Search Results (33)

Ultrasound probe calibration is crucial for precise spatial mapping in ultrasound-guided surgical navigation and free-hand 3D ultrasound imaging as it establishes the rigid-body transformation between the ultrasound image plane and an external tracking sensor. However, the existing methods often rely on manual feature point selection and exhibit limited robustness to outliers, resulting in reduced accuracy, reproducibility, and efficiency. To address these limitations, we propose a fully automated calibration framework that leverages the geometric priors of an N-wire phantom to achieve reliable recognition. The method incorporates a robust feature point extraction algorithm and integrates a hybrid outlier rejection strategy based on the Random Sample Consensus (RANSAC) algorithm. The experimental evaluations demonstrate sub-millimeter accuracy (<0.6 mm) across varying imaging depths, with the calibration process completed in under two minutes and exhibiting high repeatability. These results suggest that the proposed framework provides a robust, accurate, and time-efficient solution for ultrasound probe calibration, with strong potential for clinical integration. Full article

In order to avoid the dependence of traditional sub-pixel displacement methods on interpolation method calculation, image gradient calculation, initial value estimation and iterative calculation, a Swin Transformer-based sub-pixel displacement measurement method (ST-SDM) is proposed, and a square dataset expansion method is also proposed to rapidly expand the training dataset. The ST-SDM computes sub-pixel displacement values of different scales through three-level classification tasks, and solves the problem of positive and negative displacement with the rotation relative tag value method. The accuracy of the ST-SDM is verified by simulation experiments, and its robustness is verified by real rigid body experiments. The experimental results show that the ST-SDM model has higher accuracy and higher efficiency than the comparison algorithm. Full article

Sensor data fusion is increasingly crucial in the field of autonomous driving. In sensor fusion research, LiDAR and camera have become prevalent topics. However, accurate data calibration from different modalities is essential for effective fusion. Current calibration methods often depend on specific targets or manual intervention, which are time-consuming and have limited generalization capabilities. To address these issues, we introduce MSANet: LiDAR-Camera Online Calibration with Multi-Scale Fusion and Attention Mechanisms, an end-to-end deep learn-based online calibration network for inferring 6-degree of freedom (DOF) rigid body transformations between 2D images and 3D point clouds. By fusing multi-scale features, we obtain feature representations that contain a lot of detail and rich semantic information. The attention module is used to carry out feature correlation among different modes to complete feature matching. Rather than acquiring the precise parameters directly, MSANet online corrects deviations, aligning the initial calibration with the ground truth. We conducted extensive experiments on the KITTI datasets, demonstrating that our method performs well across various scenarios, the average error of translation prediction especially improves the accuracy by 2.03 cm compared with the best results in the comparison method. Full article

This paper introduces a new mathematical modeling of a thermoelastic and electromagnetic infinite body with a cylindrical cavity in the context of four different thermoelastic theorems; Green–Naghdi type-I, type-III, Lord–Shulman, and Moore–Gibson–Thompson. Due to the convergence of the four theories under study and the simplicity of putting them in a unified equation that includes these theories, the theories were studied together. The bunding plane of the cavity surface is subjected to ramp-type heat and is connected to a rigid foundation to stop the displacement. The novelty of this work is considering Maxwell’s time-fractional equations under the Caputo fractional derivative definition. Laplace transform techniques were utilized to obtain solutions by using a direct approach. The Laplace transform’s inversions were calculated using Tzou’s iteration method. The temperature increment, strain, displacement, stress, induced electric field, and induced magnetic field distributions were obtained numerically and represented in figures. The time-fractional parameter of Maxwell’s equations has a significant impact on all the mechanical studied functions and does not affect the thermal function. The time-fractional parameter of Maxwell’s equations works as a resistance to deformation, displacement, stress, and induced magnetic field distributions, while it acts as a catalyst to the induced electric field through the material. Full article

