Coordinate System Research Articles

Low-dimensional projection of reactivity classes in chemical reaction dynamics using supervised dimensionality reduction.

Transition state theory (TST) provides a framework to estimate the rate of chemical reactions. Despite its great success with many reaction systems, the underlying assumptions such as local equilibrium and nonrecrossing do not necessarily hold in all cases. Although dynamical systems theory can provide the mathematical foundation of reaction tubes existing in phase space that enables us to predict the fate of reactions free from the assumptions of TST, numerical demonstrations for large systems have been yet one of the challenges. Here, we propose a dimensionality reduction algorithm to demonstrate structures in phase space (called reactive islands) that predict reactivity in systems with many degrees of freedom. The core of this method is the application of supervised principal component analysis, where a coordinate transformation is performed to preserve the dynamical information on reactivity (i.e., to which potential basin the system moves from a region of interest) as much as possible. The reactive island structures are expected to be reflected in the transformed, low-dimensional phase space. As an illustrative example, the algorithm is scrutinized using a modified Hénon-Heiles Hamiltonian system extended to many degrees of freedom, which has three channels leading to three different products from one stable potential basin. It is shown that our algorithm can predict the reactivity in the transformed, low-dimensional coordinate system better than a naïve coordinate system and that the reactivity distribution in the transformed low-dimensional space is considered to reflect the underlying reactive islands.

Morphological observation of occipital condyle position in Chinese skulls and potential clinical significance.

To study the anatomy of the Chinese occipital condyle and its position relative to the occipital foramen and skull. Measurements were taken from 106 adult Chinese skulls using a Cartesian coordinate system centered on the foramen magnum. Measurements included the longitudinal diameter of the foramen magnum, distances from various points on the occipital condyles to the foramen magnum and skull landmarks, and the occipital condyle classification index (OCI) and skull-occipital condyle classification index (SOCI). OCI categorized the position of the foramen magnum and occipital condyles into three groups: OCI ≤ 0.40 (3 cases, 2.83%), 0.40 < OCI ≤ 0.50 (75 cases, 70.75%), and OCI > 0.50 (28 cases, 26.42%). SOCI categorized the relationship between the skull and occipital condyles into two groups: 0.5 < SOCI ≤ 0.6 (49 cases, 46.23%) and 0.6 < SOCI ≤ 0.7 (57 cases, 53.77%). Four relationship types were identified based on specific measurements: Type I (23 cases, 21.70%), Type II (42 cases, 39.62%), Type III (4 cases, 3.77%), and Type IV (37 cases, 34.91%). Sagittal movement of the occipital condyle affects the cervical spine's curvature. Asymmetry between the occipital condyles and the foramen magnum may misalign the skull with the body's coronal plane.

Low-rank rotation matrices-based DOA estimation with a moored circular vector sensor array

Abstract Water currents affect circular vector sensor arrays (CVSAs) suspended from a moored platform, causing them to rotate underwater. This rotation alters the direction of sources within the array coordinate system over time. Traditional methods that rely on numerous snapshots often yield inaccurate results, particularly for faint sources. To improve the accuracy, we introduce a direction-finding technique for CVSAs that employs low-rank rotation matrices. The low-rank rotation matrices are constructed using the heading information of the CVSAs and the subregion array manifold vector matrices to achieve spatial focusing. When these matrices are applied to the measurement data, the resulting covariance matrix displays subspace characteristics similar to that of a stationary CVSA. Our performance analysis revealed that low-rank rotation matrices offer higher focusing gains than conventional rotation matrices. The method proposed in this study effectively improves the direction estimation performance for weak targets and extends the practical applicability of measurement techniques for rotating platforms. Both simulations and experiments confirm that our approach outperforms the modified traditional beamforming and other spatial focusing techniques in terms of resolution and precision. Notably, when the signal-to-noise ratio (SNR) is below -4 dB, the resolution for distinguishing between the two sources increases by more than 50%.&amp;#xD;

A graphics-based digital twin (GBDT) framework for accurate UAV localization in GPS-denied environments

