Search Results (1,977)

With the advancement of technology, unmanned ground vehicles (UGVs) have shown increasing application value in various tasks, such as food delivery and cleaning. A key capability of UGVs is obstacle detection, which is essential for avoiding collisions during movement. Current mainstream methods use point cloud information from onboard sensors, such as light detection and ranging (LiDAR) and depth cameras, for obstacle perception. However, the substantial volume of point clouds generated by these sensors, coupled with the presence of noise, poses significant challenges for efficient obstacle detection. Therefore, this paper presents a fast obstacle detection algorithm designed to ensure the safe operation of UGVs. Building on multi-sensor point cloud fusion, an efficient ground segmentation algorithm based on multi-plane fitting and plane combination is proposed in order to prevent them from being considered as obstacles. Additionally, instead of point cloud clustering, a vertical projection method is used to count the distribution of the potential obstacle points through converting the point cloud to a 2D polar coordinate system. Points in the fan-shaped area with a density lower than a certain threshold will be considered as noise. To verify the effectiveness of the proposed algorithm, a cleaning UGV equipped with one LiDAR sensor and four depth cameras is used to test the performance of obstacle detection in various environments. Several experiments have demonstrated the effectiveness and real-time capability of the proposed algorithm. The experimental results show that the proposed algorithm achieves an over 90% detection rate within a 20 m sensing area and has an average processing time of just 14.1 ms per frame. Full article

The evaluation of smartphone camera technology for close-range photogrammetry includes assessing captured photos for 3D measurement. In this work, experiments are conducted on many smartphones to study distortion levels and accuracy performance in close-range photogrammetry applications. Analytical methods and specialized digital tools are employed to evaluate the results. OpenCV functions estimate the distortions introduced by the lens. Diagrams, evaluation images, statistical quantities, and indicators are utilized to compare the results among sensors. The accuracy achieved in photogrammetry is examined using the photogrammetric bundle adjustment in a real-world application. In the end, generalized conclusions are drawn regarding this technology’s use in close-range photogrammetry applications. Full article

Additive manufacturing of advanced materials has become widespread, encompassing a range of materials including thermoplastics, metals, and ceramics. For the ceramics, the complete production process typically involves indirect additive manufacturing, where the green ceramic part undergoes debinding and sintering to achieve its final mechanical and thermal properties. To avoid unnecessary energy-intensive steps, it is crucial to assess the internal integrity of the ceramic in its green stage. This study aims to investigate the use of active thermography for defect detection. The approach is to examine detectability using two benchmarks: the first focuses on the detectability threshold, and the second on typical defects encountered in 3D printing. For the first benchmark, reflection and transmission modes are tested with and without a camera angle to minimize reflection. The second benchmark will then be assessed using the most effective configurations identified. All defects larger than 1.2 mm were detectable across the benchmarks. The method can successfully detect defects, with transmission mode being more suitable since it does not require a camera angle adjustment to avoid reflections. However, the method struggles to detect typical 3D-printing defects because the minimum defect size is 0.6 mm, which is the size of the nozzle. Full article

Underwater vision data facilitate a variety of underwater operations, including underwater ecosystem monitoring, topographical mapping, mariculture, and marine resource exploration. Conventional laser-based underwater imaging systems with complex system architecture rely on high-cost laser systems with high power, and software-based methods can not enrich the physical information captured by cameras. In this manuscript, a low-cost modulated laser-based imaging system is proposed with a spot in the shape of a square ring to eliminate the overlap between the illumination light path and the imaging path, which could reduce the negative effect of backscatter on the imaging process and enhance imaging quality. The imaging system is able to achieve underwater imaging at long distance (e.g., 10 m) with turbidity in the range of 2.49 to 7.82 NTUs, and the adjustable divergence angle of the laser tubes enables the flexibility of the proposed system to image on the basis of application requirements, such as the overall view or partial detail information of targets. Compared with a conventional underwater imaging camera (DS-2XC6244F, Hikvision, Hangzhou, China), the developed system could provide better imaging performance regarding visual effects and quantitative evaluation (e.g., UCIQUE and IE). Through integration with the CycleGAN-based method, the imaging results can be further improved, with the UCIQUE increased by 0.4. The proposed low-cost imaging system with a compact system structure and low consumption of energy could be equipped with platforms, such as underwater robots and AUVs, to facilitate real-world underwater applications. Full article