This paper presents an improved method for the non-inertial dynamic analysis of the 3-SPS/U parallel platform (3-SPS/U PM), employing the screw theory and Kane’s method, where S, P, and U denote spherical, prismatic, and universal joints, respectively. The proposed method extends the traditional inertial dynamic analysis to non-inertial systems. First, the generalized screw method is introduced, followed by the derivation of a transformation formula that adapts the screw method to various co-ordinate systems. Subsequently, the velocities and accelerations of each rigid body within the platform under non-inertial conditions are examined by combining the extended screw method with the system’s inverse kinematics model. The extended screw method is not only conceptually simple, but also adaptable to other non-inertial systems. Finally, the standard non-inertial dynamic model of the 3-SPS/U PM is derived through the Kane’s method and validated by the co-simulations with RecurDyn (V9R5) and MATLAB/Simulation (2019b). Full article

Combining multiple data sources, Digital Earth is an integrated observation platform based on air–space–ground–sea monitoring systems. Among these data sources, the Inverse Synthetic Aperture Radar (ISAR) is a crucial observation method. ISAR is typically utilized to monitor both military and civilian ships due to its all-day and all-weather superiority. However, in complex scenarios, multiple targets may exist within the same radar antenna beam, resulting in severe defocusing due to different motion conditions. Therefore, this paper proposes a multiple-target ISAR imaging method with the removal of micro-motion connections based on the integration of joint constraints. The fully motion-compensated targets exhibit low rank and local similarity in the high-resolution range profile (HRRP) domain, while the micro-motion components possess sparsity. Additionally, targets display sparsity in the image domain. Inspired by this, we formulate a novel optimization by promoting the low-rank, the Laplacian, and the sparsity constraints of targets and the sparsity constraints of the micro-motion components. This optimization problem is solved by the linearized alternative direction method with adaptive penalty (LADMAP). Furthermore, the different motions of various targets degrade their inherent characteristics. Therefore, we integrate motion compensation transformation into the optimization, accordingly achieving the separation of rigid bodies and the micro-motion components of different targets. Experiments based on simulated data demonstrate the effectiveness of the proposed method. Full article

The reconstruction of traffic accidents has grown as an interdisciplinary field, encompassing bodies of research from automotive engineering, traffic and transport engineering, biomechanics, and forensic sciences. In this work, a method is proposed by which the value of the force in the safety belt buckle can be determined provided the belt buckle is equipped with a pretensioning system with a pyrotechnic trigger in the pretensioner tube, PBP—Pyrotechnical Buckle Pretensioner, or PLP—Pyrotechnical Lap Pretensioner type. The anti-return system of the pretensioner mechanism, which prevents the passenger’s body from moving forward, contains a set of balls that block the movement of the piston in the pretensioner tube after its activation. When limiting the movement, the force the human body exerts on the safety belt webbing is transformed into the deformation of the pretensioner tube by the balls of the anti-return system. Depending on the magnitude of the force, the marks left by the balls differ. This is an alternative method for determining the force that occurs in a seatbelt and causes injury to the occupants of a vehicle. The advantage of this method is that the force in the seatbelt buckle cable can be determined relatively quickly and accurately by analyzing the deformations in the pretensioner tube, without a need for expensive laboratory equipment. The limitation of the model resides in the consideration of a static system with rigid bodies. The correlation between the normal force causing the deformation of the tube and the force in the belt buckle cable is obtained by means of a mechanical model that explains the operation of the anti-return system. By comparing the values of the normal force given by the proposed model and the elastoplastic model, a good correlation is found. Finally, a regression curve is determined to help the expert in approximating the force in the buckle cable depending on the deformation size in the pretensioner tube. The value of this force also enables biomechanical or medical specialists to correlate the degree of injury to occupants of a vehicle depending on the force in the seatbelt. Full article

Back pain is regularly associated with biomechanical changes in the spine. The traditional methods to assess spine biomechanics use ionising radiation. Vertebral Metrics (VM) is a non-invasive instrument developed by the authors in previous research that assesses the spinous processes’ position. However, the spine model used by VM is not accurate. To overcome it, the present paper proposes a pioneering and simple articulated model of the spine built through the data collected by VM. The model is based on the spring–mass system and uses the Levenberg–Marquardt algorithm to find the arrangement of vertebral bodies. It represents the spine as rigid geometric transformations from one vertebra to the other when the extremity vertebrae are stationary. The validation process used the Bland–Altman method to compare the Cobb and the intervertebral angles computed by the model with the radiographic exams of eight patients diagnosed with Ankylosing Spondylitis. The results suggest that the model is valid; however, previous clinical information would improve outcomes by customising the lower and upper vertebrae positions, since the study revealed that the C6 rotation slightly influences the computed angles. Applying VM with the new model could make a difference in preventing, monitoring, and early diagnosing spinal disorders. Full article