Autonomous navigation of Unmanned Aerial Vehicles (UAVs) is crucial for effective assessment of large-scale civil infrastructure, as manual UAV control is time consuming and prone to mishaps. Autonomous navigation outdoors typically employs GPS signals to enable accurate localization and reduce long-term drifts. However, in many civil engineering applications, GPS signals are either poor or unavailable due to interference and/or multi-path effects. Current approaches for UAV localization in GPS-denied environments, track geometric features such as corners; however, these natural features can be misrepresented due to the presence of occlusions and/or image processing errors, resulting in significant localization errors that can grow with time. AprilTags can reduce localization errors, but installation on large-scale civil infrastructure can be challenging. Therefore, this paper proposes a framework that leverages the wealth of visual and geometric information encoded in a Graphics-Based Digital Twin (GBDT) of a target infrastructure to provide accurate localization of a UAV. The GBDT is comprised of a computer graphics model that faithfully represents a target structure’s geometry, structural features, and visual textures. The visual details of the GBDT are exploited to design an object recognition algorithm that detects GBDTtags, which are distinctive objects (or a collection of components) on the target structure in advance; GBDTtags provide functionality similar to AprilTags. When the camera attached to a UAV detects one or more GBDTtags, the vertices of the GBDTtags are mapped from the image plane into the GBDT coordinate system, allowing for the UAV to be localized. The framework, termed herein as GBDTpose, is first validated numerically using Blender, Gazebo, and Mavros software-in-the-loop (SITL). Subsequently, field validation is carried out using the Kavita and Lalit Bahl Smart Bridge at the University of Illinois Urbana-Champaign (UIUC). Results show that localization in GPS-denied environments can be achieved with 5-50 cm accuracy without the need for physical markers being placed on the structure.

A comparative analysis of intelligent energy modelling approaches for a grid-tied PVT system application

Renewable energy resources are a long-term answer to the current chronic energy dilemma. Solar photovoltaic (PV) systems are the most often used form of a practical solution for power supply and energy management in buildings. A PV-thermal (PVT) system is essential to lowering the demand for grid energy by capturing electrical and thermal energy from sunlight, optimising energy usage and encouraging sustainable energy practices. The most significant difficulty faced by developing countries, such as South Africa, is a lack of power supply to meet demand while limiting grid overload. An alternative source of energy is a critical component. This research compares two intelligent energy modelling methodologies: optimal control scheme-based open loop and model predictive control (MPC) in a PVT application. The primary goal of the modelling is to limit the electricity required from the grid while stressing the system’s energy efficiency and cost-effectiveness. The open loop approach uses mathematical optimisation techniques to establish the best control strategy for the PVT system. The ideal set-points for various system parameters are found by presenting the problem as an optimisation task to reduce grid power usage. The optimal control technique delivers a global optimisation solution based on the system dynamics and constraints. The MPC technique employs a predictive control technique of the PVT system to create optimal control actions in a receding horizon manner. The MPC algorithm anticipates future system behaviour and generates control actions that minimise grid power drawn by iteratively solving an optimisation problem at each time step. This robust online control scheme enables real-time modifications and responses to system disruptions that effectively and dynamically coordinate system behaviour.

Proposal of UAV-SLAM-Based 3D Point Cloud Map Generation Method for Orchards Measurements

This paper proposes a method for generating highly accurate point cloud maps of orchards using an unmanned aerial vehicle (UAV) equipped with light detection and ranging (LiDAR). The point cloud captured by the UAV-LiDAR was converted to a geographic coordinate system using a global navigation satellite system / inertial measurement unit (GNSS/IMU). The converted point cloud is then aligned with the simultaneous localization and mapping (SLAM) technique. As a result, a 3D model of an orchard is generated in a low-cost and easy-to-use manner for pesticide application with precision. The method of direct point cloud alignment with real-time kinematic-global navigation satellite system (RTK-GNSS) had a root mean square error (RMSE) of 42 cm between the predicted and true crop height values, primarily due to the effects of GNSS multipath and vibration of automated vehicles. Contrastingly, our method demonstrated better results, with RMSE of 5.43 cm and 2.14 cm in the vertical and horizontal axes, respectively. The proposed method for predicting crop location successfully achieved the required accuracy of less than 1 m with errors not exceeding 30 cm in the geographic coordinate system.

