Angle Measurement Error Research Articles

Research on achromatic Risley prism in normal tracing angle measurement system

The normal tracing angle measurement system based on Risley prisms can eliminate the influence of aberrations other than the dispersion of Risley prisms on the angle measurement accuracy. Although the traditional dispersion optimization method based on the extreme point can make the beam directions of different wavelengths more consistent after passing through the Risley prisms, the light intensity distribution that deviates from the extreme point wavelength causes the spot centroid to deviate from the target position, thus introducing the angle measurement error. In this paper, we propose a highly symmetry-glued achromatic Risley prisms optimization method for the needs of a normal tracing angle measurement system. Our method not only realizes the beam direction as closely as possible after the deflection of the Risley prisms but also compensates for the centroid error caused by the beam deviating from the central wavelength. ZEMAX simulation shows that, in the normal tracing angle measurement system, within the angle measurement range of ±700 ″ and the light source wavelength range of 600 to 700 nm, the angle measurement error introduced by the dispersion of the optimized Risley prisms is not >0.01 ″ .

Preparation of an Integrated Polarization Navigation Sensor via a Nanoimprint Photolithography Process

Based on the navigation strategy of insects utilizing the polarized skylight, an integrated polarization sensor for autonomous navigation is presented. The polarization sensor is fabricated using the proposed nanoimprint photolithography (NIPL) process by integrating a nanograting polarizer and an image chip. The NIPL process uses a UV-transparent variant template with nanoscale patterns and a microscale metal light-blocking layer. During the NIPL process, part of the resist material is pressed to fill into the nanofeatures of the variant template and is cured under UV exposure. At the same time, the other parts of the resist material create micropatterns according to the light-blocking layer. Polymer-based variant templates can be used for conformal contacts on non-flat substrates with excellent pattern transfer fidelity. The NIPL process is suitable for cross-scale micro–nano fabrication in wide applications. The measurement error of the polarization angle of the integrated polarization sensor is ±0.2°; thus, it will have a good application prospect in the polarization navigation application.

A high-accuracy calibration method for fusion systems of millimeter-wave radar and camera

Multi-sensor information fusion is widely used in the field of unmanned aerial vehicles obstacle avoidance flight, particularly in millimeter-wave (MMW) radar and camera fusion systems. Calibration accuracy plays a crucial role in fusion systems. The low-angle measurement accuracy of the MMW radar usually causes large calibration errors. To reduce calibration errors, a high-accuracy calibration method based on a region of interest (ROI) and an artificial potential field was proposed in this paper. The ROI was selected based on the initial calibration information and the MMW radar’s angle measurement error range from the image. An artificial potential field was established using the pixels of the ROI. Two moving points were set at the left and right ends of the ROI initially. The potential forces of the two moving points are different because the pixels of the obstacle and the background are different in the image. The two moving points were iteratively moved towards each other according to the force until their distance was less than the iteration step. The new calibration point is located in the middle of the final position of the two moving points. In contrast to the existing calibration methods, the proposed method avoids the limitations of low angle measurement accuracy by using image pixels. The experimental results show that the calibration errors decrease by 83.95% and 75.79%, which is significantly improved compared to the traditional methods and indicates the efficiency of the proposed method.

Petroleum Pipeline Interface Recognition and Pose Detection Based on Binocular Stereo Vision

Liquified natural gas (LNG) manipulator arms have been widely used in natural gas transportation. However, the automatic docking technology of LNG manipulator arms has not yet been realized. The first step of automatic docking is to identify and locate the target and estimate its pose. This work proposes a petroleum pipeline interface recognition and pose judgment method based on binocular stereo vision technology for the automatic docking of LNG manipulator arms. The proposed method has three main steps, including target detection, 3D information acquisition, and plane fitting. First, the target petroleum pipeline interface is segmented by using a color mask. Then, color space and Hu moment are used to obtain the pixel coordinates of the contour and center of the target petroleum pipeline interface. The semi-global block matching (SGBM) algorithm is used for stereo matching to obtain the depth information of an image. Finally, a plane fitting and center point estimation method based on a random sample consensus (RANSAC) algorithm is proposed. This work performs a measurement accuracy verification experiment to verify the accuracy of the proposed method. The experimental results show that the distance measurement error is not more than 1% and the angle measurement error is less than one degree. The measurement accuracy of the method meets the requirements of subsequent automatic docking, which proves the feasibility of the proposed method and provides data support for the subsequent automatic docking of manipulator arms.

