Search Results (357)

This work introduces a comprehensive vision-based framework for autonomous space debris removal using robotic manipulators. A real-time debris detection module is built upon the YOLOv8 architecture, ensuring reliable target localization under varying illumination and occlusion conditions. Following detection, object motion states are estimated through a calibrated binocular vision system coupled with a physics-based collision model. Smooth interception trajectories are generated via a particle swarm optimization strategy integrated with a 5–5–5 polynomial interpolation scheme, enabling continuous and time-optimal end-effector motions. To anticipate future arm movements, a Transformer-based sequence predictor is enhanced by replacing conventional multilayer perceptrons with Kolmogorov–Arnold networks (KANs), improving both parameter efficiency and interpretability. In practice, the Transformer+KAN model compensates the manipulator’s trajectory planner to adapt to more complex scenarios. Each component is then evaluated separately in simulation, demonstrating stable tracking performance, precise trajectory execution, and robust motion prediction for intelligent on-orbit servicing. Full article

Background/Objectives: The Tecnis Eyhance is an enhanced monofocal intraocular lens (IOL) designed to improve intermediate vision without compromising distance clarity or increasing the incidence of photic phenomena. Although short-term results have been encouraging, long-term data remain limited. This study presents the 5-year follow-up of a previously published 6-month clinical evaluation, aiming to assess the stability of visual, optical, and patient-reported outcomes over time. Methods: A single-center retrospective study of 18 patients (36 eyes) undergoing bilateral Tecnis Eyhance IOL implantation was conducted. The same cohort from the original 6-month study was re-evaluated after a mean follow-up of 5 years. Visual acuity (distance, intermediate, near), defocus curves, contrast sensitivity, optical quality, effective lens position (ELP), halo size, and patient-reported measures were assessed. Results: Visual acuity remained stable across all distances, with binocular uncorrected intermediate visual acuity (UIVA) ≤ 0.2 logMAR in all patients. No significant changes were observed in optical quality parameters or contrast sensitivity. ELP remained consistent over time (p = 0.298), and posterior capsule opacification (PCO) requiring Nd:YAG capsulotomy developed in 5% of the eyes. Halo size was mild, and subjective glare perception did not increase. Spectacle independence remained high for distance (100%) and intermediate (more than 75%) tasks. Conclusions: This 5-year follow-up study confirms the long-term stability and effectiveness of the Tecnis Eyhance IOL. These findings support its long-term use as a stable monofocal IOL with enhanced intermediate function. Full article

The real-time detection and localization of dynamic targets in cattle farms are crucial for the effective operation of intelligent equipment. To overcome the limitations of wearable devices, including high costs and operational stress, this paper proposes a lightweight, non-contact solution. The goal is to improve the accuracy and efficiency of target localization while reducing the complexity of the system. A novel approach is introduced based on YOLOv8s, incorporating a C2f_DW_StarBlock module. The system fuses binocular images from a ZED2i camera with GPS and IMU data to form a multimodal ranging and localization module. Experimental results demonstrate a 36.03% reduction in model parameters, a 33.45% decrease in computational complexity, and a 38.67% reduction in model size. The maximum ranging error is 4.41%, with localization standard deviations of 1.02 m (longitude) and 1.10 m (latitude). The model is successfully integrated into an ROS system, achieving stable real-time performance. This solution offers the advantages of being lightweight, non-contact, and low-maintenance, providing strong support for intelligent farm management and multi-target monitoring. Full article