In recent years, there has been significant progress in human pose estimation, fueled by the widespread adoption of deep convolutional neural networks. However, despite these advancements, multi-person 2D pose estimation still remains highly challenging due to factors such as occlusion, noise, and non-rigid body movements. Currently, most multi-person pose estimation approaches handle joint localization and association separately. This study proposes a direct regression-based method to estimate the 2D human pose from a single image. The authors name this network YOLO-Rlepose. Compared to traditional methods, YOLO-Rlepose leverages Transformer models to better capture global dependencies between image feature blocks and preserves sufficient spatial information for keypoint detection through a multi-head self-attention mechanism. To further improve the accuracy of the YOLO-Rlepose model, this paper proposes the following enhancements. Firstly, this study introduces the C3 Module with Swin Transformer (C3STR). This module builds upon the C3 module in You Only Look Once (YOLO) by incorporating a Swin Transformer branch, enhancing the YOLO-Rlepose model’s ability to capture global information and rich contextual information. Next, a novel loss function named Rle-Oks loss is proposed. The loss function facilitates the training process by learning the distributional changes through Residual Log-likelihood Estimation. To assign different weights based on the importance of different keypoints in the human body, this study introduces a weight coefficient into the loss function. The experiments proved the efficiency of the proposed YOLO-Rlepose model. On the COCO dataset, the model outperforms the previous SOTA method by 2.11% in AP. Full article

The rapid evolution of 3D technology in recent years has brought about significant change in the field of agriculture, including precision livestock management. From 3D geometry information, the weight and characteristics of body parts of Korean cattle can be analyzed to improve cow growth. In this paper, a system of cameras is built to synchronously capture 3D data and then reconstruct a 3D mesh representation. In general, to reconstruct non-rigid objects, a system of cameras is synchronized and calibrated, and then the data of each camera are transformed to global coordinates. However, when reconstructing cattle in a real environment, difficulties including fences and the vibration of cameras can lead to the failure of the process of reconstruction. A new scheme is proposed that automatically removes environmental fences and noise. An optimization method is proposed that interweaves camera pose updates, and the distances between the camera pose and the initial camera position are added as part of the objective function. The difference between the camera’s point clouds to the mesh output is reduced from 7.5 mm to 5.5 mm. The experimental results showed that our scheme can automatically generate a high-quality mesh in a real environment. This scheme provides data that can be used for other research on Korean cattle. Full article

The rigid body displacement mathematical model is a Lie group of the special Euclidean group SE (3). This article is about the Lie algebra se (3) group. The standard exponential map from se (3) onto SE (3) is a natural parameterization of these displacements. In technical applications, a crucial problem is the vector minimal parameterization of manifold SE (3). This paper presents a unitary variant of a general class of such vector parameterizations. In recent years, dual algebra has become a comprehensive framework for analyzing and computing the characteristics of rigid-body movements and displacements. Based on higher-order fractional Cayley transforms for dual quaternions, higher-order Rodrigues dual vectors and multiple vectorial parameters (extended by rotational cases) were computed. For the rigid body movement description, a dual tangent operator (for any vectorial minimal parameterization) was computed. This paper presents a unitary method for the initial value problem of the dual kinematic equation. Full article

