Control Vertices Research Articles

Augmented-reality based brain-computer interface of robot control

Brain Computer Interface (BCI) is a new approach to human-computer interaction. It can control the external devices directly with the brain without words and body movements. Brain-controlled robot is a major research area in the field of BCI, which organically integrates BCI with robotic systems to achieve safe and effective real-time control of robots using the user's electroencephalogram (EEG). Currently, there are two types of control methods for brain-controlled robots. One is direct control and the other is shared control. Direct brain control has its shortcomings, namely, low control efficiency and easy user fatigue. Shared control technique can effectively improve the control of brain-controlled robots and reduce the thinking ability of brain-controlled robots, thus making it the main control method of brain-controlled robots. The brain-computer collaborative control system based on augmented reality (AR) technology studied in this paper is a human-computer shared control method. In the experimental analysis of virtual reality (VR) systems and AR systems, this paper processes polylines through a series of control vertices with specific coordinates, using the relative distance measured between each point and the starting point as the relative coordinates, and calculates the operational errors of the two types of systems. In the system error of machining broken lines, when the relative coordinates are (10, 20), (40, 50), and (70, 80), the error values of the VR system are 0.17 mm, 0.36 mm, and 0.55 mm, respectively, while the error values of the AR system are 0.11 mm, 0.24 mm, and 0.41 mm, respectively. Therefore, the studies have illustrated the importance of AR systems for the study of brain-computer collaborative control of robots.

Interactive modelling of fair ship hulls with B-spline surfaces avoiding gaps and discontinuities

ABSTRACT Ship hull surfaces are commonly represented as parametric B-spline or NURBS 1 surfaces. The shape of a surface is controlled by a regular mesh of vertices with constant numbers of vertices in each parametric direction. This restriction complicates the modelling of complex features like bulbous bows, stern bulbs, transoms. Multiple surface patches may be used to overcome the limitations of a regular control mesh, but it is challenging to keep the patches properly aligned at the seams. This paper presents a systematic methodology to design fully featured ship hulls without any gaps, overlaps or tangent and curvature discontinuities. With proper layout of the control vertex mesh and exploitation of the geometrical properties inherent to the B-spline/NURBS definition, the resulting three-dimensional hull models are readily transferred to analysis and manufacturing systems.

Rational reparameterization of unstructured quadrilateral meshes for isogeometric analysis with optimal convergence

Unstructured quadrilateral meshes are widely used in representing surfaces of arbitrary topology. However, in connection with isogeometric analysis, unstructured meshes suffer from sub-optimal convergence rates in extraordinary regions, especially for solving higher-order PDEs (partial differential equations). In this work, a rational reparameterization method is proposed to achieve optimal convergence rates for isogeometric analysis using Catmull-Clark surfaces. The scheme lifts the convergence of analysis solutions by tuning the weights of control vertices of the input geometry in extraordinary regions, which are often neglected in constructing analysis-suitable parameterizations. Preferred tuning parameters with optimal convergence rates in L2-norm are determined statistically based on a test suite composed of typical testing solutions with a range of parameters. Numerical experiments confirm the validity of the proposed method for PDEs up to the fourth-order. Comparisons with the original Catmull-Clark scheme and a state-of-the-art tuned subdivision scheme also show the superiority of the proposed method in terms of both optimal convergence and reduced absolute errors of resulting analysis solutions.

A Surface Subdivision Scheme Based on Four‐Directional S13 Non‐Box Splines

AbstractIn this paper, we propose a novel surface subdivision scheme called non‐box subdivision, which is generalized from four‐directional S13 non‐box splines. The resulting subdivision surfaces achieve C1 continuity with the convex hull property. This scheme can be regarded as either a four‐directional subdivision or a special quadrilateral subdivision. When used as a quadrilateral subdivision, the proposed scheme can control the shape of the limit surface more flexibly than traditional schemes due to the natural introduction of auxiliary face control vertices.

