the main shortcomings of the original design. Critical structural and operational parameters affecting lifting performance–including the lifting roller pitch, roller diameter, roller inclination angle, and lifter shoe length—were redesigned using mechanism-based constraints and simulation-assisted evaluation. The optimized SSL exhibited increased lifting speed and stability under low–speed, severe–lodging conditions. Under side-forward lodging (side deflection angle = 30°), the average maximum vertical height of the centroid (VHC) increased by 40.36%, and paired comparisons across three simulated lodging-angle scenarios showed significant improvement. Field tests under severe lodging at 0.55 m/s (≈2 km/h) yielded an average absolute simulation–to–field error of 5.37%. These findings support the effectiveness of the proposed parameter redesign for the tested medium-size harvester, although further validation is required under higher forward speeds, greater biomass throughput, and more variable soil conditions. Full article

Background: Patellar motion trajectory (PMT) is a key kinematic parameter for evaluating patellofemoral joint (PFJ) stability, but traditional static imaging indices are unable to capture the dynamic six-degrees-of-freedom (6-DOF) characteristics of patellar motion throughout the entire knee flexion–extension cycle. Four-dimensional computed tomography (4D-CT) facilitates in vivo dynamic imaging of the PFJ, while the systematic classification of PMT in asymptomatic populations has remained underexplored. Methods: A retrospective cross-sectional study was performed on 64 asymptomatic and functionally normal knees that underwent 4D-CT dynamic scanning from March 2021 to December 2025. Patellar 6-DOF kinematic data during 0° to 90° of knee flexion–extension were extracted through manifold optimization, automatic segmentation, and spatial registration. Following standardization of the motion cycle, unsupervised K-means clustering was employed to classify PMT phenotypes, with nonparametric tests used to analyze intergroup kinematic differences and evaluate clustering quality. Results: Three distinct PMT types were identified based on clustering validity indices, including a silhouette score of 0.381, a Davies-Bouldin index of 0.916, and a Calinski–Harabasz index of 44.06: Type 1 (7.81%, 35.11 ± 6.56 mm), Type 2 (56.25%, 15.67 ± 6.59 mm), and Type 3 (35.94%, 2.82 ± 2.41 mm). Lateral translation (Tx) served as the dominant determinant for PMT typing (p < 0.001), whereas non-lateral DOF parameters exhibited no consistent intergroup differences. Postural DOFs exhibited coupled fluctuations with Tx but had no independent stratification effect. Traditional static imaging parameters demonstrated no consistent correlation with these dynamic subtypes. Conclusions: Functionally asymptomatic knees exhibited three in vivo patellar 6-DOF motion trajectory phenotypes dominated by lateral translation amplitude. This 4D-CT-based typing framework provides a dynamic kinematic baseline for PFJ stability evaluation and lays a foundation for individualized optimization of ligament reconstruction and pathophysiological research of patellofemoral disorders. Full article

Background: The primary aim of this study is to evaluate the concurrent validity and practical applicability of the MetricVBT smartphone application compared with the Vitruve linear position transducer (VitruveLPT) for measuring mean velocity (MV) and peak velocity (PV) at one-repetition maximum (1-RM) during the Smith machine bench press (SMBP). A secondary aim is to assess the range of motion (ROM). Methods: Eighteen resistance-trained men completed a single 1-RM SMBP exercise test, with barbell kinematics simultaneously recorded using VitruveLPT and MetricVBT. Between-device differences were assessed using Wilcoxon signed-rank and paired-sample t-tests with Bonferroni correction (α ≤ 0.05). Associations were examined using Spearman’s (ρ) and Pearson’s (r) correlations, and absolute agreement was evaluated via intraclass correlation coefficients (ICC) and Bland-Altman analyses. Results: Significant differences were observed for MV (p = 0.026), but not for PV (p = 0.143) or ROM (p = 0.130). PV showed a very high correlation (r = 0.91, p < 0.001), whereas MV (ρ = 0.65, p = 0.002) and ROM (ρ = 0.55, p = 0.018) demonstrated moderate correlations. Agreement was good for PV (ICC = 0.888), moderate for MV (ICC = 0.612), and poor for ROM (ICC = 0.236). Mean bias was small for MV (−0.02 m·s⁻¹) and PV (0.02 m·s⁻¹), whereas ROM showed a larger bias (1.64 cm) and wide limits-of-agreement (LoA) for all variables (MV: −0.07 to 0.04 m·s⁻¹; PV: −0.08 to 0.11 m·s⁻¹; ROM: −13.82 to 17.10 cm). Conclusions: Although no statistically significant differences were observed, MetricVBT did not meet the reliability criteria for velocity monitoring. Despite small mean bias, the wide LoA for MV, PV, and ROM indicates that MetricVBT and VitruveLPT are not interchangeable for assessing performance parameters. Full article