Addressing the problem that control methods of wheel-legged robots for future Mars exploration missions are too complex, a time-efficient control method based on velocity planning for a hexapod wheel-legged robot is proposed in this paper, which is named time-efficient control based on velocity planning (TeCVP). When the foot end or wheel at knee comes into contact with the ground, the desired velocity of the foot end or knee is transformed according to the velocity transformation of the rigid body from the desired velocity of the torso which is obtained by the deviation of torso position and posture. Furthermore, the torques of joints can be obtained by impedance control. When suspended, the leg is regarded as a system consisting of a virtual spring and a virtual damper to realize control of legs in the swing phase. In addition, leg sequences of switching motion between wheeled configuration and legged configuration are planned. According to a complexity analysis, velocity planning control has lower time complexity and less times of multiplication and addition compared with virtual model control. In addition, simulations show that velocity planning control can realize stable periodic gait motion, wheel-leg switching motion and wheeled motion and the operation time of velocity planning control is about 33.89% less than that of virtual model control, which promises a great prospect for velocity planning control in future planetary exploration missions. Full article

This paper proposes a new pose and focal length estimation method using two vanishing points and a known camera position. A vanishing point can determine the unit direction vector of the corresponding parallel lines in the camera frame, and as input, the unit direction vector of the corresponding parallel lines in the world frame is also known. Hence, the two units of direction vectors in camera and world frames, respectively, can be transformed into each other only through the rotation matrix that contains all the information of the camera pose. Then, two transformations can be obtained because there are two vanishing points. The two transformations of the unit direction vectors can be regarded as transformations of 3D points whose coordinates are the values of the corresponding unit direction vectors. The key point in this paper is that our problem with vanishing points is converted to rigid body transformation with 3D–3D point correspondences, which is the usual form in the PnP (perspective-n-point) problem. Additionally, this point simplifies our problem of pose estimation. In addition, in the camera frame, the camera position and two vanishing points can form two lines, respectively, and the angle between the two lines is equal to the angle between the corresponding two sets of parallel lines in the world frame. When using this geometric constraint, the focal length can be estimated quickly. The solutions of pose and focal length are both unique. The experiments show that our proposed method has good performances in numerical stability, noise sensitivity and computational speed with synthetic data and real scenarios and also has strong robustness to camera position noise. Full article

To better understand the horizontal well transient productivity in the bottom-water reservoir with finite water bodies, the horizontal well transient productivity model for the bottom-water reservoir with finite water-body multiple was developed using Green’s function and potential superposition method. Laplace transforms, Fourier transforms, superposition of point source, and Duhamel principle were used to obtain the transient productivity of the horizontal well, and the transient productivity of the horizontal well in real space was obtained by the Stehfest numerical inversion method. The typical pressure response curve and dimensionless productivity curves were plotted. The effects of the water-body multiple, the distance between the horizontal well and oil–water contact, and the skin factor, were analyzed. Six main flowing stages were divided for horizontal wells in the bottom-water reservoir with finite water bodies. When the water body multiples are zero or tend to infinity, the results obtained from the model are consistent with the calculations by the conventional top-bottom closed reservoir model or infinite rigid bottom-water reservoir model, respectively, and the pressure dynamic for the finite water body falls in between both. With the increase in the water body multiples and the decrease in distance between the horizontal well and the oil–water contact, and the horizontal well productivity decreases slowly. With the increase in the skin factor, the initial productivity decreases; moreover, the skin factor has a great influence on the initial productivity of the horizontal well, while the later influence gradually decreases. Accurate horizontal well productivity prediction in the bottom-water reservoir with finite water bodies provides a strong basis for horizontal well deployment, design optimization, and formulation of development policy. Full article

In this paper, the compact reducer which can be used as a rigid drive mechanism with a high-speed reduction ratio is systematically studied for kinematics and dynamics. The speed ratio is determined by the number of cam lobes and engaged rollers. The eccentric rotating conjugate lobe cam profile is synthesized by using the rigid body transformation method. To characterize the input torque based on Newton’s second law, the transmission forces of the resisting and driven multi-roller are proportional to the arm length of each actuating roller found by its geometric vector. In consideration of machining undercutting, roller limit load, and contact stresses, favorable designs can be achieved by adjusting the cam size, turret dimension, eccentricity, and roller size. Together with experimental tests, a prototype of the lobe cam reducer is made to verify the feasibility of the proposed design procedure and to investigate its kinematic and dynamic characteristics for speed reduction ratios, torques, and transmission efficiency. Full article