Mixed reality-based coordinate system for enhancing survey knowledge acquisition: a study on allocentric and egocentric perspectives

ABSTRACT Spatial knowledge, especially survey knowledge, plays a pivotal role in people’s daily spatial tasks. However, the inherently limited visual perception and integration of spatial information often leads to inaccuracies in survey knowledge, with far-reaching consequences that affect performance, emotion, and safety in completing spatial tasks. In this study, we developed a mixed reality (MR)-based coordinate system and conducted a comparative user experiment involving 56 participants to explore whether perceiving metric and global spatial references during navigation may enhance the accuracy of user-acquired spatial knowledge. The experiment encompassed a spatial learning task where participants navigated and learned the selected indoor environment, followed by a desktop-based landmark recalling task to evaluate the accuracy of participants’ acquired survey knowledge. The results revealed the following insights: (1) the use of MR-based coordinate system significantly improved egocentric and allocentric spatial relations in participants’ survey knowledge; (2) participants’ errors in spatial relations among landmarks accumulate over distance, whereas the MR-based coordinate system helps maintain the errors at a consistent level; (3) no significant correlations were found between errors in participants’ survey knowledge and environmental familiarity, suggesting that the aiding effect of the MR-based coordinate system was independent of users’ prior knowledge of the environment; (4) participants reported increased mental demand using the MR-based coordinate system, but this did not result in diminished spatial learning performance or additional time pressure and learning efforts. These empirical results contribute to the future study of spatial knowledge acquisition and the design of spatial learning interfaces in mixed reality.

High-resolution motion compensation for brain PET imaging using real-time electromagnetic motion tracking.

Substantial improvements in spatial resolution in brain positron emission tomography (PET) scanners have greatly reduced partial volume effect, making head movement the main source of image blur. To achieve high-resolution PET neuroimaging, precise real-time estimation of both head position and orientation is essential for accurate motion compensation. A high-resolution electromagnetic motion tracking (EMMT) system with an event-by-event motion correction is developed for PET-CTscanners. EMMT is comprised of a source, an array of sensors, and a readout electronic unit (REU). The source acts as a transmitter and emits an EM dipole field. It is placed in close proximity to the sensor array and detects changes in EM flux density due to sensor movement. The REU digitizes signals from each sensor and captures precise rotational and translational movements in real time. Tracked motion in the EMMT coordinate system is synchronized with the PET list-mode data and transformed into the scanner coordinate system by locating paired positions in both systems. The optimal rigid motion is estimated using singular value decomposition. The rigid motion and depth-of-interaction (DOI) parallax effect are corrected by event-by-event rebinning of mispositioned lines-of-response (LORs). We integrated the EMMT with our recently developed ultra-high resolution Prism-PET prototype brain scanner and a commercial Siemens Biograph mCT PET-CT scanner. We assessed the imaging performance of the Prism-PET/EMMT system using multi-frame motion of point sources and phantoms. The mCT/EMMT system was validated using a set of point sources attached to both a mannequin head and a human volunteer, for simulating multiframe and continuous motions, respectively. Additionally, a human subject for [18F]MK6240 PET imaging wasincluded. The tracking accuracy of the Prism-PET/EMMT system was quantified as a root-mean-square (RMS) error of 0.49 for 100 axial rotations, and an RMS error of 0.15 mm for 100 mm translations.The percent difference (%diff) in average full width at half maximum (FWHM) of point source between motion-corrected and static images, within a motion range of and 10 mm from the center of the scanner's field-of-view (FOV), was 3.9%. The measured recovery coefficients of the 2.5-mm diameter sphere in the activity-filled partial volume correction phantom were 23.9%, 70.8%, and 74.0% for the phantom with multi-frame motion, with motion and motion compensation, and without motion, respectively. In the mCT/EMMT system, the %diff in average FWHM of point sources between motion-corrected and static images, within a motion range of and 10 mm from the center of the FOV, was 14%. Applying motion correction to the [18F]MK6240 PET imaging reduced the motion-induced spill-in artifact in the lateral ventricle region, lowering its standardized uptake value ratio (SUVR) from 0.70 to 0.34. The proposed EMMT system is a cost-effective, high frame-rate, and none-line-of-sight alternative to infrared camera-based tracking systems and is capable of achieving high rotational and translational tracking accuracies for mitigating motion-induced blur in high-resolution brain dedicated PETscanners.