Comparing the accuracy of three-dimensional mini-optical portable navigation and accelerometer-based portable navigation system for acetabular cup placement during total hip arthroplasty.

This study compared the accuracy of three dimensional (3D) mini-optical navigation and accelerometer-based portable navigation systems for cup positioning during a total hip arthroplasty (THA) in the supine position. This retrospective cohort study assessed data for 77 hips using 3D mini-optical navigation (n = 37) and accelerometer-based portable navigation (n = 40). The patients underwent THA through the mini-anterolateral approach in the supine position using a portable navigation system. We assessed the preoperative target angles, recorded intraoperative cup angles, postoperative CT imaging angles, cup angle measurement errors, and other clinical parameters. The mean absolute differences in radiographic inclination were similar between 3D mini-optical navigation and accelerometer-based portable navigation systems during THA in the supine position (2.8° ± 1.7° vs 2.8° ± 1.9°, p = 0.637). The mean absolute differences in radiographic anteversion were also similar (2.6° ± 2.3° vs 2.5° ± 1.9°, p = 0.737). Cup malalignment (absolute difference of inclination or anteversion between postoperative CT and preoperative target angle of > 5°) was significantly associated with body mass index (BMI) in accelerometer-based portable navigation but not in 3D mini-optical navigation. This is the first study to compare the accuracy of cup positioning between 3D mini-optical and accelerometer-based navigations in THA in the supine position. Both portable navigation systems accurately identified the orientation of cup placement. The accuracy of 3D mini-optical navigation is not affected by high BMI and may be preferred over other options in such patients.

An All-Fiber Optical Sensor Combined with FBG and CFBG-FP for Attitude Estimation.

In order to meet the needs of attitude correction of the optical fiber sensor array, an all-fiber optical sensor combined with FBG and CFBG-FP is proposed to monitor its attitude angle. The FBG sensor for pitch and roll angles detection employs a geometric model solution to shift the center wavelength of the three fiber Bragg gratings connected to it through the mass sphere, allowing for pitch and roll angle detection. Based on the magnetostrictive effect, the CFBG-FP sensor for heading angle detection employs changes of the cavity length of the chirped grating Fabry-Pérot cavity connected to its surface. The method of interpolation data processing and derivation of the attitude angle matrix is used to realize heading angle detection. The experimental results indicate that the FBG sensor for the pitch and roll angles detection has an effective detection range of 180 degrees and an angle measurement error of less than 1.5 degrees. Meanwhile, in the region beyond 10 degrees in the geomagnetic north-south direction, the angle measurement error of the CFBG-FP sensor for the heading angle detection is less than 1.3 degrees. Moreover, the impact of temperature in the system is minimized, demonstrating the validity of this combined fiber optical approach in the attitude angle measurements.

Electromagnetic Angular Position Sensing Using High-Magnetic-Permeability Materials

In this paper, a new electromagnetic angular position sensing method using high-magnetic-permeability metal (e.g., mu-metal) is proposed for measurement of joint angles of rotational mechanisms. An electromagnet and magnetic sensors are both located on one mechanical part and the mu-metal element is located on the other mechanical part with relative rotation to the first part around the joint. The mu-metal with high magnetic permeability is easily magnetized by the electromagnet and it exerts an additional magnetic field on the magnetic sensors dependent on the rotation angle nonlinearly. This influence is utilized for angle estimation using an extended Kalman filter. Two configurations of the angle sensing system are designed and modeled using numerical simulation. Experimental results show that the angle measurement error for both configurations is under 1% over their respective sensing range. The mu-metal based angle sensing system is also validated to be immune to ferromagnetic disturbances due to the use of an alternating magnetic field. The proposed angle sensing method is non-contacting and non-intrusive, and its off-joint configuration can measure joint angle without needing to be installed in the joint.

