Local Plane Research Articles

Vision-aided precise positioning for long-reach robotic manipulators using local calibration

A vision-based guidance methodology is proposed for precise positioning of the tool center point (TCP) of heavy-duty, long-reach (HDLR) manipulators. HDLR manipulators are non-rigid structures with many nonlinearities. Therefore, conventional rigid-body–based modeling and control methods issue challenges for accurate TCP positioning. To compensate for these errors, we compute the pose error between the TCP and an object of interest (OOI) directly in the camera frame, while using motion-based local calibration to find the extrinsic sensor-to-robot correspondence. The proposed pipeline for local calibration is twofold: first, the detected tool is oriented perpendicularly with respect to the OOI. Second, range adjustment is performed in the local planar plane by exploiting the visual measurements. Two methods for adjusting the range were examined: a line equation–based method and a trajectory matching–based method. Real-time experiments were conducted using a HDLR manipulator with a 5 m reach, and visual fiducial markers were used as detectable objects for the visual sensor. The experimental results demonstrated that the proposed methodology can provide sub-centimeter positioning accuracy, which is very challenging to achieve with HDLR manipulators due to their characteristic uncertainties.

CONTINUOUS 3D-LABEL SEMI-GLOBAL MATCHING FOR SATELLITE STEREO

Abstract. We present Continuous 3D-Label Semi-Global Matching (CoSGM), a new dense stereo matching algorithm for satellite stereo. CoSGM overparameterizes the disparity map as an array of local planes, so it can regularize the first-order smoothness of the estimated disparity. Furthermore, the algorithm can produce a dense normal map beside the disparity map. We show experimentally that CoSGM could achieve denser depth maps with comparable accuracy to traditional semi-global matching algorithms.

Simultaneous Horizontal and Vertical Oscillation of a Quiescent Filament Observed by CHASE and SDO

In this paper, we present the imaging and spectroscopic observations of the simultaneous horizontal and vertical large-amplitude oscillation of a quiescent filament triggered by an extreme-ultraviolet (EUV) wave on 2022 October 2. Particularly, the filament oscillation involved winking phenomenon in Hα images and horizontal motions in EUV images. Originally, a filament and its overlying loops across AR 13110 and 13113 erupted with a highly inclined direction, resulting in an X1.0 flare and a non-radial coronal mass ejection. The fast lateral expansion of loops excited an EUV wave and the corresponding Moreton wave propagating northward. Once the EUV wave front arrived at the quiescent filament, the filament began to oscillate coherently along the horizontal direction, and the “winking filament” appeared concurrently in Hα images. The horizontal oscillation involved an initial amplitude of ∼10.2 Mm and a velocity amplitude of ∼46.5 km s−1, lasting for ∼3 cycles with a period of ∼18.2 minutes and a damping time of ∼31.1 minutes. The maximum Doppler velocities of the oscillating filament are 18 km s−1 (redshift) and −24 km s−1 (blueshift), which were derived from the spectroscopic data provided by the Chinese Hα Solar Explorer/Hα Imaging Spectrograph. The three-dimensional velocity of the oscillation is determined to be ∼50 km s−1 at an angle of ∼50° to the local photosphere plane. Based on the wave–filament interaction, the minimum energy of the EUV wave is estimated to be 2.7 × 1020 J. Furthermore, this event provides evidence that Moreton waves should be excited by the highly inclined eruptions.

Optical transmission modulation by fiber guide bending

The study is aimed at finding out the influence of bending on the waveguide from the point of view of ray equivalence with its modification based on the concept of local plane waves to provide an illustrative way to describe optical transmission in a multimode optical fiber. The paper covers the physical principles of modulation of optical transmission of fiber light guide by the bending radial variation. In addition, the authors obtained the expression for the total radiant energy in the light guide bend section/cutting in the ray equivalence. The mechanism of modulation of the fiber optical light guide and obtained mathematical expressions are the theoretical foundation for producing amplitude fiber-optic sensors.

