Accurate Coordinates Research Articles

Error analysis and accuracy evaluation method for coordinate measurement in transformed coordinate system

Multiple coordinate system transformations are required for engineering measurements of multi-faceted components. Traditional engineering measurements neglect coordinate errors after transformations, leading to inaccurate accuracy evaluations for coordinates. In this study, the effects of angular deviation and coordinate value magnitude on coordinate errors during transformations are first analyzed. Additionally, the transformation deviation of the three-point method is examined. Subsequently, an accuracy evaluation method for coordinate measurements is proposed to determine the scale scaling factor and the formula for calculating the variance of measuring coordinate errors. Finally, a coordinate accuracy evaluation method and evaluation formula that consider coordinate system transformation errors are proposed by self-checking. The validity of the proposed accuracy evaluation formula is confirmed through experiments. The coordinate measurement accuracy of the low-cost binocular camera is higher than that of the total station, whether or not coordinate system transformations are considered. Stereo-vision measurement technology is more suitable for small-scale engineering measurements.

Utilizing Fisheye Cameras and Mass Spectrometry Imaging to Obtain Probing Coordinates for Histological Samples

Detecting chemical compositions in histological samples using mass spectrometry often requires time-consuming user interaction with a probe to ensure it is positioned as closely as possible to a sampling region. Fisheye cameras can obtain images of samples with a wide field-of-view; however, barrel distortion makes it difficult to analyze them as a flat plane. This research project aimed to develop an application that unwarps live images of histological samples captured with a fisheye camera and calculates the exact image-to-real-world probing coordinates with minor user interaction. Python’s PyQt5 and OpenCV libraries were utilized to create interactive software that removes fisheye distortion, finds image-to-real-world coordinates, and segments images. Connected hardware consisted of a Prusa 3D printer, liquid micro junction-surface sampling probe, fisheye camera, and LED light strips. The printer provided a bed for capturing sample images and control of the camera and probe within 1/100 of a millimetre. The software was outlined to process at least 2 photos of checkerboards for the fisheye undistortion, capture a photo of a sample to be unwarped, and require the user to map 4 points from the image to probe coordinates. Using this approach, real-world coordinates could be found for any image location. The application successfully unwarps live photos and converts image-to-real-world coordinates with sub-millimeter accuracy. Users can take new calibration photos, control lighting, save photos, and check undistortion entirely within the application to ensure all parameters are satisfactory. Coordinates of significant regions are displayed or may be manually selected, making it easier to sample specific areas. The success of unwarping relies on the camera’s focus and height, lighting, and object positioning. Future development plans to improve robustness and coordinate accuracy, and reduce the amount of calibration needed.

Biofeedback and Exercise Load Affect Accuracy of Tongue Strength Exercise Performance.

Rehabilitative exercises require precise movement coordination and target accuracy for optimal effectiveness. This paper explores the impact of tongue strength exercises (TSE) performance accuracy on exercise outcomes, adherence, and participant confidence and motivation. An 8-week randomized clinical trial included 84 typically aging participants divided into four groups defined by access to biofeedback (present/absent) and TSE intensity dosing (maximal/submaximal) during a home exercise program (HEP). Retention, training, and HEP accuracy were tracked at biweekly visits and during HEP for participants with access to a biofeedback device. Associations with tongue strength outcomes, participant factors, biofeedback, and intensity dosing were analyzed. Exercise accuracy measures did not contribute to tongue strength outcomes at the end of 8weeks. Increased training accuracy (less practice required to achieve competency) was associated with higher participant confidence and better adherence to the HEP. The presence of biofeedback was associated with reduced adherence but better retention accuracy, while maximal intensity was associated with improvements in all accuracy measures compared to submaximal intensity exercise. These findings in typically aging participants suggest the need for tailored approaches in swallowing-related exercise programs, given the effects of biofeedback and exercise intensity on motor learning and exercise retention. Accuracy performance and its effect on clinical outcomes warrants study in clinical populations with dysphagia and with various rehabilitative approaches.Trial Registration Clincialtrials.gov: NCT04809558.

Exploring Phase Transition and Structural Complexity in the Mixed Cation Uranium Oxide CaUNb2O8.