Automated Pipeline for Multi-LiDAR Extrinsic Calibration: Experimental Evaluation and Performance Analysis

Abstract. In recent years, 3D LiDAR (Light Detection and Ranging) has become a crucial sensor in various applications such as autonomous vehicles, robotics, object detection, precision forestry, and agriculture. However, specific LiDAR sensors, such as Velodyne VLP16, exhibit some drawbacks, such as a limited field of view and sparse data density, making them inadequate for certain specific applications. Hence, this research proposes a method for calibrating two VLP16 LiDAR sensors to improve coverage and reduce blind spots. The pipeline for performing the calibration begins with mounting LiDARs correctly in a rod at a specific orientation and distance, followed by the selection of multiple sites for data collection, then performing a registration algorithm for estimating calibration parameters, and then an accuracy assessment of the calibrated point clouds. The registration algorithm used here is a modified version of ICP (Iterative Closest Point), which overcomes the need for initialization and eliminates manual intervention in installing targets or retro-reflectors. Finally, we evaluated the accuracy of the fused point cloud collected in an open environment using two calibrated Velodyne VLP16 sensors. For accuracy assessment, we used the PCA eigenvalue and RMSE value to observe how tightly point clouds are fused. As a calibration result, we got the orientation and translation parameters, which are used to achieve the common coordinate system, and accomplished calibration accuracy up to single-digit precision from all the experimental sites. Now the system of two calibrated VLP16 sensors will provide higher coverage and increased data density and might be useful for forest applications.

Method for prediction magnetic silencing of uncertain energy-saturated extended technical objects in prolate spheroidal coordinate system

Aim. Development of method for prediction by energy-saturated extended technical objects magnetic silencing based on magnetostatics geometric inverse problems solution and magnetic field spatial spheroidal harmonics calculated in prolate spheroidal coordinate system taking into account of technical objects magnetic characteristics uncertainties. Methodology. Spatial prolate spheroidal harmonics of extended technical objects magnetic field model calculated as magnetostatics geometric inverse problems solution in the form of nonlinear minimax optimization problem based on near field measurements for prediction far extended technical objects magnetic field magnitude. Nonlinear objective function calculated as the weighted sum of squared residuals between the measured and predicted magnetic field COMSOL Multiphysics software package used. Nonlinear minimax optimization problems solutions calculated based on particle swarm nonlinear optimization algorithms. Results. Results of prediction extended technical objects far magnetic field magnitude based on extended technical objects spatial prolate spheroidal harmonics of the magnetic field model in the prolate spheroidal coordinate system using near field measurements with consideration of extended technical objects magnetic characteristics uncertainty. Originality. The method for prediction by extended technical objects magnetic cleanliness based on spatial prolate spheroidal harmonics of the magnetic field model in the prolate spheroidal coordinate system with consideration of magnetic characteristics uncertainty is developed. Practical value. The important practical problem of prediction extended technical objects magnetic silencing based on the spatial prolate spheroidal harmonics of the magnetic field model in the prolate spheroidal coordinate system with consideration of extended technical objects magnetic characteristics uncertainty solved. References 48, figures 2.

A Virtual Reality Tool for Accuracy Assessment of 3D Models in an Immersive Virtual Environment

Abstract. Accurate validation and assessment techniques are essential for ensuring the reliability of spatial reconstructions derived from photogrammetry, enabling well-informed decision-making across diverse domains. This study presents a Virtual Reality (VR) based accuracy assessment tool tailored for evaluating the accuracy and quality of 3D models generated by Unmanned Aerial Vehicles (UAVs). Leveraging the Unity game engine platform, our workflow entails three key steps: aligning real-world coordinates with an arbitrary Unity coordinate system, transforming the positions of Ground Control Points (GCPs) from field survey to the arbitrary system using a reference GCP, and marking observed points on the 3D models. Absolute and Relative Root Mean Square Errors (RMSE), Mean Errors (ME), and Standard Deviation of errors (SD) are computed within the virtual environment via the game object transform properties. The error distributions around each GCP are visually depicted using Unity game engine components for enhanced interaction and comprehension. The efficacy of the tool is validated through experimentation on four 3D models generated from varying camera angles during UAV data capture. The tool provides the opportunity to directly interact with the 3D models and visualize the errors, which is quite distinct from traditional methods. Using the developed tool, results were obtained to indicate that configurations employing camera angles of 60° + 75º exhibit notable performance in terms of relative and absolute accuracy.