Normal calculation of artillery cradle before the robot arm assisted ultrasonic phased array automatic detection

This study is interested in the normal calculation of artillery cradle. When the beam axis of ultrasonic phased array probe cannot detect the workpiece surface vertically, the detection result is usually inaccurate. Thus, in order to determine the normal of the surface to be detected, a method based on visual point cloud to calculate the normal of artillery cradle is proposed in this paper. The proposed method solves two key problems. One is to sparse the point cloud while preserving the tiny information on the surface. A mesh division method along the uv direction is proposed. The disordered point cloud data in 3D space are connected into regular polygon meshes. While establishing the local relationship of point cloud data, it also maintains the overall integrity of point cloud data. The other is to calculate the normal vector of the point cloud. The local plane fitting method based on the least square method calculates the normal at a point of the point cloud. At this time, the calculated normal are nondirective. When there is no abrupt curvature change near the calculated point cloud, the direction of the normal is determined based on the same slope at two adjacent points. The calculated point cloud normal vector is compared with the actual normal vector of the mathematical model. The maximum deviation between the theoretical value and the actual value of the normal vector is 0.465°, and the average deviation is 0.302°. The experimental results show that the proposed method can be used to detect the actual normal of artillery cradle.

Automatic calibration of terrestrial laser scanners using intensity features

AbstractWe propose an in situ self‐calibration method by detecting and matching intensity features on the local planes in overlapping point clouds based on the Förstner operator. We successfully matched the intensity features from scans at different locations by feature matching on common local planes rather than on the rasterised grids of the horizontal and vertical angles adopted by the affirmed keypoint‐based algorithm. The capability of extracting features from different stations offers the possibility of comprehensive scanner calibration, solving the disadvantage that the existing keypoint‐based methods can only estimate the two‐face‐sensitive model parameters. The proposed algorithm has been tested with a high‐precision panoramic scanner, Leica RTC360, using datasets from a calibration hall and a general working scenario. It has been shown that the proposed approach consistently calibrates the two‐face‐sensitive model parameters with the affirmed keypoint‐based one. For the case of comprehensive calibration with the offset estimated and some angular parameters separated where the previous keypoint‐based one failed, the proposed algorithm achieves an accuracy of 0.16 mm, 2.7″ and 2.1″ in range, azimuth and elevation for the estimated target centres. The proposed algorithm can accurately calibrate two‐face‐sensitive and more comprehensive model parameters without any preparation on‐site, for example, mounting targets.

Transverse abdominis plane block as a method of anesthesia after caesarean section

Although we have various methods of analgesia, the prevalence of severe pain after caesarean section remains high. Therefore, it is necessary to look for new reliable technologies for optimal postoperative anesthesia.The objective was to compare the efficiency of postoperative wound infiltration with a local anesthetic and transverse abdominis plane block (TAP-block) as a component of multimodal analgesia in the postoperative period after cesarean section.Materials and methods. A prospective randomized study was conducted. It included 91 patients after elective caesarean section under spinal anesthesia. Patients were divided into 3 groups depending on the method of postoperative analgesia. In group 1 (n = 30), we used wound analgesia. In group 2 (n = 32), transverse abdominis plane block was performed. In group 3 (n = 29), intravenous infusion of paracetamol in combination with intramuscular injection of tramadol 0.5 mg/kg were used for postoperative analgesia.Results. Pain syndrome was less severe after wound analgesia and TAP-block for 24 hours compared to analgesia with systemic analgesics. Moreover, during wound analgesia, lower points of the visual analogue scale (VAS) were traced for three days. The minimum consumption of paracetamol was on the background of wound analgesia, while no patient required the introduction of narcotic analgesics. Women in the wound analgesia group were able to earlier activating: they could walk after 5.6±0.2 hours, compared to 6.1± 0.2 hours with TAP-block and 8.8± 0.4 hours with analgesia with systemic analgesics.Conclusion. Continuous analgesia of postoperative wound is a safe and effective method that allows achieving adequate postoperative analgesia, avoiding using narcotic analgesics and reducing the consumption of non-narcotic systemic analgesics.

Road potholes detection from MLS point clouds

The extraction of pavement damage information is one of the major difficulties in the application research of mobile laser scanning point cloud data. To address the problem of inaccurate detection results by using only relative distance to detect potholes, this paper proposes a novel pothole detection method that combines directed distance and skewed distribution. Firstly, the rapid positioning of the pothole is realized by the directed distance, which is calculated from the points and the local fitted plane. And monomerization and denoising of potential potholes are achieved by density clustering. Then, the new accurate plane is fitted by the surrounding pavement points of the potential pothole to obtain accurate directed distances. The negative skewed distribution of the directed distance histogram and the skewness coefficient are used for the accurate determination of the pothole. Finally, the three-dimensional geometric features of the pothole are extracted. Experiments were carried out on a road with poor road conditions. The experimental results validated the effectiveness and practicality of the proposed method. It can achieve automatic detection of potholes with different shapes and deformation degrees, and has effectively improved the efficiency of automatic road inspection.