The structures and high-temperature phase transition of CaUNb2O8 were studied in situ using synchrotron X-ray and neutron powder diffraction. Rietveld refinements provided an accurate description of the crystal structures of both the monoclinic fergusonite-type I2/b structure observed at room temperature and the tetragonal scheelite-type I41/a structure found at high temperatures. Bond valence sum analysis showed Nb5+ to be octahedrally coordinated in the monoclinic fergusonite-type structure, akin to other ANbO4 materials. Rietveld analysis of the variable temperature data allowed for the determination of accurate unit cell parameters and atomic coordinates, as well as revealing a reversible phase transition around ∼750 °C. The Nb-O bond distances display anomalous behavior, with a discontinuity in the longer Nb-O(1') distance coinciding with the phase transition suggestive of a reconstructive phase transition. Mode analysis identified the Γ2+ mode as the primary mode that drives the phase transition; this is linearly coupled to the induced spontaneous strain within the monoclinic fergusonite-type structure. Analysis of the temperature dependence of the Nb(z) positional parameter, as well as of the ϵ1-ϵ2 and ϵ6 strain parameters, showed that the phase transition is not strictly second order, with the critical exponent β ≠ 1/2. This study demonstrates the complex structural features of mixed cation metal oxides at elevated temperatures.

Validation of Tenths Stereotactic Coordinates Method Using Probabilistic Tractography of the Ansa Lenticularis in Parkinson's Disease Patients

To evaluate the accuracy of stereotactic coordinates to target the ansa lenticularis (AL) using 2 surgical planning methods, the conventional millimeter method (MM) and the normalized Tenths method (TM), assessed through individualized probabilistic tractography. Stereotactic targeting of the AL was assessed in 2 groups: 16 patients with Parkinson's disease and 16 healthy controls from Group 1, and 39 Parkinson's disease patients from Group 2. Structural and diffusion magnetic resonance imaging probabilistic tractography identified the AL based on the Schaltenbrand-Wahren Atlas. The MM defined stereotactic coordinates in millimeters, while the TM refined the planning by dividing the intercommissural line (AC-PC) distance into 10 equal parts, normalizing the "X," "Y," and "Z" coordinates for each patient. We subsequently compared the percentage of structural connectivity (%conn) of the AL with predefined regions of interest (ROIs), including the frontopontine-corticothalamic tracts, globus pallidus internus-ventral oral anterior, and ventral oral posterior, and quantified the streamlines in 142 brain hemispheres using the MM and TM coordinates. Despite anatomical variations in intercommissural (AC-PC) line lengths between both groups (22.5 ± 2.09mm and 24.4 ± 2.56mm, respectively; P= 0.002), as well as differences in magnetic resonance imaging acquisition parameters, we found that the TM significantly enhanced streamline identification and %conn compared to the MM. These enhancements were noted across ROIs: frontopontine-corticothalamic and globus pallidus internus-ventral oral anterior in both hemispheres, and globus pallidus internus-ventral oral posterior in the left (P < 0.001) and right hemispheres (P= 0.03). TM surpasses MM in identifying the structural connectivity between the AL and predefined ROIs, underscoring the advantages of coordinate normalization. However, variations in AC-PC line lengths and Euclidean distances between methods could lead to inaccuracies in the coordinate settings, potentially affecting the precision of structural connectivity and the efficacy of therapeutic outcomes.

Development of a GIS Tool to Find Fiber Cable Fault Using Python Scripting for ArcGIS in Amman City

Optical fiber cables are characterized by a larger bandwidth than other transmission media, which increases the amount of data transmitted per unit of time. Managing a fiber optic network using Geographic Information Systems (GIS) has benefits for the operation and maintenance of the communication network. The study aims to develop a GIS tool to detect fiber optic cable faults using Python Scripting for ArcGIS in the city of Amman. To achieve this goal, the Esri data model for telecommunications was used. The study concluded that it is possible to locate faults using the Python programming language, and the program provides accurate coordinates based on the precision of the OTDR device.