The effect of pulse shape in theta-burst stimulation: Monophasic vs biphasic TMS

BackgroundIntermittent theta-burst stimulation (i) (TBS) is a transcranial magnetic stimulation (TMS) plasticity protocol. Conventionally, TBS is applied using biphasic pulses due to hardware limitations. However, monophasic pulses are hypothesised to recruit cortical neurons more selectively than biphasic pulses, predicting stronger plasticity effects. Monophasic and biphasic TBS can be generated using a custom-made pulse-width modulation-based TMS device (pTMS). ObjectiveUsing pTMS, we tested the hypothesis that monophasic iTBS would induce a stronger plasticity effect than biphasic, measured as induced increases in motor corticospinal excitability. MethodsIn a repeated-measures design, thirty healthy volunteers participated in three separate sessions, where monophasic and biphasic iTBS was applied to the primary motor cortex (M1 condition) or the vertex (control condition). Plasticity was quantified as increases in motor corticospinal excitability after versus before iTBS, by comparing peak-to-peak amplitudes of motor evoked potentials (MEP) measured at baseline and over 60 min after iTBS. ResultsBoth monophasic and biphasic M1 iTBS led to significant increases in MEP amplitude. As predicted, linear mixed effects (LME) models showed that the iTBS condition had a significant effect on the MEP amplitude (χ2 (1) = 27.615, p < 0.001) with monophasic iTBS leading to significantly stronger plasticity than biphasic iTBS (t (693) = 2.311, p = 0.021). Control vertex iTBS had no effect. ConclusionsIn this study, monophasic iTBS induced a stronger motor corticospinal excitability increase than biphasic within participants. This greater physiological effect suggests that monophasic iTBS may also have potential for greater functional impact, of interest for future fundamental and clinical applications of TBS.

An extended tuned subdivision scheme with optimal convergence for isogeometric analysis

This paper presents an extended tuned subdivision scheme for quadrilateral meshes that recovers optimal convergence rates in isogeometric analysis while preserving high-quality limit surfaces. Convergence rates can be improved for subdivision surfaces through proper mask tuning with a lower subdominant eigenvalue λ. However, such a tuning might affect the quality of limit surfaces if the tuning parameters are restricted to one-ring refined control vertices only. In this work, we further relax Catmull–Clark subdivision rules for 2-ring refined vertices with additional degrees of freedom in tuning masks with limit surfaces towards curvature continuity at extraordinary positions. Curvatures are bounded near extraordinary positions of valences N≤7, and a relaxation approach is proposed to suppress the local curvature variation for N≥8. We compare the proposed tuned subdivision scheme with several state-of-the-art schemes in terms of both surface qualities and applications in isogeometric analysis. Laplace–Beltrami equations with prescribed test solutions are adopted for verification of analysis results, and the proposed scheme recovers optimal convergence rates in the L2-norm with considerably lower absolute solution error than other schemes. As to surface quality, the proposed scheme has significant improvements compared with other schemes with optimal convergence rates for isogeometric analysis. The proposed scheme produces tighter curvature bounds with comparable reflection lines to the prevalent Catmull–Clark subdivision.

INTEGRAL PARAMETRIC SURFACE RECONSTRUCTION METHOD BASED ON DIFFERENTIAL MANIFOLD AND NON-UNIFORM RATIONAL B-SPLINE

A reconstruction method based on differential manifold and non-uniform rational B-spline is proposed to improve the reconstruction performance of massive point complex surface models. First, this method is simplified based on the Hausdorff distance of feature points. Second, in order to completely reconstruct the model and avoid the complex splicing of non-uniform rational B-spline, the regular domain of non-uniform rational B-spline is extended to differential manifolds, and the basis functions of the control vertices are established by using the shortest distance. Finally, the element decomposition of the differential manifold is calculated through the normalized basis functions, composite element decomposition, and control vertices to achieve the final surface model. The experiment results show that the proposed method has high reconstruction efficiency and accuracy for arbitrary topological surfaces.