Quadrature by Two Expansions for Evaluating Helmholtz Layer Potentials

In this paper, a Quadrature by Two Expansions (QB2X) numerical integration technique is developed for the single and double layer potentials of the Helmholtz equation in two dimensions. The QB2X method uses both local complex Taylor expansions and plane wave type expansions to achieve a resulting representation which is numerically accurate for all target points inside a leaf box in the fast multipole method (FMM) hierarchical tree structure. The QB2X method explicitly includes nonlinear dependency of the boundary geometry in the plane wave expansions, thereby providing for higher-order representations of both the boundary geometry and density functions in the integrand, with its convergence following standard FMM error analysis. Numerical results are presented to demonstrate the performance of the QB2X method for Helmholtz layer potentials using one expansion center for the entire FMM-leaf box for both flat and curved boundaries with various densities.

Visualizing local bending of lattice planes by extending two-azimuth synchrotron X-ray diffraction datasets to asymmetric reflection

Synchrotron X-ray rocking curve imaging (RCI) is modified to visualize local bending of lattice planes of a single crystal substrate (XR-V-LBLP). This method uses two-azimuth RCI datasets of asymmetric reflection or symmetric reflection. The analysis algorithm is described and a Python software code is provided in the Supplementary material. The two symmetrically equivalent 112¯4 datasets obtained from a GaN (0001) 4-inch wafer are reanalyzed using this software. The normal vector, reciprocal-lattice vector, of the local lattice planes, which is approximately parallel to the sample surface, is formulated as the product of two rotation matrices. This vector is written in polar coordinates using the length and two declination angles, newly introduced in this article. The spatial and probability distributions of the declination angles are also presented. The proposed method enables visualization of the local shape or orientation of the lattice planes of the entire wafer. The limits of application of the method are examined for the samples studied. The sample is found to satisfy two conditions regarding the relative d-spacing difference and the curvature of the lattice planes at all 50 adjacent μm positions.

Orientation of the spins of galaxies in the local volume

ABSTRACT We estimated the angular momentum, J, of 720 galaxies in the Local Volume with distances r < 12 Mpc. The distribution of the average angular momentum along the Hubble sequence has a maximum at the morphological type T = 4 (Sbc), while the dispersion of the J-values for galaxies is minimal. Among the Local Volume population, 27 elite spiral galaxies stand out, with an angular momentum > 0.15 of the Milky Way, J > 0.15JMW, making the main contribution ($\gt 90~{{\ \rm per\ cent}}$ ) to the total angular momentum of galaxies in the considered volume. Using observational data on the kinematics and structure of these galaxies, we determined the direction of their spins. We present the first map of the distribution of the spins of 27 nearby massive spiral galaxies in the sky and note that their pattern does not exhibit significant alignment with respect to the Local Sheet plane. The relationship between the magnitude of the angular momentum and stellar mass of the local galaxies is well represented by a power law with an exponent of (5/3) over an interval of six orders of magnitude of the mass of galaxies.

A Novel Method for Obstacle Detection in Front of Vehicles Based on the Local Spatial Features of Point Cloud

Obstacle detection is the primary task of the Advanced Driving Assistance System (ADAS). However, it is very difficult to achieve accurate obstacle detection in complex traffic scenes. To this end, this paper proposes an obstacle detection method based on the local spatial features of point clouds. Firstly, the local spatial point cloud of a superpixel is obtained through stereo matching and the SLIC image segmentation algorithm. Then, the probability of the obstacle in the corresponding area is estimated from the spatial feature information of the local plane normal vector and the superpixel point-cloud height, respectively. Finally, the detection results of the two methods are input into the Bayesian framework in the form of probabilities for the final decision. In order to describe the traffic scene efficiently and accurately, the detection results are further transformed into a multi-layer stixel representation. We carried out experiments on the KITTI dataset and compared several obstacle detection methods. The experimental results indicate that the proposed method has advantages in terms of its Pixel-wise True Positive Rate (PTPR) and Pixel-wise False Positive Rate (PFPR), particularly in complex traffic scenes, such as uneven roads.