APPLICATION OF SPECIAL EQUIPMENT AND INNOVATIVE METHOD FOR MEASURING THE ANGLE OF EXHIBITION AND SHAPE OF THE BLADE OF A BLADE COLD COLL

Forensic science, as an object of forensics, is a system of technical means, methods and techniques based on a set of scientific and technical provisions used to identify, collect, study evidence, which will contribute to the effectiveness of crime detection and investigation. The purpose of this work is to acquaint a wide range of experts with the achievements of the team of authors and to consider the possibilities of developing and implementing new domestic tools for photofixation and innovative way to determine the angle and shape of the blade, as one of the technical characteristics of bladed melee weapons. research. The successful conduct of forensic research largely depends on the state of development of their theoretical foundations and technical equipment, which is the basis for practical activities. That is why at present the study of current problems of methodology and technical organization of the examination of bladed melee weapons is becoming more important. The experience of application of various technical means and methods of measuring the sharpening angle of the blade is analyzed, the search for analogues is carried out, the shortcomings of the available equipment are established and the value of sharpening angle measurement error is estimated in different ways. A patent search of the database was conducted, which revealed the opportunities and shortcomings of existing technical solutions. It is established that from practical experience there are different forms of sharpening at the intersection of the blade of a cold weapon. The main dimensional characteristics and structure of the blade and its individual elements are analyzed. An innovative method with the use of modern innovative equipment for determining the angle of sharpening and angles of inclination of the blade using modern CAD software products on a personal computer is proposed. Describes the design of equipment for photography when lighting the object of study from below. As an example of application of the offered method of measurement the process of step-by-step actions of the expert at carrying out expert researches of the cold blade weapon and results of definition of an angle of sharpening and angles of inclination of a blade of a sample is resulted.

Multi-landmark environment analysis with reinforcement learning for pelvic abnormality detection and quantification.

Morphological abnormalities of the femoroacetabular (hip) joint are among the most common human musculoskeletal disorders and often develop asymptomatically at early easily treatable stages. In this paper, we propose an automated framework for landmark-based detection and quantification of hip abnormalities from magnetic resonance (MR) images. The framework relies on a novel idea of multi-landmark environment analysis with reinforcement learning. In particular, we merge the concepts of the graphical lasso and Morris sensitivity analysis with deep neural networks to quantitatively estimate the contribution of individual landmark and landmark subgroup locations to the other landmark locations. Convolutional neural networks for image segmentation are utilized to propose the initial landmark locations, and landmark detection is then formulated as a reinforcement learning (RL) problem, where each landmark-agent can adjust its position by observing the local MR image neighborhood and the locations of the most-contributive landmarks. The framework was validated on T1-, T2- and proton density-weighted MR images of 260 patients with the aim to measure the lateral center-edge angle (LCEA), femoral neck-shaft angle (NSA), and the anterior and posterior acetabular sector angles (AASA and PASA) of the hip, and derive the quantitative abnormality metrics from these angles. The framework was successfully tested using the UNet and feature pyramid network (FPN) segmentation architectures for landmark proposal generation, and the deep Q-network (DeepQN), deep deterministic policy gradient (DDPG), twin delayed deep deterministic policy gradient (TD3), and actor-critic policy gradient (A2C) RL networks for landmark position optimization. The resulting overall landmark detection error of 1.5 mm and angle measurement error of 1.4° indicates a superior performance in comparison to existing methods. Moreover, the automatically estimated abnormality labels were in 95% agreement with those generated by an expert radiologist.

A low-cost and real-time pose measurement method for straight pipe jacking machine based on dual-screen laser target in tunneling guidance

In this paper, a low-cost and real-time pose measurement method for straight pipe jacking machine in tunneling guidance is proposed, which utilizes an instruction laser and a dual-screen laser target. The precise localization of light-spot on target is realized by high-performance processing of the image and grid calibration of the target. The spatial matrix transformation method is used to calculate the parameters for the specified position of the pipe jacking machine. Subsequently, the horizontal/vertical deviation between the actual moving route of the straight pipe jacking machine and the design tunnel axis (DTA) can be calculated. The results of the experiment show that the precision and absolute error of the azimuth angle measurement are better than 0.03° (1∑) and 0.05°, respectively. The measurement error of horizontal/vertical deviation is less than 3 mm. Hence, this method is feasible and highly accurate, which can effectively solve the guidance problem of pipe jacking construction.