Evaluation of the errors of measuring residual stresses by the hole drilling method

A sample configuration with a specified distribution of residual stresses in depth was developed to elaborate modes for studying residual stresses using mechanical and physical methods. The sample formation technique is based on non-uniform plastic deformation of an aluminum beam of rectangular cross section according to the pure bending scheme. The control of the deformed state during loading was performed on the end surface of the sample by the field of normal deformations obtained using a digital image correlation system. The depth of the plastically deformed layer was 1.3 mm. The theoretical distribution of residual stresses obtained as a result of unloading of a plastically deformed sample was determined from the results of a numerical calculation of a finite element model, with allowance for the physical and mechanical characteristics, elastic-plastic hardening, as well as the deformation curve in true coordinates obtained as a result of uniaxial tension on elementary samples. A study of residual stresses inhomogeneous in depth was carried out by drilling holes in accordance with ASTM E837 on two opposite sides of the sample: the region of tension under loading and the area of compression, respectively. The control of the deformation response resulted from drilling was recorded using three-axis strain gauge rosettes. The results of the actual measurement of the longitudinal component of residual stresses were compared with their theoretical distribution obtained by a numerical method. The root-mean-square error in measuring residual stresses, relative to their theoretical distribution, for an aluminum alloy sample reaches 18.7 MPa. It should be noted that largest measurement errors were recorded at small depths, since they are characterized by small values of deformations comparable to the value of shot noise.

Mapping and spectroscopy of telecom quantum emitters with confocal laser scanning microscopy

Efficiently coupling single-photon emitters in the telecommunication C-band that are not deterministically positioned to photonic structures requires both spatial and spectral mapping. This study introduces the photoluminescence mapping of telecom C-band self-assembled quantum dots (QDs) by confocal laser scanning microscopy, a technique previously unexplored in this wavelength range which fulfills these two requirements. We consider the effects of distortions inherent to any imaging system but largely disregarded in prior works to derive accurate coordinates from photoluminescence maps. We obtain a position uncertainty below 11 nm for 10% of the QDs when assuming no distortions, highlighting the potential of the scanning approach. After distortion correction, we found that the previously determined positions are on average shifted by 428 nm from the corrected positions, demonstrating the necessity of this correction for accurate positioning. Then, through error propagation, the position uncertainty for 10% of the QDs increases to 110 nm.

LORE++: Logical location regression network for table structure recognition with pre-training

Table structure recognition (TSR) aims at extracting tables in images into machine-understandable formats. Current approaches address this issue by either predicting the adjacency of detected cells or direct generation of structural sequences. Nonetheless, these approaches either count on additional heuristic rules for post-processing, or involve the generation of extremely long-range sequences that lead to computational intricacy. In this paper, We redefine TSR as a LOgical location REgression paradigm, which effectively captures inherent logical dependencies and constraints among table cells. Correspondingly, we propose LORE, a novel approach for TSR. LORE simultaneously predicts accurate geometric coordinates of table cells and the logical structures of the entire table. Our proposed LORE is conceptually simpler, easier to train, and more accurate than other TSR paradigms. Moreover, to enhance the model’s spatial and logical representation capabilities, we propose two pre-training tasks, resulting in an upgraded version named LORE++. The incorporation of pre-training is proven to enjoy significant advantages, leading to a substantial enhancement in terms of accuracy, generalization, and few-shot capability compared to its predecessor. Experiments on standard benchmarks demonstrate the superiority of LORE++, which highlights the potential and promising prospect of the logical location regression paradigm for TSR.

Research on the optimization methods of common points layout for survey and alignment of particle accelerators

As a fourth-generation synchrotron light source based on a diffraction-limited storage ring, Hefei Advanced Light Facility (HALF) puts forward higher requirements for the alignment accuracy of the main components. Aggregated common points result in a loss of accuracy during the coordinate transformation required by accelerator alignment. To address this challenge, we proposed two methods: “aggregated points centralization (APC)" and “uniformity-weighted algorithm (UWA)" according to different usage scenarios. APC combines uniformity with the K-means algorithm to enhance the accuracy of coordinate transformation while reducing the number of common points. UWA calculates the uniformity in different directions and assigns weights to common points, reducing the accuracy loss. Simulations demonstrate that these two methods have strong superiority and stability with significantly improved accuracy. Applications of these 2 methods in the magnet unit pre-alignment experiment and tunnel network measurement show promising results. APC in pre-alignment can reduce the cost of building common points by 26% while maintaining the coordinate conversion accuracy. In tunnel network measurement, accuracy can be increased by 28% using UWA. The methods proposed offer broad applicability in the field of particle accelerator alignment and guiding alignment solutions for HALF.