Multidisciplinary teaching with an active video game: the effect on learning in mathematics and physical education

ABSTRACT Practising active video games (AVGs) requires performing motor and cognitive tasks, which might foster success in physical education and other school subjects but remains poorly investigated. This study examined the learning effects of six lessons using AVGs with physical education and mathematics content. Overall, 216 school-students composed an experimental group (n = 99) and a control group (n = 107). Both attended six lessons, each on using a Cartesian coordinate system and ball-throwing accurately, with AVGs in the experimental group only. Learning was assessed at Lessons 1 and 6, situational interest and moderate-to-vigorous physical activity (MVPA) at Lessons 3 and 5. MANOVAs showed no between-group differences in situational interest and higher MVPA for the control group at Lesson 3 only. Statistical analysis showed higher learning scores (mathematics and physical education) for the experimental group at Lesson 6, suggesting possible interest in AVGs during multidisciplinary sequences connecting physical education and mathematics.

Assessment of a multiphase formulation of one-dimensional turbulence using direct numerical simulation of a decaying turbulent interfacial flow

The interaction between turbulence and surface tension is studied numerically using the one-dimensional-turbulence (ODT) model. ODT is a stochastic model simulating turbulent flow evolution along a notional one-dimensional line of sight by applying instantaneous maps that represent the effects of individual turbulent eddies on property fields. It provides affordable high resolution of interface creation and property gradients within each phase, which are key for capturing the local behavior as well as overall trends, and has been shown to reproduce the main features of an experimentally determined regime diagram for primary jet breakup. Here ODT is used to investigate the interaction of turbulence with an initially planar interface. The notional flat interface is inserted into a periodic box of decaying homogeneous isotropic turbulence, simulated for a variety of turbulent Reynolds and Weber numbers. Unity density and viscosity ratios serve to focus solely on the interaction between fluid inertia and the surface-tension force. Statistical measures of interface surface density and spatial structure along the direction normal to the initial surface are compared to corresponding direct-numerical-simulation (DNS) data. Allowing the origin of the lateral coordinate system to follow the location of the median interface element improves the agreement between ODT and DNS, reflecting the absence of lateral nonvortical displacements in ODT. Beyond the DNS-accessible regime, ODT is shown to obey the predicted parameter dependencies of the Kolmogorov critical scale in both the inertial and dissipative turbulent-cascade subranges. Notably, the probability density function of local fluctuations of the critical scale is found to collapse to a universal curve across both subranges. Published by the American Physical Society 2024

Industrial robot calibration optimization method based on R-optimal criterion and improved IOOPS algorithm

Abstract In this paper, a novel kinematic parameter calibration method based on the R-optimal criterion and the improved iterative one-by-one pose search (IOOPS) algorithm is proposed to improve the end-effector positioning accuracy of industrial robots. First, a novel industrial robot error calibration model based on the product of exponential model and generalized error model is established, and the ideal pose transformation matrix from the robot base coordinate system to the laser tracker measurement coordinate system is obtained using the least-squares method, thereby obtaining the initial parameter vector of the robot calibration system. Second, various joint angle values at different positions within the robot’s workspace and the corresponding end-effector coordinate data, namely calibration sampling point data, are collected. Subsequently, the improved IOOPS algorithm combined with the observability index O R proposed by the R-optimal criterion is used to select the optimized calibration sampling points. Finally, the optimized sampling point data are combined with the Levenberg–Marquardt algorithm to optimize the parameters and obtain the optimal kinematic parameters. The experimental results show that the average end-effector error of the robot decreases from 0.5822 to 0.2492 mm after calibration using this method, demonstrating the effectiveness of the optimized sampling points in the calibration process achieved through the improved algorithm and the new observability index.