Non-Local Means De-Speckling Based on Multi-Directional Local Plane Inclination Angle

The unavoidable speckle in SAR images seriously interferes with image quality and has a negative effect on subsequent image interpretation. The existing filters still need to be strengthened in terms of both noise suppression and edge preservation. Based on this, a novel non-local means filter by multi-directional local plane inclination angle (MDLPIA) is proposed. The proposed filter uses the MDLPIA to reconstruct a new weight function for non-local means filtering. One instance of simulation data and four real SAR images are used for filtering experiments. In the experiment, seven other filters with excellent performance are selected for comparison, and six quantitative indicators are selected for algorithm performance evaluation. The experimental results show that the proposed filter achieves good visual and index evaluation results, and the equivalent number of looks (ENL) is at least 22.13 times higher than the unfiltered image. The effectiveness and superiority of the proposed algorithm are thus verified.

Effect of retained austenite on the fracture behavior of a novel press-hardened steel

• Effect of RA on both the tensile and bending properties of the PHS has been studied. • RA with various mechanical stabilities and volume fraction are obtained via tuning the degree of auto-tempering of martensite during die quenching. • The tensile performance is improved with increasing of volume fractions of RA in the novel PHS. • The mechanical stability, rather than volume fraction of RA, has significant impact on the bendability of the PHS. Tensile and bending properties are two critical attributes of press hardened steels (PHSs) for automotive body structural components. However, the research on these properties of PHSs with retained austenite (RA), which is introduced to improve the mechanical properties, has not been well reported. In this study, the effect of RA on the quasi-static uniaxial tensile and three-point bending behaviors has been systematically investigated for a newly developed Cr and Si alloyed PHS. RA with various degrees of mechanical stabilities was obtained by tuning the auto-tempering of martensite through the control of the die contact pressure during the press hardening process. Mechanically stable RA provides the optimal combination of tensile and bending performance, while the PHS with RA of poor mechanical stability has a deteriorated bending toughness as manifested by a reduction of bending angle from approximately 61.6° to 56.8°. However, its tensile properties, in contrast, are the best in terms of the product of ultimate tensile strength and total elongation (15.9 GPa %). This is mainly attributed to the unstable RA on the outermost surface of the bending sample. The unstable RA can easily transform into brittle martensite under local plane strain and strain gradient conditions in the bending test compared with uniaxial stress in the tensile test, promoting crack initiation and propagation. Furthermore, the effect of martensitic auto-tempering or contact pressure on the quantity and stability of RA are also discussed. This study would provide a useful reference to guide hot stamping process optimization for the newly developed Cr and Si-containing press-hardened steel.

Response of 2D and 3D crystal plasticity models subjected to plane strain condition

The plane strain assumption is generally applied in crystal plasticity finite element (CPFE) simulations in a 2D space to characterize the macroscopic material response considering microstructural features. However, the reliability and accuracy of 2D approximations need to be addressed. In this paper, crystal plasticity finite element simulations of 2D and 3D RVEs are performed with local and averaged plane strain assumptions in Abaqus/Standard. Plane strain postulation is implemented via plane strain elements in 2D and zero average thickness strain in 3D. Irregularly shaped RVEs are generated using the open-source software library Voro++. A conforming mesh is rendered to assign periodic boundary conditions on geometrically periodic RVEs. Periodic boundary condition (PBC) is applied using a prescribed macroscopic deformation gradient tensor. A rate-independent finite strain crystal plasticity model is employed as the user-defined material behavior in finite element simulations. A discrepancy is observed between macroscopic flow curves of 2D and 3D RVEs. The comparison was made for three cases of latent hardening in the crystal plasticity model. In all cases, 3D flow curves exceed 2D results. The results indicate that the deviation is caused by out-of-plane slip activation in 3D simulations, which proves to be an additional hardening source.

A local tangent plane distance-based approach to 3D point cloud segmentation via clustering

This paper proposes an effective measure for the planar segmentation problem based on the clustering method. It uses the distance from a point to the local plane as a metric to characterize the relationship between data. As a result, the data points of the coplanar have a high similarity to distinguish each plane. A dissimilarity matrix of the input point cloud can be evaluated, and multidimensional scaling analysis is performed to reconstruct the correlation information between data points in the 3D Euclidean space. The obtained reconstructed point cloud shows the separation between different planes. An adaptive DBSCAN clustering method based on density stratification is developed to perform cluster segmentation on the reconstructed point cloud. Experimental results show that the proposed method can effectively solve the over-segmentation problem, and at the same time provide high segmentation accuracy.