Where Is That Crater? Best Practices for Obtaining Accurate Coordinates from LROC NAC Data

The Lunar Reconnaissance Orbiter Camera (LROC) Narrow Angle Camera (NAC) images and their derived products make up one of the highest-resolution and most spatially accurate data sets available for the Moon, making them a crucial resource for planners of landed lunar missions. However, it is essential to understand the best uses for each data type and the limits on the accuracy and resolution of the data sets available. With this understanding, users can better interpret and communicate their results. In this paper, we describe what assumptions may be made about the accuracy of LROC NAC images and the various derived products created by the LROC team. NAC digital terrain models and their corresponding orthophotos have the best accuracy of all NAC products, usually better than 10 m horizontally, and should be used where available. Other controlled NAC products usually have accuracies better than 30 m. For areas without controlled products, we describe how to process NAC images to obtain coordinates with the highest possible accuracy. We also recommend best practices for data users interacting with LROC data through online map servers, such as QuickMap or Lunaserv, and for processing LROC data locally using the US Geological Survey Integrated Software for Imagers and Spectrometers.

A new novel recognition and positioning system of black light-absorbing volute for automation depalletizing development

Abstract In the application of vision measurement, the black light-absorbing object is difficult to reflect the structured light from infrared emitter of the RGB-D camera. Therefore, an image recognition algorithm based on reference environment information is proposed to acquire the spatial positioning information of black volutes in the depalletizing system. The hardware system of the depalletizing system is mainly constructed of an upper computer, a six-axis industrial robot, an RGB-D camera and an end adsorption device. Firstly, the horizontal position information of each volute placed on the cardboard is obtained by the depth differences between the cardboard and the volute. Then, the depth information of the volute is obtained by the upper cardboard depth through collecting the position of the end vacuum suction cup triggered by feedback signal from vacuum generator. Secondly, a regional planar hand-eye calibration method is developed to improve the calibration accuracy in two-dimensional coordinates. The regional calibration method divides the robot working area into four regions: upper left, lower left, upper right, and lower right. The transformation matrix of each region is calculated separately. Finally, the depalletizing experiment is conducted on the three types of volutes. It is concluded that the average positioning error of the grasping center point of each volute obtained by our method is 3.795 mm, and its standard deviation is 1.769 mm. The average value of regional planar hand-eye calibration error is 4.044 mm, and its standard deviation is 1.501 mm. Under a stack of materials with dimensions of 1350 mm × 1350 mm × 1500 mm, the maximum error is controlled within 15 mm. Additionally, when combined with the end feedback compensation mechanism, the success rate for grasping all three volutes reaches 100%.

Facial Action Unit detection based on multi-task learning strategy for unlabeled facial images in the wild

Facial Action Unit (AU) detection often relies on highly-cost accurate labeling or inaccurate pseudo labeling techniques in recent years. How to introduce large amounts of unlabeled facial images in the wild into supervised AU detection frameworks has become a challenging problem. Additionally, nearly every type of AUs has the problem of unbalanced positive and negative samples. Inspired by other multi-task learning frameworks, we first propose a multi-task learning strategy boosting AU detection in the wild through jointing facial landmark detection and AU domain separation and reconstruction. Our introduced dual domains facial landmark detection framework can solve the lack of accurate facial landmark coordinates during the AU domain separation and reconstruction training process, while the parameters of homostructural facial extraction modules from these two similar facial tasks are shared. Moreover, we propose a pixel-level feature alignment scheme to maintain the consistency of features obtained from two separation and reconstruction processes. Furthermore, a weighted asymmetric loss is proposed to change the contribution of positive and negative samples of each type of AUs to model parameters updating. Experimental results on three widely used benchmarks demonstrate our superiority to most state-of-the-art methods for AU detection.