Visual servo grasping technology has garnered significant attention in intelligent manufacturing for its potential to enhance both the flexibility and precision of robotic operations. However, traditional approaches frequently encounter challenges such as task failure when visual features move outside the camera’s field of view (FoV) and system instability due to interaction matrix singularities, limiting the technology’s effectiveness in complex environments. This study introduces a novel control strategy that leverages an asymmetric time-varying performance function to address the issue of visual feature escape. By strictly limiting the range of feature error, our approach ensures that visual features consistently remain within the camera’s FoV, thereby enhancing both transient and steady-state system performance. Furthermore, we have developed an adaptive damped least squares controller that dynamically adjusts the damping term to mitigate numerical instability resulting from interaction matrix singularities. The effectiveness of our method has been validated through grasping experiments involving significant rotations around the camera’s optical axis and other complex movements. Full article

Perception systems for assisted driving and autonomy enable the identification and classification of objects through a concentration of sensors installed in vehicles, including Radio Detection and Ranging (RADAR), camera, Light Detection and Ranging (LIDAR), ultrasound, and HD maps. These sensors ensure a reliable and robust navigation system. Radar, in particular, operates with electromagnetic waves and remains effective under a variety of weather conditions. It uses point cloud technology to map the objects in front of you, making it easy to group these points to associate them with real-world objects. Numerous clustering algorithms have been developed and can be integrated into radar systems to identify, investigate, and track objects. In this study, we evaluate several clustering algorithms to determine their suitability for application in automotive radar systems. Our analysis covered a variety of current methods, the mathematical process of these methods, and presented a comparison table between these algorithms, including Hierarchical Clustering, Affinity Propagation Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH), Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Mini-Batch K-Means, K-Means Mean Shift, OPTICS, Spectral Clustering, and Gaussian Mixture. We have found that K-Means, Mean Shift, and DBSCAN are particularly suitable for these applications, based on performance indicators that assess suitability and efficiency. However, DBSCAN shows better performance compared to others. Furthermore, our findings highlight that the choice of radar significantly impacts the effectiveness of these object recognition methods. Full article

The advancement of unloading technology in combine harvesting is crucial for the intelligent development of agricultural machinery. Accurately measuring material pile height in transport vehicles is essential, as uneven accumulation can lead to spillage and voids, reducing loading efficiency. Relying solely on manual observation for measuring stack height can decrease harvesting efficiency and pose safety risks due to driver distraction. This research applies binocular vision to agricultural harvesting, proposing a novel method that uses a stereo matching algorithm to measure material pile height during harvesting. By comparing distance measurements taken in both empty and loaded states, the method determines stack height. A linear regression model processes the stack height data, enhancing measurement accuracy. A binocular vision system was established, applying Zhang’s calibration method on the MATLAB (R2019a) platform to correct camera parameters, achieving a calibration error of 0.15 pixels. The study implemented block matching (BM) and semi-global block matching (SGBM) algorithms using the OpenCV (4.8.1) library on the PyCharm (2020.3.5) platform for stereo matching, generating disparity, and pseudo-color maps. Three-dimensional coordinates of key points on the piled material were calculated to measure distances from the vehicle container bottom and material surface to the binocular camera, allowing for the calculation of material pile height. Furthermore, a linear regression model was applied to correct the data, enhancing the accuracy of the measured pile height. The results indicate that by employing binocular stereo vision and stereo matching algorithms, followed by linear regression, this method can accurately calculate material pile height. The average relative error for the BM algorithm was 3.70%, and for the SGBM algorithm, it was 3.35%, both within the acceptable precision range. While the SGBM algorithm was, on average, 46 ms slower than the BM algorithm, both maintained errors under 7% and computation times under 100 ms, meeting the real-time measurement requirements for combine harvesting. In practical operations, this method can effectively measure material pile height in transport vehicles. The choice of matching algorithm should consider container size, material properties, and the balance between measurement time, accuracy, and disparity map completeness. This approach aids in manual adjustment of machinery posture and provides data support for future autonomous master-slave collaborative operations in combine harvesting. Full article