A Lightweight Real-Time 3D LiDAR SLAM for Autonomous Vehicles in Large-Scale Urban Environment

For autonomous vehicles, real-time localization and mapping in the unknown environment is very important. In this paper, a fast and lightweight 3D LiDAR simultaneously localization and mapping (SLAM) is presented for the localization of autonomous vehicles in large-scale urban environments. A novel encoding approach based on depth information is proposed to encode unordered point clouds with various resolutions, which avoids missing dimensional information in the projection of point clouds onto a 2D plane. Principal components analysis (PCA) is modified by dynamically selecting neighborhood points according to the encoded depth information to fit the local plane with less time consuming. The threshold and the number of feature points are adaptive according to distance intervals, results in sparse feature points extracted and uniformly distributed in the three-dimensional space. The extracted significant feature points improve the accuracy of the odometer and speed up the alignment of the point cloud. The effectiveness and robustness of the proposed algorithm are verified on the KITTI odometry benchmark and MVSECD. A fast runtime of 21 ms is obtained for the odometer estimation. Compared to several typical state-of-the-art methods on the KITTI odometry benchmark, the proposed approach reduces translation errors by at least 19% and rotation errors by 7.1%.

Fire Detection on Video Using ViBe Algorithm and LBP-TOP

In this research, we built a system to detect fire using the ViBe (Visual Background Extractor) algorithm to extract dynamic targets. The ViBe algorithm is better at detecting moving target objects such as flame combustion. In this research we combined the ViBe algorithm with three frame differencing to gain better results on movement object. The HSI color space model was applied after the movement object was obtained. We used Local Binary Pattern-Three Orthogonal Planes to obtain the feature extraction to be classified with Support Vector Machine. Our result has shown that the proposed system were able to detect the fire using the LBP-TOP and ViBe algorithm methods with an average accuracy rate of 88.10%, and the best accuracy was 90.37%. The parameters used to achieve this accuracy in the feature extraction process were T=120, Radius=2, and frame gap=15, then the threshold value parameter for three-frame difference parameter was 25.

Memristor synapse-coupled piecewise-linear simplified Hopfield neural network: Dynamics analysis and circuit implementation

Electromagnetic induction current is generated between the adjacent neurons in neural network caused by the existence of membrane potential difference. Memristor is the fourth fundamental electric element, which can mimic the behavior of neural synapses and simulate the electromagnetic induction effect. In this paper, in order to simplify practical implementation, the commonly used hyperbolic tangent activation function of Hopfield neural network (HNN) is replaced by a piecewise-linear function, and a simple bi-neuron-based memristor synapse-coupled HNN is proposed. Theoretical analysis and numerical simulation results illustrate that the memsirstive HNN possesses five equilibria including one unstable saddle-focus, two unstable saddle points, and two stable node points (or node-foci). Local attraction basins and phase plane plots show that the memristive HNN model behaves multistability of coexisting chaos, periodic limit cycles, and stable point attractors. Various system dynamical behaviors affected by parameters of the piecewise-linear activation function, memristor coupling strength, and initial conditions of the neurons are investigated by numerical simulations. Furthermore, an analog circuit of the memristive HNN model is simply designed, which is easier for hardware implementation as the piecewise-linear activation function can be implemented by simple op-amp-based module. Finally, the experimental results verify the correctness of the design and analyses.

Automated identification of slip system activity fields from digital image correlation data

Crystallographic slip system identification methods are widely employed to characterize the fine scale deformation of metals. While powerful, they usually rely on the occurrence of discrete slip bands with clear slip traces and can struggle when complex mechanisms such as cross-slip, curved slip, diffuse slip and/or intersecting slip occur. This paper proposes a novel slip system identification framework, termed SSLIP (for Slip Systems based Local Identification of Plasticity), in which the measured displacement gradient fields (from Digital Image Correlation) are locally matched to the kinematics of one or multiple combined theoretical slip systems, based on the measured crystal orientations. To identify the amount of slip that conforms to the measured kinematics, an optimization problem is solved for every datapoint individually, resulting in a slip activity field for every considered slip system. The identification framework is demonstrated and validated on an HCP virtual experiment, for discrete and diffuse slip, incorporating 24 slip systems. Experimental case studies on FCC and BCC metals show how full-field identification of discrete slip, diffuse slip and cross-slip becomes feasible, even when considering 48 slip systems for BCC. Moreover, the methodology is extended into a dedicated cross-slip identification method, which directly yields the orientation of the local slip plane trace orientation, purely based on the measured kinematics and on one or two chosen slip directions. For even more challenging cases revealing a persistent uncertainty in the slip identification, a two-step identification approach can be employed, as is demonstrated on a highly challenging HCP virtual experiment.