Duality of spaces and the origin of integral reflection conditions

The dualism between direct and reciprocal space is at the origin of well known relations between basis vectors in the two spaces. It is shown that when a coordinate system corresponding to a non-primitive unit cell is adopted, this dualism has to be handled with care. In particular, the reciprocal of a non-primitive unit cell is not a unit cell but a region in reciprocal space that does not represent a unit of repetition by translation. The basis vectors do not correspond to reciprocal-space cell lengths, contrary to what is stated even in the core CIF dictionary. The corresponding unit cell is a multiple of this region. The broken correspondence between basis vectors and unit cell is at the origin of the integral reflection conditions.

Modified medial approach for the treatment of fractures of the lower third of the humeral shaft: An anatomical study

BackgroundThe anatomical study of the modified medial approach for addressing fractures of the distal third of the humeral shaft aimed to elucidate the benefits of this method in providing optimal exposure for surgical intervention. MethodsSixteen upper limb specimens from eight cadavers, obtained from the Anatomy Teaching Department of Fujian Medical University, were dissected. Three-dimensional anatomical structures were mapped onto a two-dimensional coordinate system. Key anatomical structures relevant to the modified medial approach, including the medial cutaneous nerve, musculocutaneous nerve, ulnar nerve, basilic vein, brachial artery, superior ulnar collateral artery, and inferior ulnar collateral artery, were documented in detail. ResultsThe average humeral shaft length measured (29.22 ± 2.78) cm, with its medial surface being flat and well-suited for plate fixation. The basilic vein, located superficially in the upper arm's first quadrant, measured (1.35 ± 0.35) cm from the most prominent point of the medial epicondyle of the humerus, with the deep fascia being penetrated at (12.41 ± 1.71) cm. The basilic vein serves as a key landmark for the modified medial approach. The nervi cutanei antebrachii medialis, running along the medial biceps humerus, closely accompanies the basilic vein, perforating the deep fascia above the medial epicondyle and extending anterior external and posterior medial branches. These branches are positioned (0.80 ± 0.17) cm and (0.45 ± 0.29) cm, respectively, from the basilic vein. Additionally, all nervi cutanei antebrachii medialis pass anteriorly to the basilic vein before continuing distally to the forearm. The ulnar nerve initially accompanies the basilic vein in the upper arm but diverges posteriorly without branching at (14.75 ± 1.74) cm, with the maximum separation from the basilic vein measuring (2.28 ± 0.59) cm. The brachial artery bifurcates into the superior and inferior ulnar collateral arteries along the humeral shaft. The superior collateral ulnar artery primarily supplies the ulnar nerve, positioned (14.14 ± 1.27) cm from the medial epicondyle, which ensures a sufficient blood supply for operative procedures. The musculocutaneous nerve and radial nerve branch are located in the lateral region of the brachial muscle, with minimal postoperative impact on muscle strength when splitting the brachial muscle by one-third. ConclusionsThe modified medial approach, as revealed by anatomical studies, focuses on the fracture site with a straight skin incision aligned between the most prominent point of the medial epicondyle and the midpoint of the axilla, positioned one transverse finger from the radial side. Using the basilic vein as a reference, major vessels and nerves remain undisturbed, ensuring a safe operative zone. This technique allows for significant exposure of both the anterior and external humeral shaft fracture site and the ulnar side butterfly fragment while minimizing tissue damage and facilitating rapid recovery. The approach offers notable clinical value due to its reduced invasiveness and accelerated postoperative rehabilitation.

Macroscale Gradient Dysfunction in Alzheimer's Disease: Patterns With Cognition Terms and Gene Expression Profiles.

Macroscale functional gradient techniques provide a continuous coordinate system that extends from unimodal regions to transmodal higher-order networks. However, the alterations of these functional gradients in AD and their correlations with cognitive terms and gene expression profiles remain to be established. In the present study, we directly studied the functional gradients with functional MRI data from seven scanners. We adopted data-driven meta-analytic techniques to unveil AD-associated changes in the functional gradients. The principal primary-to-transmodal gradient was suppressed in AD. Compared to NCs, AD patients exhibited global connectome gradient alterations, including reduced gradient range and gradient variation, increased gradient scores in the somatomotor, ventral attention, and frontoparietal regions, and decreased in the default mode network. More importantly, the Gene Ontology terms of biological processes were significantly enriched in the potassium ion transport and protein-containing complex remodeling. Our compelling evidence provides a new perspective in understanding the connectome alterations in AD.