Enhancement of evaluating flatfoot on a weight-bearing lateral radiograph of the foot with U-Net based semantic segmentation on the long axis of tarsal and metatarsal bones in an active learning manner

Robust labeling for semantic segmentation in radiographs is labor-intensive. No study has evaluated flatfoot-related deformities using semantic segmentation with U-Net on weight-bearing lateral radiographs. Here, we evaluated the robustness, accuracy enhancement, and efficiency of automated measurements for flatfoot-related angles using semantic segmentation in an active learning manner.A total of 300 consecutive weight-bearing lateral radiographs of the foot were acquired. The first 100 radiographs were used as the test set, and the following 200 radiographs were used as the training and validation sets, respectively. An expert orthopedic surgeon manually labeled ground truths. U-Net was used for model training. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to evaluate the segmentation results. In addition, angle measurement errors with a minimum moment of inertia (MMI) and ellipsoidal fitting (EF) based on the segmentation results were compared between active learning and learning with a pooled dataset.The mean values of DSC, HD, MMI, and EF of the average of all bones were 0.967, 1.274 mm, 0.792°, and 1.147° in active learning, and 0.964, 1.292 mm, 0.828°, and 1.186° in learning with a pooled dataset, respectively. The mean DSC and HD were significantly better in active learning than in learning with a pooled dataset. Labeling of all bones required 0.82 min in active learning and 0.88 min in learning with a pooled dataset.The accuracy and angle errors generally converged in both learning. However, the accuracies based on DSC and HD were significantly better in active learning. Moreover, active learning took less time for labeling, suggesting that active learning could be an accurate and efficient learning strategy for developing flatfoot classifiers based on semantic segmentation.

A simple and precise calibration method for binocular vision

Binocular vision is an important part of machine vision measurement. Calibration accuracy is crucial for binocular vision. As for the determination of the structure parameters of the two cameras, the existing approaches usually obtain the initial values and optimize them according to the image-space errors, object-space errors or a combination of these. In the optimization process, constructing the objective function only through the image-space errors or object-space errors is not enough. Moreover, the image-space and object-space errors can form a variety of combinations to construct the objective function. Therefore, it is hard to choose the error criterion. An inadequate error criterion may lead to over-optimized or local minima (ambiguity solution). To solve this problem, this paper proposes a simple and precise calibration method for binocular vision based on the points distance constraints and image-space errors. The process of determining the structure parameters was divided into noniterative and iterative parts. We calculated the structure parameters of the two cameras according to the distance constraints of every two feature points noniteratively. The results obtained in this step were set as the initial value and refined through minimizing the reprojection errors using the Levenberg–Marquardt method. Because the results obtained in the noniterative step are accurate enough, only one iteration is needed. In this way, we finish the calibration avoiding the need to choose the error criterion. Furthermore, our method reduces the number of iterations to improve the calibration efficiency on the premise of guaranteeing the calibration accuracy. The experimental results show the superiority of this calibration method compared with other calibration methods. Using the calibration results of our method, in the measurement range of −45°∼ 45°, the rotation angle measurement error was less than ±0.032°. In the measurement range of 0 ∼ 39 mm, the displacement measurement error was less than ±0.047 mm. As for the length measurement of a 300 × 225 mm target, the length measurement error was less than ±0.039 mm.

Study on nonlinear error calibration of fiber optical gyroscope scale factor based on LSTM

The calibration accuracy of the inertial navigation system (INS) has a non-negligible effect on its actual navigation performance. As the core component of the INS, the scale factor error of the fiber optical gyroscope (FOG) is one of the main error sources of the INS, which has a vital impact on the navigation accuracy. Generally, the scale factor of FOG is considered to be a constant value, but with the increasing demand for the accuracy of FOG, the scale factor error can not be ignored, how to calibration the FOG scale factor at different input velocity rates and temperature has attracted people's attention. The traditional calibration methods usually select several fixed temperature points and input velocity points, then the scale factor error is compensated by linear fitting or piecewise fitting. In order to improve the calibration accuracy, our paper considers the coupling effect of input velocity rate and temperature and designs a calibration experiment at continuous input velocity rates and temperature, the calibration time is shortened by 30%, then we propose a nonlinear error compensation method based on the LSTM. The experimental result shows that the std error of the FOG scale factor is reduced from 280 ppm to 13 ppm and the angle measurement error is reduced by 70%, which verify the effectiveness of our method.