Background: Spectacle independence is a key goal in refractive lens exchange (RLE), especially in younger, high-expectation patients. This study evaluates a novel extended monovision approach combining a monofocal aspheric intraocular lens (IOL) in the dominant eye with a rotationally asymmetric bifocal extended-depth-of-focus (EDOF) IOL in the non-dominant eye. The strategy aims to optimize full-range visual performance while minimizing photic phenomena. Methods: In this retrospective cohort study, presbyopic patients underwent bilateral RLE with a monofocal IOL (Hoya Vivinex XC1-SP; target: 0 diopters [D]) in the dominant eye and a rotationally asymmetric bifocal EDOF IOL (LENTIS LS-313 MF15; addition: +1.5 D; target: −1.25 D) in the non-dominant eye. Uncorrected distance visual acuity (UDVA, at 6 m), uncorrected intermediate visual acuity (UIVA, at 66 cm), and uncorrected near visual acuity (UNVA, at 36 cm) were assessed. Additional evaluations included binocular defocus curves, contrast sensitivity, stereoacuity, and photic phenomena. Spectacle independence and satisfaction were measured using the PRSIQ and NEI-RQL-42 questionnaires. Results: A total of 38 patients (76 eyes) were included. The mean postoperative binocular UDVA, UIVA, and UNVA were −0.03 ± 0.08, −0.08 ± 0.09, and 0.04 ± 0.08 logMAR, respectively. The defocus curve peaked at 0.0 D (6 m) with a mean visual acuity of −0.03 ± 0.08 logMAR. Functional vision better than 0.2 logMAR extended over defocus steps from +1.00 to −3.25 D. All patients were spectacle-independent for distance and intermediate vision, and 84% reported complete spectacle independence. Contrast sensitivity was within normal limits for age. Minimal photic phenomena were reported, and stereoacuity was preserved in 97% of patients (≤100 arcseconds). Conclusions: This innovative extended monovision approach, combining two different IOLs in a mini-monovision setup, provides excellent uncorrected visual acuity at all distances, high spectacle independence, and minimal side effects. It represents a compelling alternative to multifocal IOL implantation in presbyopic RLE candidates. Full article

Background: Early identification of visual disorders in children is essential to prevent long-term visual impairment and support academic development. Despite the recognized importance of visual screenings, no universal consensus exists on which visual parameters or threshold values should be used, particularly for measuring visual acuity (VA) in pediatric populations. Objectives: This study aimed to develop age-related percentile norms for VA using LEA symbol charts. Methods: A sample of Italian schoolchildren aged 5 to 15 years (n = 1510) participated in the study. Data were collected retrospectively from school-based vision screenings conducted across 12 schools in the Lombardy and Piedmont regions from 2010 to 2019. Monocular and binocular VA were measured at 3 m using a standardized LEA symbol chart, and values were scored letter-by-letter on a LogMAR scale. Smoothed percentile curves were derived using Box–Cox, Cole, and Green distribution modeling and regression analysis. Results: The results showed a non-linear improvement in VA with age. Compared to prior studies, LEA symbols yielded slightly lower VA scores, reinforcing the need for chart-specific norms. The 50th percentile VA improved from approximately +0.07 LogMAR at age 6 to about −0.09 LogMAR at age 15. Conclusions: These findings highlight the importance of age-specific, chart-specific, and statistically robust reference data for VA screening in children. The derived percentile tables offer a more sensitive tool than fixed cut-offs for identifying visual anomalies and tailoring clinical interventions. This work contributes to standardizing pediatric VA screening practices and improving early detection of visual deficits. Full article

Functional Optical Balance (FOB) is a novel personalized strategy for intraocular lens (IOL) selection in cataract surgery, designed to reconcile the trade-off between optical quality and spectacle independence. FOB is a core concept aiming to maximize visual performance by treating the two eyes as a synergistic pair. One eye (often the dominant eye) is optimized for pristine optical quality (typically distance vision with a high-contrast monofocal or low-add IOL). In contrast, the fellow eye is optimized for extended depth of focus and pseudoaccommodation (using an extended depth-of-focus or multifocal/trifocal IOL) to reduce dependence on glasses. This review introduces the rationale and theoretical basis for FOB, including the interplay of depth of focus and optical aberrations, binocular summation, ocular dominance, and neuroadaptation. We discuss the clinical implementation of FOB: how the first-eye results guide the second-eye IOL choice in a tailored “mix-and-match” approach, as well as practical workflow considerations such as patient selection, ocular measurements, and decision algorithms. We also review current evidence from the literature on asymmetric IOL combinations (e.g., monofocal plus multifocal, or EDOF plus trifocal), highlighting visual outcomes, patient satisfaction, and remaining evidence gaps. Overall, FOB represents a paradigm shift toward binocular, patient-customized refractive planning. Early clinical reports suggest it can deliver a continuous range of vision without significantly compromising visual quality, though careful patient counseling and case selection are essential. Future directions include the integration of advanced diagnostics, artificial intelligence-driven IOL planning tools, and adaptive optics simulations to refine this personalized approach further. The promise of FOB is to improve cataract surgery outcomes by achieving an optimal balance: one that provides each patient with excellent visual quality and functional vision across distances, tailored to their lifestyle and expectations. Full article