Smooth Planning for Manipulator with Multi-dimensional Actuator based on Quintic B-spline

In order to solve the impact problem of uneven velocity during continuous operation for manipulator with multi-dimensional actuator, a smooth planning scheme based on Quintic B-spline algorithm was proposed. Firstly, the physical model of multi-dimensional actuator and its working principle were introduced. At the same time, the motion of the output axis vertex in space was decomposed into three steps, which can make the position relationship between the points more intuitive and convenient for our study. Secondly, the characteristics of Quintic B-spline algorithm were analysed. In this step, the B-spline interpolation function was defined at first, and the basis function of polynomial of degree p was defined according to the relevant information and its characteristics were indicated. Then, we analysed the node sequence parameters. For Quintic B-spline algorithm, when the position sequence of the rotor running track was given, three conditions must be satisfied to uniquely determine the corresponding B-spline function, namely: node vector, control vertex and the degree p of the B-spline curve. On this basis, the boundary constraints and control vertices were solved, which was a very important step. By solving the control vertices of Quintic B-spline curve, a smooth and continuous angular displacement curve can be obtained. The addition of four boundary conditions greatly increases the controllability of the system, making the rotor can start and stop in any way within the constraint conditions, and the connection of each interpolation point is smooth and continuous. The Quintic B-spline algorithm interpolation curve was obtained by simulation based on the time-position sequence of the actuator interpolation points. The results of the interpolation curve verified the effectiveness of the Quintic B-spline algorithm. In addition, three continuous running planning conditions were designed for the same interpolation sequence of the rotor to verify the controllability of the algorithm to the angular velocity and angular acceleration of the rotor during operation. The simulation results show that the Quintic B-spline algorithm has strong controllability for the angular velocity of actuator, and can effectively alleviate the soft impact of the system. Finally, a smooth planning experimental platform with multi-dimensional actuator was built. By setting the same trajectory and different interpolation points, the proposed Quintic B-spline algorithm was compared with the existing S-shaped curve planning algorithm based on the improvement. The results show that the proposed scheme has high control accuracy and strong impact mitigation performance, which can provide a reference for other multi-dimensional actuator trajectory planning.

Dynamic guidance virtual fixture for hydraulic manipulator via learning from demonstration

Operating heavy-duty hydraulic manipulators with a master-slave control system is very challenging to execute complex tasks in unstructured environments. In this paper, to improve the operational efficiency for performing repetitive tasks, we designed a dynamical guidance virtual fixture via learning from demonstration to assist the operation. A data fitting method is proposed by reconstituting the control vertexes to address the operation noises caused by response lag and oscillation tendency of hydraulic manipulators, such that a smooth nominal trajectory is obtained and used to generate the virtual fixture. Then, a pipe-constraint guidance virtual fixture is designed with multiple control modes to meet the demands of free and constraint motion. Comparative tests were carried out with a 3-DOF hydraulic manipulator to perform trajectory tracking tasks and movement within a limited space. Compared with no assistance, the results show that the average time of task completion can be reduced by over 50% with the proposed guidance virtual fixture. Besides, the mental pressure of the operator can be reduced since collision avoidance can be easily achieved.

Full-cross-section deformation characterization of Cu/Al bimetallic tubes under Rotary-Draw-Bending based on physics-driven B-spline curves fitting

It is difficult to detect the inner layer of the bimetallic tube and to describe its full-cross-section deformation, which negatively affects its verification and utility. To tackle this issue, a novel theory is proposed for fitting the full-cross-section deformation characterization of Cu/Al bimetallic tubes under Rotary-Draw-Bending. The cross-section profiles on the bending outside are fitted by the physics-driven B-spline curves. The geometric characteristics and the bending principles are set as the physics information and drive the design of the control vertices of the fitting B-curves. The interlaminar shape inheritance of the bimetallic tube is implemented by the same position angle of the corresponding control vertices. The cross-section profiles on the bending inside are fitted by the regular curves considering the elongation percentage. The comparison between the theoretical profiles and the experimental profiles shows remarkable agreement. The average circumferential errors of the theoretical profiles are within 1.82%, far smaller than the errors of the traditional ovalization profiles. Additionally, the representative parameters of full-cross-section deformation are differently affected by the wall-thickness. The wall-thinning of the outer layer and inner layer usually shows an opposite tendency when the wall-thickness varies.