The slug frequency (SF), which refers to the number of liquid slugs passing through a pipe during a specific time, is an important parameter for characterizing the multiphase intermittent flows and monitoring some process involving this kind of flow. The simplicity of the definition of SF contrasts with the difficulty of correctly measuring it. This manuscript aims to review and discuss the various techniques and methods developed to determine the slug frequency experimentally. This review significantly reveals the absence of a universal measurement method applicable to a wide range of operating conditions. Thus, the recourse to recording videos with high-speed cameras, which can be used only at a laboratory scale, remains often necessary. From the summarized state-of-the-art, it appears that correctly defining the threshold values for detecting the liquid slugs/elongated bubbles interface from physical parameters time series, increasing the applicability of instrumentations at industrial scales, and properly estimating the uncertainties are the challenges that have to be faced to advance in the measurement of SF. Full article

To permit the collection of quantitative data on start, turn and clean swimming performances in any swimming pool, the aims of the present study were to (1) validate a mobile in-field performance analysis system (PAS) against the Kistler starting block equipped with force plates and synchronized to a 2D camera system (KiSwim, Kistler, Winterthur, Switzerland), (2) assess the PAS’s interrater reliability and (3) provide percentiles as reference values for elite junior and adult swimmers. Members of the Swiss junior and adult national swimming teams including medalists at Olympic Games, World and European Championships volunteered for the present study (n = 47; age: 17 ± 4 [range: 13–29] years; World Aquatics Points: 747 ± 100 [range: 527–994]). All start and turn trials were video-recorded and analyzed using two methods: PAS and KiSwim. The PAS involves one fixed view camera recording overwater start footage and a sport action camera that is moved underwater along the side of the pool perpendicular to the swimming lane on a 1.55 m long monostand. From a total of 25 parameters determined with the PAS, 16 are also measurable with the KiSwim, of which 7 parameters showed satisfactory validity (r = 0.95–1.00, p < 0.001, %-difference < 1%). Interrater reliability was determined for all 25 parameters of the PAS and reliability was accepted for 21 of those start, turn and swimming parameters (ICC = 0.78–1.00). The percentiles for all valid and reliable parameters provide reference values for assessment of start, turn and swimming performance for junior and adult national team swimmers. The in-field PAS provides a mobile method to assess start, turn and clean swimming performance with high validity and reliability. The analysis template and manual included in the present article aid the practical application of the PAS in research and development projects as well as academic works. Full article

Friction drilling is a non-conventional process that generates heat through the interaction between a rotating tool and a workpiece, forming a hole with a bushing. In this study, the effect of the preheating temperature, rotational speed, and feed rate on the induced temperature during the friction drilling of A356 aluminum alloy was investigated. This study aimed to analyze the influence of friction-drilling parameters on the thermal conditions in the induced bushing, where it focused on the relationship between preheating and the resulting heat generation. The analysis of variance (ANOVA) approach was carried out to optimize the friction-drilling parameters that contributed most to the induced temperature during the friction-drilling processing. Experiments were conducted at various preheating temperatures (100 °C, 150 °C, 200 °C), rotational speeds (2000 rpm, 3000 rpm, 4000 rpm), and feed rates (40 mm/min, 60 mm/min, 80 mm/min). The induced temperature during the process was recorded using an infrared camera, where the observed temperatures ranged from a minimum of 154.4 °C (at 2000 rpm, 60 mm/min, and 100 °C preheating) to a maximum of 366.8 °C (at 4000 rpm, 40 mm/min, and 200 °C preheating). The results show that preheating increased the peak temperature generated in the bushing during friction drilling, especially at lower rotational speeds. The rotational speed rise led to an increase in the induced temperature. However, the increase in the feed rate resulted in a decrease in the observed temperature. The findings provide insights into optimizing friction-drilling parameters for enhanced thermal management in A356 aluminum alloy. Full article