A new method for measuring 3D rotation angle of spherical joint

A new method for measuring 3D rotation angle of precision spherical joint based on eddy current sensors is proposed in this study. A pseudorandom code is used to generate a 2D plane absolute code and then mapped to the sphere. The 3D absolute code is formed on the ball head through precision cutting, and an eddy current sensor array is arranged in the ball socket to identify the code. The experimental tests were conducted on the parameter-optimized prototype, and the experimental results showed that the mean squared error of the 3D rotation angle measurement was approximately 25′ in the range. The proposed new measurement principle provides a new approach to the precision measurement of spherical rotary motion, which is expected to produce a breakthrough in the theory and technology of spherical-angle sensor measurement. The proposed new principle also provides a theoretical basis and technical experience for the integration and development of intelligent devices.

РАДІОЛОКАЦІЙНЕ ВИМІРЮВАННЯ КУТІВ МІСЦЯ ЦІЛЕЙ МЕТОДОМ ROOT-MUSIC З УРАХУВАННЯМ СФЕРИЧНОСТІ ФАЗОВИХ ФРОНТІВ РАДІОХВИЛЬ

Subject and Purpose. The paper is an effectiveness study of the root-MUSIC technique as applied to elevation angle measurements of low-altitude radar targets over the sea, specifically with account of the radio waves’ phase front sphericity. The purpose is to find out whether and how much can the measurement accuracy be improved through account of the phase front sphericity, as compared with the classical approach assuming a plane phase front. Methods and Methodology. The work proceeds from computer simulation, considering a variety of sea roughness levels, and covers a range of radio wave reflection conditions from a nearly specular return to strong diff use reflection from the sea surface. The simulation involves a wide range of target distances within the far-field region with respect to the receive array. Results. A new approach has been suggested for taking into account the phase-front sphericity of the radio waves arriving from the target. The level of errors of elevation angle measurements has been estimated and compared with such shown by the conventional root-MUSIC method which assumes a plane phase front for the waves reflected from the target. The comparison concerns a wide range of sea roughness levels and target separations. Conclusion. It has been established that the proposed version of the root-MUSIC technique which takes wave front sphericity into account can significantly reduce the errors in elevation angle measurements for low-altitude targets.

A Position and Attitude Measurement Method Based on Laser Displacement Sensor and Infrared Vision Camera

The position and attitude measurement of objects plays an important role in industrial manufacture and inspection. However, in the existing measurement methods, the challenges brought by the environmental uncertainty to the visual measurement algorithm and the coordinate conversion errors caused by the joint measurement of various precision equipment will lead to poor accuracy and stability. In this paper, a measurement method is proposed to measure the object’s position and attitude based on laser displacement sensor and infrared vision camera. Firstly, when measuring the position and attitude, the combination of infrared vision camera and measurement target is an effective method to solve the challenges brought by environmental changes and measurement target changes in visual measurement methods. In addition, the measurement results and data of the whole system need not be converted between multiple coordinate systems, which avoids the complexity of system calculation and coordinate conversion errors. Through position and attitude measuring experiments, the position measurement error is 2.6 mm and the attitude angle measurement error is 1.1°, which verifies the feasibility and stability of the method.

A Vehicle-Based Laser System for High-Resolution DEM Development – Performance Evaluation of System Components.

Surface microtopography is quantified by the deviations in the direction of the normal vector of the surface. Soil microtopography is a major factor influencing soil erosion by water and wind. Surface microtopography can be accurately described using the Digital Elevation Model (DEM). In this study, a vehicle-based laser system was developed to generate high-resolution DEM data. The system consisted of five major components: a laser line scanner, a gyroscope sensor, a real-time kinematic GPS, a frame-rail mechanism, and a data acquisition and control unit. A series of experiments were conducted in the laboratory to evaluate the performance of the components. The result of distance measurements indicated that the system gave the most consistent distance measurement on a white paper. Static gyroscope sensor accuracy tests showed that angle measurement errors observed in combined pitch/roll rotations were larger than in single rotations. Within ±30º of single rotations, the measurement errors for pitch and roll angles were within 0.8º and 0.4º, respectively. The tests of the angular displacement on the linear rail showed that it slightly tilted towards the laser line scanner when it moved along the rail.