Repetitive transcranial magnetic stimulation in the treatment of mild cognitive impairment due to cerebral small vessel disease

Introduction. Mild cognitive impairment (MCI) negatively affects patients quality of life and is a risk factor for dementia. One of the main causes of MCI is cerebral small vessel disease (CSVD). The previously established link between decreased activity in the supplementary motor area (SMA) and cognitive impairment in patients with CSVD makes it possible to consider repetitive transcranial magnetic stimulation (rTMS) of the SMA with functional magnetic resonance imaging (fMRI)-assisted positioning as a promising method for treating MCI caused by CSVD.&#x0D; The aim of the study was to evaluate the efficacy and tolerability of fMRI-guided rTMS of the SMA in patients with MCI caused by CSVD.&#x0D; Materials and methods. Twenty patients were randomly assigned to the intervention (SMA stimulation; n = 10) and the control (vertex stimulation; n = 10) groups. All patients underwent 10 sessions of high-frequency rTMS. The MoCA scale, trail making test, Tower of London test, and copying and delayed recall in the ReyOsterrieth complex figure test were used to assess treatment effect. Testing was conducted before, immediately after and 3 months post rTMS.&#x0D; Results. The intervention group demonstrated a significant improvement in the MoCA, the Tower of London test and delayed recall in the ReyOsterrieth complex figure test immediately after rTMS. Statistically significant improvement in the MoCA and the Tower of London test results was maintained after 3 months. No statistically significant improvements were found in the control group. Groups were comparable in the incidence of headache during and in the 24-hour period after the stimulation session, and in unpleasant sensations during the session.&#x0D; Conclusion. fMRI-guided rTMS of the SMA is an effective and promising treatment method for MCI caused by CSVD, with effects lasting three or more months, and good tolerability.

Disrupting Short-Term Memory Maintenance in Premotor Cortex Affects Serial Dependence in Visuomotor Integration.

Human behavior is biased by past experience. For example, when intercepting a moving target, the speed of previous targets will bias responses in future trials. Neural mechanisms underlying this so-called serial dependence are still under debate. Here, we tested the hypothesis that the previous trial leaves a neural trace in brain regions associated with encoding task-relevant information in visual and/or motor regions. We reasoned that injecting noise by means of transcranial magnetic stimulation (TMS) over premotor and visual areas would degrade such memory traces and hence reduce serial dependence. To test this hypothesis, we applied bursts of TMS pulses to right visual motion processing region hV5/MT+ and to left dorsal premotor cortex (PMd) during intertrial intervals of a coincident timing task performed by twenty healthy human participants (15 female). Without TMS, participants presented a bias toward the speed of the previous trial when intercepting moving targets. TMS over PMd decreased serial dependence in comparison to the control Vertex stimulation, whereas TMS applied over hV5/MT+ did not. In addition, TMS seems to have specifically affected the memory trace that leads to serial dependence, as we found no evidence that participants' behavior worsened after applying TMS. These results provide causal evidence that an implicit short-term memory mechanism in premotor cortex keeps information from one trial to the next, and that this information is blended with current trial information so that it biases behavior in a visuomotor integration task with moving objects.SIGNIFICANCE STATEMENT Human perception and action are biased by the recent past. The origin of such serial bias is still not fully understood, but a few components seem to be fundamental for its emergence: the brain needs to keep previous trial information in short-term memory and blend it with incoming information. Here, we present evidence that a premotor area has a potential role in storing previous trial information in short-term memory in a visuomotor task and that this information is responsible for biasing ongoing behavior. These results corroborate the perspective that areas associated with processing information of a stimulus or task also participate in maintaining that information in short-term memory even when this information is no longer relevant for current behavior.