Background/Objectives: Comparing a given variable between the lower extremities (LEs) usually involves calculating the value of a selected asymmetry index. The aim of this study was to evaluate the mean-dependent asymmetry index for gait variables. Methods: The three-point crutch gait asymmetry between the non-surgical LE (NS) and surgical LE (S) was assessed in 14 patients after unilateral total hip arthroplasty. An eight-camera motion capture system integrated with two force platforms was used. The values of the new gait asymmetry index (MA) were calculated for such variables as stance phase time (ST), knee flexion and extension range of motion (KFE RoM), hip flexion and extension range of motion (HFE RoM), and vertical ground reaction force (VGRF). Results: An analysis related to gait asymmetry showed significantly higher values for all variables for the NS than for the S (the MA ranged from 9.9 to 42.0%; p < 0.001). In the case of comparisons between the MA and other indices, the intraclass correlation coefficient ranged from 0.566 to 0.998 (p < 0.001) with Bland–Altman bias values that ranged from −18.2 to 0.3 %GC (ST), from 0.0 to 0.5° (KFE RoM), from −12.4 to 1.4° (HFE RoM), and from −11.9 to −0.1 %BW (VGRF). Conclusions: The findings revealed a prominent three-point crutch gait asymmetry for all variables, especially a disturbingly large asymmetry for the HFE RoM and VGRF. The comparisons also showed generally excellent or good agreement with the other indices. Furthermore, the mean MA result from n single values was the same as the MA result calculated using the mean values of a given variable. The MA, as an accurate asymmetry index, can be used to objectively assess pathological gait asymmetry. Full article

The fluorescence intensity of fluorescent dyes typically employed in the dual-emission laser-induced fluorescence (DELIF) method gradually degrades as the excitation time increases, and the degradation rate depends on the type of fluorescent dye used. Therefore, the DELIF method is unsuitable for long-term temperature measurements. In this study, we focused on the fluorescence intensity ratio of a single fluorescent dye at two fluorescence wavelengths and developed a DELIF method for long-term temperature measurements based on this ratio. The fluorescence intensity characteristics of Fluorescein disodium and Rhodamine B, which are typically used in the DELIF method, in the temperature range of 10–60 °C were comprehensively investigated using two high-speed monochrome complementary metal-oxide semiconductor cameras and narrow bandpass filters. Interestingly, the ratio of the fluorescence intensity of each fluorescent dye at the peak emission wavelength of the fluorescence spectrum, λ, to the fluorescence intensity at wavelengths very close to the peak wavelength (λ ± 10 nm) was highly sensitive to temperature variations but not excitation time. Particularly, when Rhodamine B was used, the selection of the fluorescence intensity ratios at a wavelength combination of 589 and 600 nm enabled highly accurate temperature measurements with a temperature resolution of ≤0.042 °C. Moreover, the fluorescence intensity ratio varied negligibly throughout the excitation time of 180 min, with a measurement uncertainty (95% confidence interval) of 0.045 °C at 20 °C. The results demonstrate that the proposed DELIF method enables highly accurate long-term temperature measurements. Full article