Real-time tracking of high-speed targets in autonomous systems requires detection and decision-making pipelines that can operate within sub-millisecond time budgets. Single Photon Avalanche Diode (SPAD) sensors are well suited for this task, offering 10 kHz Time-of-Flight (ToF) measurements with picosecond timing precision. However, processing such high-frequency time-series data with conventional deep learning models introduces computational bottlenecks that are difficult to handle on resource-constrained embedded hardware. This paper presents an ultra-lightweight, dual-head architecture built on the MiniRocket transformation algorithm, where a single shared feature extractor simultaneously feeds two independent decision pathways: one for multi-class target classification and one for 3-parameter kinematic regression covering velocity, pitch, and yaw. As a single-pixel sensor, the device provides only 1D range information; lateral 3D spatial localization is outside the scope of this work. To the best of the authors’ knowledge, this is the first application of MiniRocket to continuous kinematic estimation from high-frequency sensor data. Since collecting labeled physical flight data at these speeds is largely infeasible, a physics-based ray-casting simulation was developed to generate a 55,440-sample dataset across four 3D CAD target models under varying speed (100–450 m/s), orientation, and noise conditions. The proposed architecture achieves 98.6% classification accuracy and a velocity Mean Absolute Error (MAE) of 0.26 m/s, with orientation estimation yielding a pitch MAE of 3.47° and a yaw MAE of 2.46°—values consistent across all five cross-validation folds, indicating that the orientation performance floor is governed by the sensor’s physical angular resolution rather than by model capacity. With approximately 27,000 trainable parameters, the system completes full dual-task inference in 0.56 ms on a 16-core CPU (1785 Frames Per Second-FPS), satisfying the 1 ms real-time constraint of a 10 kHz sensor without GPU acceleration. It should be noted that the single-pixel SPAD architecture provides only 1D range-along-beam information; full 3D spatial localization is physically not extractable from a single sensor and is not addressed in this study. Full article

Sustainable production in dental and orthodontic 3D printing has gained increasing attention due to environmental concerns and the need for cost-effective and resource-saving solutions. This study presents a proof of concept for using recycled polymers and fused granular fabrication (FGF) in a closed-loop 3D printing approach, omitting intermediate filament manufacturing. A desktop 3D printer served as the kinematic platform and was modified with a pellet-based extruder to directly process recycled polyethylene terephthalate glycol (PETG) flakes, obtained by shredding previously printed PETG parts, into dental models. Dimensional accuracy was evaluated using optical 3D scanning analysis. The results indicate that models produced from recycled PETG are, in principle, suitable for dental and orthodontic applications within the investigated scope. This technical note provides initial evidence supporting the integration of recycled thermoplastics into dental and orthodontic model fabrication as part of sustainable additive manufacturing workflows. Potential pathways for workflow integration in clinical and laboratory environments, as well as directions for future research, are outlined, including the optimization of printing parameters and process stability. The main technical challenges were unreliable feedstock flow, causing bridging and jamming, while thermal creep from insufficient inlet cooling promoted premature softening of the flakes, causing torque spikes and unstable feeding. Full article

This paper proposes an adaptive residual extended Kalman filter method optimized by a multi-strategy improved parrot optimization algorithm (MIPO-ARKEKF) to improve the kinematic parameter calibration accuracy and efficiency of robotic polishing systems. To address the limitations of the standard extended Kalman filter (EKF), such as truncation-error accumulation during repeated linearization and sensitivity to manually selected noise parameters, an integrated improvement framework is developed. Specifically, a gradient stabilizer based on state-estimation increments is introduced to alleviate estimation degradation caused by accumulated truncation errors, while the proposed MIPO algorithm is employed to adaptively optimize the process and measurement noise covariance matrices, thereby improving the robustness of parameter identification under practical measurement uncertainty. The calibration process is established on the basis of high-precision external measurement data obtained from the robotic polishing system. In benchmark-function tests, MIPO demonstrates superior convergence performance. In physical experiments based on a KUKA KR210 R2700 robot, the proposed MIPO-ARKEKF method reduces the root mean square positioning error from 0.8927 mm to 0.4858 mm, corresponding to a 45.58% improvement in accuracy. Compared with representative hybrid calibration methods, the proposed method achieves comparable compensation accuracy while reducing computation time by 34.88% to 65.08%. Practical polishing experiments on ultra-low-expansion glass lenses further verify that the proposed method effectively improves end-effector trajectory tracking accuracy and polishing quality, providing an efficient solution for high-precision robotic polishing. Full article