To enable intelligent inspection of underground cable systems, this study presents a gecko-inspired quadruped robot that integrates multi-degree-of-freedom motion with a deep learning-based visual detection system. Inspired by the gecko’s flexible spine and leg structure, the robot exhibits strong adaptability to confined and uneven tunnel environments. The motion system is modeled using the standard Denavit–Hartenberg (D–H) method, with both forward and inverse kinematics derived analytically. A zero-impact foot trajectory is employed to achieve stable gait planning. For defect detection, the robot incorporates a binocular vision module and an enhanced YOLOv8 framework. The key improvements include a lightweight feature fusion structure (SlimNeck), a multidimensional coordinate attention (MCA) mechanism, and a refined MPDIoU loss function, which collectively improve the detection accuracy of subtle defects such as insulation aging, micro-cracks, and surface contamination. A variety of data augmentation techniques—such as brightness adjustment, Gaussian noise, and occlusion simulation—are applied to enhance robustness under complex lighting and environmental conditions. The experimental results validate the effectiveness of the proposed system in both kinematic control and vision-based defect recognition. This work demonstrates the potential of integrating bio-inspired mechanical design with intelligent visual perception to support practical, efficient cable inspection in confined underground environments. Full article

Our purpose is to evaluate the binocular contrast sensitivity function (CSF) in a presbyopic population and compare the results obtained with four different simultaneous-vision center-near multifocal contact lens (MCL) designs for distance vision under two illumination conditions. Additionally, chromatic CSF (red-green and blue-yellow) was evaluated. A randomized crossover pilot study was conducted. Four daily disposable lens designs, based on simultaneous-vision and center-near correction, were compared. The achromatic contrast sensitivity function (CSF) was measured binocularly using the CSV1000e test under two lighting conditions: room light on and off. Chromatic CSF was measured using the OptoPad-CSF test. Comparison of achromatic results with room lighting showed a statistically significant difference only for 3 cpd (p = 0.03) between the baseline visit (with spectacles) and all MCLs. Comparison of achromatic results without room lighting showed no statistically significant differences between the baseline and all MCLs for any spatial frequency (p > 0.05 in all cases). Comparison of CSF-T results showed a statistically significant difference only for 4 cpd (p = 0.002). Comparison of CSF-D results showed no statistically significant difference for all frequencies (p > 0.05 in all cases). The MCL designs analyzed provided satisfactory achromatic contrast sensitivity results for distance vision, similar to those obtained with spectacles, with no remarkable differences between designs. Chromatic contrast sensitivity for the red-green and blue-yellow mechanisms revealed some differences from the baseline that should be further investigated in future studies. Full article

Sensor fusion in intelligent suspension systems constitutes a fundamental technology for optimizing vehicle dynamic stability, ride comfort, and occupant safety. By integrating data from multiple sensor modalities, this study proposes a hierarchical multi-sensor fusion framework for active suspension control, aiming to enhance control precision. Initially, a binocular vision system is employed for target detection, enabling the identification of lane curvature initiation points and speed bumps, with real-time distance measurements. Subsequently, the integration of Global Positioning System (GPS) and inertial measurement unit (IMU) data facilitates the extraction of road elevation profiles ahead of the vehicle. A BP-PID control strategy is implemented to formulate mode-switching rules for the active suspension under three distinct road conditions: flat road, curved road, and obstacle road. Additionally, an ant colony optimization algorithm is utilized to fine-tune four suspension parameters. Utilizing the hardware-in-the-loop (HIL) simulation platform, the observed reductions in vertical, pitch, and roll accelerations were 5.37%, 9.63%, and 11.58%, respectively, thereby substantiating the efficacy and robustness of this approach. Full article