Strategy to Decrease the Angle Measurement Error Introduced by the Use of Circular Grating in Dynamic Torque Calibration.

A circular grating angle encoder is a key component in the dynamic torque calibration system. To improve the accuracy of an angle measurement, in this paper, the source of the angle measurement error of the circular grating is analyzed; an eccentricity error model and an inclination error model are proposed, respectively; further, these two models are combined to establish a total error model. Through the simulation study with the models, the conditions, in which the eccentricity error or inclination error can be ignored, are discussed. The calibration and compensation methods of the angle measurement error are given, and a progressive error compensation function which integrates the first harmonic fitting and the second harmonic fitting is obtained. An experiment is performed to verify the proposed calibration and compensation methods. The peak-to-peak value of the compensated angle measurement error of the single reading head can be reduced by about 93.76%, which approximates to the error of the mean value of the double reading heads. The experimental results show that the error calibration and compensation method based on the proposed error model can effectively compensate the angle measurement error of the circular grating with a single reading head, and obtain a high-precision measurement angle.

Non-iterative pose estimation method based on the polarization information via a parallelogram

As for vision-based pose estimation, which is also known as the PnP problem, non-iterative algorithms are more efficient. Precise extraction of 2D projections of feature points is important. If the projections of the feature points are not accurately extracted, the pose estimation accuracy is reduced. Under the condition of natural light, a camera captures the images of feature points, and the existence of high-light regions in the image affects the extraction accuracy of 2D projections of feature points, which reduces the number of effective feature points and leads to poor pose estimation accuracy. In the redundant cases (n > 4), redundant feature points are introduced as additional information, increasing the number of effective feature points to reduce the impact of high-light regions and improve the pose estimation accuracy. For the non-redundant cases (n = 4), it was difficult to ensure pose estimation accuracy. To solve this problem, a non-iterative pose estimation method based on the optimum polarization angle via four corner points of a parallelogram was proposed in this study. First, a model for solving optimum polarization angle was established. Thereafter, on the premise of the optimum polarization angle, the images were captured. Finally, the projections of the four corner points of a parallelogram were extracted, and the object pose was solved non-iteratively according to the four corner points. The corner point extraction experimental results show that the slope difference between the two parallel sides of each parallelogram under the condition of optimum polarization angle is less than that under the condition of natural light, thereby proving the improvement of the imaging quality. Measurement accuracy verification experiments prove that our pose estimation algorithm and the optimum polarization angle is the best combination to improve the non-iterative pose estimation accuracy in non-redundant cases. In the measurement range of −60-+60°, the angle measurement error was less than ±0.0491°. In the measurement range of 0–20 mm, the displacement measurement error was less than ±0.0435 mm.

Dual-attention-based optical terminal guidance for the recovery of unmanned surface vehicles

With the outstanding performance of unmanned surface vehicles (USVs) in maritime missions with scientific and commercial applications, increasing numbers of ships have begun to carry USVs to perform tasks. For the autonomous recovery of a USV along a preset trajectory to the docking station under various sea conditions, we propose a new navigation strategy with dual-attention-based optical terminal guidance. Monocular vision systems with creatively designed identification light sources are mounted on the docking station and USV, respectively. Thus, the azimuth angle, heading angle and relative distance between the docking station and the USV can be accurately measured. This method achieves centimeter-level homing accuracy and a 0.1-degree angle measurement error. A tracking control algorithm based on a line-of-sight method is suggested , and the control quantity of the USV is directly generated. Sea trials were conducted under various weather conditions to validate the proposed algorithm. This method provides reliable USV guidance to the docking station with a stern ramp from the maximum capture distance of approximately 100 meters. The proposed dual-attention method provides convenient implementation and transplantation to various unmanned platforms.