HISTOSTRUCTURAL ALTERATIONS IN THE CEREBRAL ARCHITECTURE ASSOCIATED WITH THE PROGRESSION OF ALCOHOL INTOXICATION: AN EXPERIMENTAL ANALYSIS

The aim of this study is to evaluate the histological changes in the cerebellum of rat brains following chronic alcohol intoxication. Materials and Methods. We employed a classical approach for modeling chronic alcohol intoxication by administering 40% ethanol to rats (n=55) in a dosage of 2 ml per 100 g of body weight daily for three months. The cerebellar structure was then analyzed. Results. This study investigates the impact of chronic alcohol intoxication on the histological structures of the cerebellar cortex. The cerebellum, like the nervous system overall, possesses a significant cellular and functional reserve. However, teratogenic factors, including ethanol, notably influence the activity of cerebellar neurons, increasing it. Ethanol exposure during early pregnancy can lead to prenatal growth retardation, stillbirth, cleft palate, hydrocephaly, and reductions in fetal body size. There is evidence suggesting a correlation between blood ethanol levels and a reduction in the number of Purkinje cells. Chronic alcohol consumption results in cerebellar ataxia, alterations in upper limb movements, decreased reaction speeds, reduced attention concentration, impaired coordination accuracy, and disturbances in postural stability and balance. Conclusion. The cerebellum, especially during development, is particularly vulnerable to the toxic effects of alcohol. Recent research suggests that changes in the neurotransmission of gamma-aminobutyric acid (GABA)-dependent receptors may contribute to cerebellar dysfunction induced by ethanol. Ethanol exposure increases the release of GABA not only in Purkinje cells but also in the interneurons of the molecular layer and granule cells.

Correlation Of Leg Muscle Strength, Agility And Eye-Foot Coordination On Dribbling Speed In Futsal Games In Fc Host Futsal Players In 2021

This study aims to determine the correlation of leg muscle strength, agility and eye-foot coordination to the dribbling speed of futsal athletes. The number of samples of 10 people was obtained by total sampling technique. The results of the first statistical analysis showed a Significance Test (0.022 &lt; 0.05) which means that leg muscle strength has a strong relationship to dribbling speed (X1 to Y). The results of the second statistical analysis showed a Significance Test (0.024 &lt; 0.05) which means that agility has a strong relationship with dribbling speed (X2 against Y). The results of the third statistical analysis showed a Significance Test (0.017 &lt; 0.05) which means that eye-foot coordination has a strong relationship to dribbling speed (X3 to Y). The results of the fourth statistical analysis show the Significance Test (0.029 &lt; 0.05) which means that leg muscle strength, agility and eye-foot coordination have a significant correlation to dribbling speed (X1, X2, X3 to Y) so it can be concluded that Simultaneously there is a strong correlation between leg muscle strength, agility and eye-foot coordination on the dribbling speed of Inang FC futsal athletes in 2021. This means that the better the leg muscle strength and the better agility and accuracy of eye-foot coordination, the better the dribbling speed in futsal games.

Determining of correlation relationship between angular elements of external orientation

The current state of development of science and technology definitely influenced the introduction of UAVs in various areas of economic development and military affairs. And this trend, since it brought positive results, will continue to grow. Therefore, the study of UAV capabilities, both design and operational, is a necessary component. The authors proposed a new algorithm for processing the results of digital shooting and determining the dependencies of the influence of the angular elements of the external orientation (EEO) of the images, which will make it possible to significantly improve the accuracy of the searched terrain coordinates. One of the main requirements for aircraft-type UAVs used in aerial surveying is absolutely horizontal flight. That is, maintaining the minimum angles of inclination of the external orientation of the images. And so, the idea arose to find the correlation coefficients between them when modeling the angles of inclination α and ω relative to the fixed angle ϰ (since this angle is actually compensated with the help of an aero device). So, if there is such a dependence, then based on the values of these values, it is possible to introduce a correction in the design of a micro-UAV and thereby increase stability during horizontal flight. Everything will depend on the value of the correlation coefficient: the larger it is, the more significant the possibility of improvement in the design of the UAV. Such modifications can be the displacement of the center of gravity of the structure, the profile and quantitative parameters of the plane, the shape of the fuselage, etc. The application of this direction will lead to the determination of the exact parameters of the EEO, since the installation of an accurate stabilization system and the determination of the angular EEO images (INS) on these devices is not possible, since there are often restrictions on the loading of UAVs. Regarding the determination of linear EEO, the issue can be solved by installing a dual-frequency GPS receiver on the UAV, which will allow obtaining the coordinates of the projection centers with an accuracy of 1–2 cm. The refinement of the EEO of digital images leads to an increase in the accuracy of the spatial coordinates of object points.