Research on on-machine measurement of machining error based on T-spline surface reconstruction

The machining quality of the parts can be directly inspected and analyzed through contact on-machine measurement. However, during the measurement of free-form surfaces, aiming at the problem that the spline surface fitting method requires too many measuring points and the original design information is not borrowed during reconstruction, a T-spline surface reconstruction method based on the centroidal Voronoi tessellation (CVT) sampling strategy is proposed. In the uv parameter region of the original designed NUBRS surface, the Gaussian curvature of the surface is taken as the regional density function, and the CVT is generated by the Lloyd algorithm. Based on the T-grid constructed by an adaptive quadtree method, three kinds of surface feature points are defined as measuring points. By using constrained optimization theory and hierarchical T-mesh knowledge, the generation and local optimization of T-spline surface based on the reconstruction of the original NUBRS surface control points is realized. At last, the example of the surface machined by Makino V77 machine tool and measured with BLUM TC60 probe shows that, the method in this paper can effectively fit a surface which is more suitable for actual processing by adjusting a relatively small number of control vertices with a limited number of measurement points.

Development of 3D Models of Knits from Multi-Filament Ultra-Strong Yarns for Theoretical Modelling of Air Permeability

The work is devoted to the study of the geometric parameters of a knitted loop. It has been found that the optimal model is a loop model detailed at the yarn level, which considers the change in the cross-sectional shape and sets the properties of the porous material in accordance with the internal porosity of the yarn. A mathematical description of the coordinates of the characteristic points of the loop and an algorithm for calculating the coordinates of the control vertices of the second order spline, which determine the configuration of the yarn axes in the loop, are presented in this work. To create 3D models, Autodesk AutoCAD software and Structura 3D software, developed in the AutoLisp programming language, were used. The simulation of the air flow process was carried out in the Autodesk CFD Simulation environment. For the experimental investigation, plane knits from 44 tex × 3 linear density ultra-high molecular weight polyethylene yarns were produced, and their air permeability was tested according to Standard DSTU ISO 9237:2003. The results obtained during the laboratory experiment and simulation differed by less than 5%.

Trajectory optimization for manipulators based on external archives self-searching multi-objective particle swarm optimization

In order to improve the quality of the non-inferior solutions obtained by multi-objective particle swarm optimization (MOPSO), an improved algorithm called external archives self-searching multi-objective particle swarm optimization (EASS-MOPSO) was proposed and applied to a multi-objective trajectory optimization problem for manipulators. The position curves of joints were constructed by using quartic B-splines; the mathematical models of time, energy and jerk optimization objectives for manipulators were established; and the kinematic constraints of joints were transformed into the constraints of the control vertexes of the B-splines. A self-searching strategy of external archives to make non-inferior solutions have the ability to search the surrounding hyperspace was explored, and a diversity maintaining strategy of the external archives was proposed. The results of several test functions by simulation show that the convergence and diversity of the proposed algorithm are better than those of other 4 selected algorithms; the results of the trajectory optimization problem for manipulators by simulation show that the convergence, diversity and time consumption of the proposed algorithm are significantly better than those of non-dominated sorting genetic algorithm.

Discrete Data Points Fitting Based on Optimization of B-Spline Parameters Using Step-Acceleration Method

<p indent=0mm>When fitting discrete data points by iterative method, the parameterization of data points will affect the approximation effect and speed at the same time. A method of optimizing the parameters of control vertices and data points by iterative adjustment is proposed, which converges faster and fits the original data points better. Firstly, the initial control vertices are selected, and the adaptive BFGS method is used to optimize the control vertices and obtain the fitting curve. Secondly, the parameters corresponding to data points are optimized by the step-size acceleration method while the control vertices are kept unchanged. Finally, the new parameters are used to re-optimize the control vertices and a new fitting curve is obtained. Numerical examples show that the convergence speed in the early iteration stage of the given algorithm is faster than most existing iterative methods. Furthermore, the optimized curves are much closer to discrete data points and fitting error are much smaller.