Collecting pavement texture information is crucial to understand the characteristics of a road surface and to have essential data to support road maintenance. Traditional texture assessment techniques often require expensive equipment and complex operations. To ensure cost sustainability and reduce traffic closure times, this study proposes a rapid, cost-effective, and non-invasive surface texture assessment technique. This technology consists of capturing a set of images of a road surface with a mobile phone; then, the images are used to reconstruct the 3D surface with photogrammetric processing and derive the roughness parameters to assess the pavement texture. The results indicate that pavement images taken by a mobile phone can reconstruct the 3D surface and extract texture features with accuracy, meeting the requirements of a time-effective documentation. To validate the effectiveness of this technique, the surface structure of the pavement was analyzed in situ using a 3D structured light projection scanner and rigorous photogrammetry with a high-end reflex camera. The results demonstrated that increasing the point cloud density can enhance the detail level of the real surface 3D representation, but it leads to variations in road surface roughness parameters. Therefore, appropriate density should be chosen when performing three-dimensional reconstruction using mobile phone images. Mobile phone photogrammetry technology performs well in detecting shallow road surface textures but has certain limitations in capturing deeper textures. The texture parameters and the Abbott curve obtained using all three methods are comparable and fall within the same range of acceptability. This finding demonstrates the feasibility of using a mobile phone for pavement texture assessments with appropriate settings. Full article

A simple and miniaturized protocol was developed for chloride extraction from Brazilian pre-salt crude oil for further salt determination by colorimetry. In this protocol, the colorimetric analysis of chloride using digital images was carried out in an aqueous phase obtained after a simple and miniaturized extraction carefully developed for this purpose. A portable device composed of a homemade 3D-printed chamber with a USB camera was used. The PhotoMetrix app converted the images into RGB histograms, and a partial least squares (PLS) model was obtained from chemometric treatment. The sample preparation was performed by extraction after defining the best conditions for the main parameters (e.g., extraction time, temperature, type and volume of solvent, and sample mass). The PLS model was evaluated considering the coefficient of determination (R²) and the root mean square errors (RMSEs)—calibration (RMSEC), cross-validation (RMSECV), and prediction (RMSEP). Under the optimized conditions, an extraction efficiency higher than 84% was achieved, and the limit of quantification was 1.6 mg g⁻¹. The chloride content obtained in the pre-salt crude oils ranged from 3 to 15 mg g⁻¹, and no differences (ANOVA, 95%) were observed between the results and the reference values by direct solid sampling elemental analysis (DSS-EA) or the ASTM D 6470 standard method. The easy-to-use colorimetric analysis combined with the extraction method’s simplicity offered a high-throughput, low-cost, and environmentally friendly method, with the possibility of portability. Additionally, the decrease in energy consumption and waste generation, increasing the sample throughput and operators’ safety, makes the proposed method a greener approach. Furthermore, the cost savings make this a suitable option for routine quality control, which can be attractive in the crude oil industry. Full article

Astrogeodetic deflections of the vertical (DoVs) are close indicators of the slope of the geoid. Thus, DoVs observed along horizontal profiles may be integrated to create geoid undulation profiles. In this study, we collected DoV data in the Eastern Swiss Alps using a Swiss Digital Zenith Camera, the COmpact DIgital Astrometric Camera (CODIAC), and two total station-based QDaedalus systems. In the mountainous terrain of the Eastern Swiss Alps, the geoid profile was established at 15 benchmarks over a two-week period in June 2021. The elevation along the profile ranges from 1185 to 1800 m, with benchmark spacing ranging from 0.55 km to 2.10 km. The DoV, gravity, GNSS, and levelling measurements were conducted on these 15 benchmarks. The collected gravity data were primarily used for corrections of the DoV-based geoid profiles, accounting for variations in station height and the geoid-quasigeoid separation. The GNSS/levelling and DoV data were both used to compute geoid heights. These geoid heights are compared with the Swiss Geoid Model 2004 (CHGeo2004) and two global gravity field models (EGM2008 and XGM2019e). Our study demonstrates that absolute geoid heights derived from GNSS/leveling data achieve centimeter-level accuracy, underscoring the precision of this method. Comparisons with CHGeo2004 predictions reveal a strong correlation, closely aligning with both GNSS/leveling and DoV-derived results. Additionally, the differential geoid height analysis highlights localized variations in the geoid surface, further validating the robustness of CHGeo2004 in capturing fine-scale geoid heights. These findings confirm the reliability of both absolute and differential geoid height calculations for precise geoid modeling in complex mountainous terrains. Full article