Despite significant advancements in indoor navigation technology over recent decades, it still faces challenges due to excessive dependency on external infrastructure and unreliable positioning in complex environments. This paper proposes an autonomous localization system that integrates advanced adaptive pedestrian dead reckoning (APDR) and binocular vision, designed to provide a low-cost, high-reliability, and high-precision solution for rescuers. By analyzing the characteristics of measurement data from various body parts, the chest is identified as the optimal placement for sensors. A chest-mounted advanced APDR method based on dynamic step segmentation detection and adaptive step length estimation has been developed. Furthermore, step length features are innovatively integrated into the visual tracking algorithm to constrain errors. Visual data is fused with dead reckoning data through an extended Kalman filter (EKF), which notably enhances the reliability and accuracy of the positioning system. A wearable autonomous localization vest system was designed and tested in indoor corridors, underground parking lots, and tunnel environments. Results show that the system decreases the average positioning error by 45.14% and endpoint error by 38.6% when compared to visual–inertial odometry (VIO). This low-cost, wearable solution effectively meets the autonomous positioning needs of rescuers in disaster scenarios. Full article

The anode assembly, as a key component in the electrolytic aluminum process, is composed of steel claws and aluminum guide rods. The connection quality between the steel claws and guide rods directly affects the current conduction efficiency, energy consumption, and operational stability of equipment. Achieving high-quality joining between the aluminum alloy and steel has become a key process in the preparation of the anode assembly. To join the guide rods and steel claws, this work uses Cold Metal Transfer (CMT) technology to clad aluminum on the steel surface and employs machine vision to detect surface forming defects in the cladding layer. The influence of different currents on the interfacial microstructure and mechanical properties of aluminum alloy cladding on the steel surface was investigated. The results show that increasing the cladding current leads to an increase in the width of the fusion line and grain size and the formation of layered Fe₂Al₅ intermetallic compounds (IMCs) at the interface. As the current increases from 90 A to 110 A, the thickness of the Al-Fe IMC layer increases from 1.46 μm to 2.06 μm. When the current reaches 110 A, the thickness of the interfacial brittle phase is the largest, at 2 ± 0.5 μm. The interfacial region where aluminum and steel are fused has the highest hardness, and the tensile strength first increases and then decreases with the current. The highest tensile strength is 120.45 MPa at 100 A. All the fracture surfaces exhibit a brittle fracture. Full article

This paper addresses the issues of Beidou navigation signal interference and blockage in complex substation environments by proposing an intelligent collaborative navigation model based on Beidou high-precision navigation and binocular vision recognition. The model is designed with Beidou navigation providing global positioning references and binocular vision enabling local environmental perception through a collaborative fusion strategy. The Unscented Kalman Filter (UKF) is used to integrate data from multiple sensors to ensure high-precision positioning and dynamic obstacle avoidance capabilities for robots in complex environments. Simulation results show that the Beidou–Binocular Cooperative Navigation (BBCN) model achieves a global positioning error of less than 5 cm in non-interference scenarios, and an error of only 6.2 cm under high-intensity electromagnetic interference, significantly outperforming the single Beidou model’s error of 40.2 cm. The path planning efficiency is close to optimal (with an efficiency factor within 1.05), and the obstacle avoidance success rate reaches 95%, while the system delay remains within 80 ms, meeting the real-time requirements of industrial scenarios. The innovative fusion approach enables unprecedented reliability for autonomous robot inspection in high-voltage environments, offering significant practical value in reducing human risk exposure, lowering maintenance costs, and improving inspection efficiency in power industry applications. This technology enables continuous monitoring of critical power infrastructure that was previously difficult to automate due to navigation challenges in electromagnetically complex environments. Full article