Research on Surface Modeling of Turbo Vane of Vehicle Based on NURBS

In order to verify the induced inverse matrix equation for the control vertices of quartic NURBS curve and to improve the construction accuracy and fairness of complex twisted surface, this work constructed the bi-quartic NURBS surface of turbo vane of vehicle with NURBS technology in MATLAB. The bi-quartic NURBS vane of turbo was reconstructed in CATIA. The results were compared with the bi-cubic NURBS surface of vane in the same data, and the bi-cubic NURBS surface were constructed with the current inverse matrix equation for the control vertices of cubic NURBS curve. It shows that the constructed surface of vane with the generalized method of modeling of quartic NURBS surface has better accuracy and fairness through analyzing the error and fairness. The work provides the reference for the accurate modeling and the high-accuracy, high-efficiency NC machining of turbo vane in the engineering application.

Rapid wavelet construction of multi-resolution fairing for curves and surfaces with any number of control vertices

In the field of curves and surfaces fairing, arbitrary resolution wavelet fairing algorithm made wavelet fairing technology widely extended to general curves and surfaces, which are determined by any number of control vertices. Unfortunately, accurate wavelet construction algorithm for general curves and surfaces still has not been perfect now. In this article, a concrete algorithm for reconstruction matrix and wavelet construction was emphatically studied, which would be used in the multi-resolution fairing process for curves and surfaces with any number of control vertices. The essence of this algorithm is to generalize wavelet construction into the solution of null space, which could be solved gradually and rapidly by the procedures of decomposition and simplification of coefficient matrix. Certainly, the related compactly supported wavelets could be constructed efficiently and accurately, too. In the last of the article, a complex curve and a complex surface case were provided to verify the stability, high performance, and robustness of this algorithm.

Application of intelligent virtual reality technology in Clothing virtual wear and color saturation after COVID-19 epidemic situation

The COVID-19 epidemic has brought a huge impact to the clothing industry. Because of the inconveniences caused by countermeasures, clothing consumers can’t go to physical stores to try on, so it is urgent to develop a virtual clothing trial system. In addition, online fitting and online shopping gradually become the trend of clothing consumption. Based on virtual reality technology, this paper proposes a virtual clothing fitting system, and studies the color saturation in the process. In this paper, a method of parametric drawing of garment characteristic curve is proposed, and the shape of garment is designed by using control vertices. Based on this, this paper presents four forms of sutured parabola space and their control point solving algorithm. According to the principle of scale method, a three-dimensional coordinate transformation model of feature points is established. The model can calculate the coordinates of each characteristic value point of clothing according to the body shape information provided by customers and the empirical formula of different clothing styles, and then reverse calculate the curve control point. Furthermore, Bezier surface generation method is used to fit the control points. After the surface patches are spliced, the 3D rigid clothing model can be obtained. Experiments show that the method of personalized clothing modeling in this paper is efficient and accurate, which can be further extended to the observation system with larger degree of freedom.

Triangular Surface Patch Based on Bivariate Meyer-König-Zeller Operator

Abstract Based on the relationship between probability operators and curve/surface modeling, a new kind of surface modeling method is introduced in this paper. According to a kind of bivariate Meyer-König-Zeller operator, we study the corresponding basis functions called triangular Meyer-König-Zeller basis functions which are defined over a triangular domain. The main properties of the basis functions are studied, which guarantee that the basis functions are suitable for surface modeling. Then, the corresponding triangular surface patch called a triangular Meyer-König-Zeller surface patch is constructed. We prove that the new surface patch has the important properties of surface modeling, such as affine invariance, convex hull property and so on. Finally, based on given control vertices, whose number is finite, a truncated triangular Meyer-König-Zeller surface and a redistributed triangular Meyer-König-Zeller surface are constructed and studied.