A unified calibration method for robot manipulators: hand-eye parameters, kinematic parameters and TCP position calibration

PurposeThe purpose of the paper is to propose an efficient, simple and concise unified robot calibration method that simultaneously considers errors in hand-eye parameters, kinematic parameters and tool center point (TCP) position.Design/methodology/approachThis paper proposes a unified robot calibration method. First, the initial hand-eye matrix and TCP position are computed without considering kinematic parameter errors. Second, the nominal TCP positions in the laser tracker coordinate system {S} are computed. The actual TCP positions in {S} are directly measured. Third, a unified parameter error calibration model is established, and the sequential quadratic programming algorithm is used for error identification. Finally, the identified errors are used for direct error compensation.FindingsSimulation results prove that the proposed scheme can accurately calibrate the hand-eye parameters, kinematic parameters and TCP position simultaneously. Experimental results reveal that the maximum value of the absolute positioning errors is reduced from 5.4725 mm to 0.4095 mm (reduced by 92.52%). Thus, the proposed approach meets the accuracy requirements of most robotic applications.Originality/valueThe main contributions of this paper are: (1) this scheme is efficient. The method can achieve fully automatic calibration by incorporating Kronecker products for the initial hand-eye matrix and TCP position computation. Thereby significantly improving the calibration efficiency and liberating the labor force. (2) This scheme is simple and concise. The hand-eye parameters, kinematic parameters and TCP position errors are modeled in a unified framework. Furthermore, the related redundant parameters are deleted.

A Method for Tracking an Underwater Pipeline from Stereo Images Using an Autonomous Underwater Vehicle

The problem of tracking an underwater pipeline (UP) is considered in the context of an inspection mission. It is assumed that the diameter of the cylindrical pipe is known. To solve this problem, a tracking method is proposed, based on searching and calculating the center line of the UP, and determining the relative position of the autonomous underwater robot (AUV) and UP in the coordinate system of the AUV camera. Unlike well-known analogues, in which the solution is based on recognizing and constructing the boundaries of the UP in images, the proposed method searches for the true position of the center line of the UP on a set of possible options by checking their veracity. Possible options for the spatial position of the search centerline of the current UP section are generated by varying the direction of the beam in the horizontal and vertical plane. The starting point of the ray is the end point of the centerline of the previous section. The veracity criterion is to check that the 3D point features constructed in the scene belong to the cylindrical surface of the UP. The generation and matching of pointfeatures in images of a stereo pair is carried out using the SURF detector. The choice of the correct direction of the center line of the current UP section is ultimately made by voting. The end point of the center line of the current section is determined taking into account the calculated common visibility area with the previous section of the UP. To evaluate the effectiveness of the method, computational experiments were carried out on virtual scenes. The effectiveness was assessed by the accuracy of UP localization (in the AUV coordinate system) and by the speed of calculations in comparison with: a) the first version of this method, based on the use of a vectorized form of images; b) analogues using the Canny and Hough Transform detectors. The stability of the method to the accumulation of navigation accuracy errors during long-term tracking of UPs was also assessed.

Post-processing algorithm of five-axis CNC machine tool under rotation angle optimization

During the operation of 5-axis CNC machine tools, the angle deviation of the rotation axis greatly affects the tool path control. Therefore, a post-processing algorithm of five-axis CNC machine tool with optimized rotation angle was proposed. Firstly, the basic The structure of the machine tool was analyzed, the Hausdoff distance was used to obtain the matching error between the actual machined surface and the difference surface, and the error compensation method was used to compensate the obtained error, and the rotation axis angle of the machine tool was completed according to the processing result. Based on the optimization results, the machine tool coordinate system was established, and the machine tool post-processor was developed through the coordinate transformation results and integrated into the relevant software to realize the post-processing of the machine tool. The experimental results show that the proposed method achieves better processing results when used for post processing of machine tools.