A Study on Three-Dimensional Modelling of the Baitul Ilmi Mosque's Itera Using Terrestrial Laser Scanner Technology

As advancements in three-dimensional (3D) modeling continue to progress, the demand for precise and efficient measurement techniques has led to significant innovations in the methods and tools used for creating 3D models. Among these, the utilization of Terrestrial Laser Scanners (TLS) has become increasingly popular. This study focuses on the integration of TLS and total station technologies for 3D modeling of a mosque. The total station was employed to conduct five sets of perfectly bonded closed polygon measurements, each consisting of five polygon points, from which three marker points were derived. Concurrently, the TLS was used to perform a comprehensive scan of the mosque from 17 different positions. The data obtained from the TLS scan provided a detailed 3D model, while the total station measurements served as control points to ensure the model's global coordinate accuracy. The processing of the closed polygon data was executed using the Bowditch method, and the TLS data was registered using the cloud-to-cloud method. This approach yielded an overall quality assessment, including a bundle error of 0.008 m, an overlap of 27%, a strength of 65%, and a cloud-to-cloud discrepancy of 0.008 m. The integration of point clouds with total station coordinates resulted in an error margin of 0.160 m. Geometric validation of the model was conducted by comparing its dimensions to measurements obtained using a measuring tape, which yielded a Root Mean Square Error (RMSE) of 0.045 m.

Application of a novel deep learning-based 3D videography workflow to bat flight.

Studying the detailed biomechanics of flying animals requires accurate three-dimensional coordinates for key anatomical landmarks. Traditionally, this relies on manually digitizing animal videos, a labor-intensive task that scales poorly with increasing framerates and numbers of cameras. Here, we present a workflow that combines deep learning-powered automatic digitization with filtering and correction of mislabeled points using quality metrics from deep learning and 3D reconstruction. We tested our workflow using a particularly challenging scenario: bat flight. First, we documented four bats flying steadily in a 2 m3 wind tunnel test section. Wing kinematic parameters resulting from manually digitizing bats with markers applied to anatomical landmarks were not significantly different from those resulting from applying our workflow to the same bats without markers for five out of six parameters. Second, we compared coordinates from manual digitization against those yielded via our workflow for bats flying freely in a 344 m3 enclosure. Average distance between coordinates from our workflow and those from manual digitization was less than a millimeter larger than the average human-to-human coordinate distance. The improved efficiency of our workflow has the potential to increase the scalability of studies on animal flight biomechanics.

OccTest: An integrated approach for quality control of species occurrence data

AbstractAimSpecies occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

Practical Limitations of Using the Tilt Compensation Function of the GNSS/IMU Receiver

The research in this paper is related to the accuracy of the tilt compensation function of the GNSS/IMU receivers, which were examined in an open sky environment. The purpose of the paper is to point out to geodesists the conditions and limitations of using GNSS/IMU technology in precise measurements to not jeopardize the coordinate’s accuracy. The environment in which the measurement is made affects the quality of the GNSS signal and can limit the visibility of the satellite, leading to larger errors in the measurement. In this experiment, the current performance of the GNSS/IMU receivers was checked. Seven GNSS/IMU receivers were used for the realization of the experiment. For six receivers the compensation angle was α = 30°, while for one receiver, the compensation angle was α = 45°. The standard uncertainty of GNSS coordinates of the antenna phase center has values less than 9 mm. The standard uncertainty of the IMU component has values less than 31 mm. The measurement uncertainty of the position of the used GNSS receivers is in the range of 18.1 mm to 31.7 mm. The limit values for the differences along the coordinate axes x and y were determined, and their values are from 26 mm to 44 mm. In the conducted experiment, it was confirmed that three GNSS/IMU receivers have a “Satisfactory” result. The results show that GNSS/IMU measurements with a slope greater than 30° significantly affect the accuracy and reliability of GNSS/IMU technology. A slope greater than 45° has a deviation along the coordinate axes of 121.3 mm. The conducted research is particularly important for geodetic works that require high positioning performance. The testing method of the GNSS/IMU receiver presented in this paper can help its users to make correct conclusions regarding the coordinate accuracy of the measured point of interest.