Polynomial Surface Research Articles

Novel Soft Gripper With Adjustable Performance Based on Blade Flexures

Abstract The design of soft grippers is challenging as the target objects to be handled involve a wide variety of sizes, shapes, and softness. Most grippers reported present drawbacks, e.g., complex control strategies for stiffness and force variation, inadequate adaptability to target shape variability, and complicated adaptation to manipulators, which in turn limit their implementation in applications such as harvesting. This paper presents a novel overlay soft gripper based on an assembling mechanism and passive soft structures, enabling the modification of grip size, orientation, and gripping force. This gripper can be assembled over a commercial robot-gripper taking the closing motion of this as the input to perform its closing motion. Input and output parameters are related by means of the displacement transmission mechanism which converts the closing motion of the robot-gripper into the closing motion of the overlay soft gripper. The gripping force can be modified through the change of stiffness, via adjustment of effective length using contact elements, of internal blade flexures. The displacement transmission mechanism works in two modes: as rigid-body mechanism without the contact elements and as rigid-body/flexible mechanism with the contact elements. The relationships between input and output parameters are obtained analytically for the case of rigid-body mechanism, and through finite element analysis simulations for the case of rigid-body/flexible mechanism. Relationships between input and output parameters are approximated with polynomial surfaces. Finally, physical prototypes are manufactured and assembled on their respective robot-grippers to qualitatively demonstrate their performance.

Effect of healthy dietary intention-behavior (in)consistency on depression and anxiety in the process of behavior change.

Although an increasing number of people are now committed to pursuing a healthy diet, it remains unclear how mental health changes during this process. The present study aimed to examine the combined effect of healthy dietary intention and behavior on depression and anxiety across two sub-studies. This study consisted of two parts: a cross-sectional survey (Study 1) involving 1,433 college students and an 11-day daily diary study (Study 2) with 117 college students. Polynomial regression and response surface analysis indicated that in cases of congruence, individuals' intention and behavior align at a high level and were associated with lower levels of depression and anxiety in the motivational phase but were not found similar association in the volitional phase. In cases of incongruence, individuals with high intention-low behavior tend to experience lower levels of depression and anxiety in the motivational phase. However, individuals with high intention-low behavior tend to experience higherlevels of depression and anxiety in the volitional phase. These findings not only enrich the current understanding of diet and health but also contribute to the development of holistic strategies for promoting a healthy diet.

Optimization of user-side electrolytic hydrogen production system considering electrolyzer efficiency degradation

This paper proposes an optimized operational strategy for user-side proton exchange membrane (PEM) electrolyzer hydrogen production systems, considering the degradation of hydrogen production efficiency over time. The work is divided into three parts. First, a combined hydrogen production efficiency model based on operational data is established, using polynomial surface fitting (PSF) and gaussian process regression (GPR) to model the electrolyzer's efficiency from two perspectives: operational time and input power. Second, an optimization model for the operational strategy of the user-side electrolytic hydrogen production system is constructed, aiming to enhance overall system efficiency by adjusting the electrolyzer's input power. Finally, the hydrogen efficiency model from the first part is applied to the optimization strategy in the second part for empirical analysis. The results show that the optimized strategy, which accounts for the degradation of hydrogen production efficiency, significantly improves system performance, validating the method's effectiveness and practicality. This study provides theoretical support and practical guidance for the efficient operation of user-side electrolyzers, contributing to the promotion and application of green hydrogen technologies.

Comparative Study on the Interest in Non-Uniform Rational B-Splines Representation versus Polynomial Surface Description in a Freeform Three-Mirror Anastigmat

Novel freeform optical design methods can be classified in two categories, depending on whether they focus on the generation of a starting point or the development of new optimization tools. In this paper, we design a freeform three-mirror anastigmat (TMA) and compare different surface representations using either a differential ray tracer as a new optimization tool or a commercial ray tracer (ANSYS-ZEMAX OpticStudio). For differential ray tracing, we used FORMIDABLE (Freeform Optics Raytracer with Manufacturable Imaging Design cApaBiLitiEs), an optical design library with differential ray tracing and Non-Uniform Rational B-Splines (NURBS) optimization capabilities, available under the European Software Community License (ESCL). NURBS allow a freeform surface to be represented without needing any prior knowledge of the surface, such as the polynomial degree in polynomial descriptions. OpticStudio and other commercial optical design software are designed to optimize polynomial surfaces but are not well-suited to optimize NURBS surfaces, requiring a custom optical design library. In order to demonstrate the interest in using NURBS representation, we designed and independently optimized two freeform telescopes over different iteration cycles; with NURBS using FORMIDABLE or with XY polynomials using OpticStudio. We then compared the resulting systems using their root mean square field maps to assess the optimization quality of each surface representation. We also provided a full-system comparison, including mirror freeform departures. This study shows that NURBS can be a relevant alternative to XY polynomials for the freeform optimization of reflective three-mirror telescopes as it achieves more a uniform imaging quality in the field of view.

Optical design of a 5× zoom afocal telescope with deformable mirrors

All-reflective zoom afocal telescopes can be integrated with existing imaging systems as foreoptics, enabling flexible imaging with adjustable resolution. This paper proposes an approach to designing a 5× zoom afocal telescope using deformable mirrors. Based on matrix optics, the first-order parameters for a coaxial reflective 5× zoom afocal telescope with a fixed primary mirror and three deformable mirrors are determined. To prevent obscuration, the mirrors are tilted at their vertices, which introduces asymmetric aberrations. To correct these aberrations, XY polynomial surfaces are employed on the primary mirror and an additional flat fold mirror. The final design and image simulations indicate that the system achieves good image quality across all zoom positions, enabling 5× zoom imaging with a maximum root mean square wavefront error of less than 0.125λ (λ = 632.8 nm), thereby validating the efficacy of the proposed design methodology.