Recent years have seen significant interest among agricultural researchers in using robotics and machine vision to enhance intelligent orchard harvesting efficiency. This study proposes an improved hybrid framework integrating YOLO VX deep learning, 3D object recognition, and SLAM-based navigation for harvesting ripe fruits in greenhouse environments, achieving servo control of robotic arms with flexible end-effectors. The method comprises three key components: First, a fruit sample database containing varying maturity levels and morphological features is established, interfaced with an optimized YOLO VX model for target fruit identification. Second, a 3D camera acquires the target fruit’s spatial position and orientation data in real time, and these data are stored in the collaborative robot’s microcontroller. Finally, employing binocular calibration and triangulation, the SLAM navigation module guides the robotic arm to the designated picking location via unobstructed target positioning. Comprehensive comparative experiments between the improved YOLO v12n model and earlier versions were conducted to validate its performance. The results demonstrate that the optimized model surpasses traditional recognition and harvesting methods, offering superior target fruit identification response (minimum 30.9ms) and significantly higher accuracy (91.14%). Full article

Background/Objectives: A direct link between sensory processing disorder (SPD) and strabismus has not been systematically investigated, though prior studies suggest sensory modulation may influence visual behaviors. Traditional approaches view strabismus through a binary lens—either normal or pathological motor deviation. This report presents a proof-of-concept case suggesting strabismus may represent a neurobehavioral manifestation of sensory processing imbalance, rooted within the broader framework of SPD. Methods: We report a pediatric case marked by episodic monocular eye closure triggered by environmental stimuli, without identifiable ophthalmologic or neurologic pathology. The child’s symptoms were most consistent with sensory over-responsivity (SOR), a subtype of SPD, manifesting as stimulus-bound monocular eye closure and secondary self-regulatory behaviors. Results: We propose the Fusion Dysregulation Hypothesis, suggesting that exotropia and esotropia represent opposing outcomes along a continuum of sensory connectivity: exotropia arising from neural underwiring (hyporesponsivity and fusion instability), and esotropia from overwiring (hyperresponsivity and excessive fusion drive). Our case, marked by sensory hyperresponsivity, showed frequent monocular eye closure that briefly disrupted but did not impair fusion. This suggests an “overwired” binocular system maintaining single vision despite sensory triggers. In early-onset esotropia, such overconnectivity may become maladaptive, leading to sustained convergence. Conversely, autism spectrum disorder, typically associated with hypoconnectivity, may predispose to exotropia through reduced fusion maintenance. Conclusions: These findings highlight the need for interdisciplinary evaluation. We advocate for structured sensory profiling in children presenting with strabismus and, conversely, for ophthalmologic assessment in those diagnosed with SPD. While our findings remain preliminary, they support a bidirectional screening approach and suggest that sensory modulation may play a previously under-recognized role in the spectrum of pediatric strabismus presentations. Full article

Aiming at the problems of visual occlusion, reduced positioning accuracy and pose loss in the dynamic scanning process of aviation large components, this paper proposes a binocular vision dynamic positioning method based on magnetic target. This method detects the spatial coordinates of the magnetic target in real time through the binocular camera, extracts the target center to construct a unified reference system of the measurement platform, and uses MATLAB simulation to analyze the influence of different target layouts on the scanning stability and positioning accuracy. On this basis, a dual-objective optimization model with the objectives of ‘minimizing the number of targets’ and ‘spatial distribution uniformity’ is established, and Monte Carlo simulation is used to evaluate the robustness under Gaussian noise and random frame loss interference. The experimental results on the C-Track optical tracking platform show that the optimized magnetic target layout reduces the rotation error of the dynamic scanning from 0.055° to 0.035°, the translation error from 0.31 mm to 0.162 mm, and the scanning efficiency is increased by 33%, which significantly improves the positioning accuracy and tracking stability of the system under complex working conditions. This method provides an effective solution for high-precision dynamic measurement of aviation large components. Full article