Data-Driven Radial Compressor Design Space Mapping

Abstract Estimates of turbomachinery performance trends inform system-level compromises during preliminary design. Existing empirical correlations for efficiency use limited experimental data, while analytical loss models require calibration to yield predictive results. From a set of 3708 radial compressor computations, this paper maps efficiency as a function of mean-line aerodynamics, and determines the governing loss mechanisms. An open-source turbomachinery design code creates annulus and blade geometry, then runs a Reynolds-averaged Navier–Stokes simulation for compressors sampled from the mean-line design space. Polynomial surface fits yield a continuous eight-dimensional representation of the design space for analysis, predicting efficiency with a root-mean-square error of 1.2% points. The results show a balance between surface dissipation in boundary layers and mixing loss due to casing separations sets optimum values for inlet Mach number, hub-to-tip ratio, de Haller number, and backsweep angle. Surface dissipation drives the effect of flow coefficient, with high surface areas at low values, and high velocities at high values. Compact compressor designs are achieved by increasing inlet Mach number, reducing hub-to-tip ratio, and minimizing the radial loading coefficient—all of which reduce efficiency approaching design space boundaries. An interactive web-based tool makes the results available to practising engineers, demonstrating large ensembles of automated designs and simulations as a higher-fidelity replacement for legacy empirical correlations in preliminary design.

Unveiling sequential layered heterogeneity in multi-spectral transmission images clustering through iterative terrace compression with adaptive neighborhoods analysis

Multi-spectral transmission imaging looks forward to an early breast cancer screening with cost-effectiveness, safety, and ease of use. However, the biological tissue of the breast owns scattering and strong absorption properties, resulting in transmission images with a low signal-to-noise ratio and prior investigation focused on detection heterogeneity within a single layer, but the different depths in heterogeneity due to the spherical shape of the breast causing the challenges. Accurately detecting heterogeneity in different layers is crucial due to low contrast, veiling layers, and unclear boundaries, which can be difficult to identify in clustering and segmentation. The breast heterogeneity identification can be handled by combining image processing techniques; nevertheless, considering labeling limits and data accessibility, the clustering algorithm provides an acceptable substitute. Therefore, the paper proposes a novel methodology integrating the iterative terrace compression method with adaptive neighborhoods analysis to identify sequential multi-layered heterogeneity and enhance the clustering of multi-spectral transmission images. Our experimental setup involved the collection of low grayscale images across six wavelengths, followed by advanced image processing techniques, including frame accumulation to improve image signal-to-noise ratio and then polynomial surface fitting to eliminate trend items from uneven light. After that, iterative terrace compression with adaptive neighborhoods analysis is applied to reduce redundancy and unveil heterogeneity in different layers and window functions to remove unnecessary gray information. Finally, clustering combined with pseudo-color is used for clustering analysis and visual representation for aiding in heterogeneity detection. Results indicate a significant improvement in detection metrics, with our method outpacing existing techniques regarding the Dice coefficient, F1 score, and Jaccard. This innovative approach not only enhances the characterization of breast tissue heterogeneities in different layers but also promises practical clinical applications in breast cancer screening.

Investigating Different Interpolation Methods for High-Accuracy VTEC Analysis in Ionospheric Research

The dynamic structure of the ionosphere and its changes play an important role in comprehending the natural cycle by linking earth sciences and space sciences. Ionosphere research includes a variety of fields like meteorology, radio wave reflection from the atmosphere, atmospheric anomaly detection, the impact on GNSS (Global Navigation Satellite Systems) signals, the exploration of earthquake precursors, and the formation of the northern lights. To gain further insight into this layer and to monitor variations in the total electron content (TEC), ionospheric maps are created using a variety of data sources, including satellite sensors, GNSS data, and ionosonde data. In these maps, data deficiencies are addressed by using interpolation methods. The objective of this study was to obtain high-accuracy VTEC (Vertical Total Electron Content) information to analyze TEC anomalies as precursors to earthquakes. We propose an innovative approach: employing alternative mathematical surfaces for VTEC calculations, leading to enhanced change analytical interpretation for anomaly detections. Within the scope of the application, the second-degree polynomial method, kriging (point and block model), the radial basis multiquadric, and the thin plate spline (TPS) methods were implemented as interpolation methods. During a 49-day period, the TEC values were computed at three different IGS stations, generating 1176 hourly grids for each interpolation model. As reference data, the ionospheric maps produced by the CODE (Center for Orbit Determination in Europe) Analysis Center were used. This study’s findings showed that, based on statistical values, the TPS model offered more accurate results than other methods. Additionally, it has been observed that the peak values in TEC calculations based on polynomial surfaces are eliminated in TPSs.

Oceanic Mesoscale Eddy Fitting Using Legendre Polynomial Surface Fitting Model Based on Along-Track Sea Level Anomaly Data

Exploring the spatial distribution of sea surface height involves two primary methodologies: utilizing gridded reanalysis data post-secondary processing or conducting direct fitting along-track data. While processing gridded reanalysis data may entail information loss, existing direct fitting methods have limitations. Therefore, there is a pressing need for novel direct fitting approaches to enhance efficiency and accuracy in sea surface height fitting. This study demonstrates the viability of Legendre polynomial surface fitting, benchmarked against bicubic quasi-uniform B-spline surface fitting, which has been proven to be a well-established direct fitting method. Despite slightly superior accuracy exhibited by bicubic quasi-uniform B-spline surface fitting under identical order combinations, Legendre polynomial surface fitting offers a simpler structure and enhanced controllability. However, it is pertinent to note that significant expansion of the spatial scope of fitting often results in decreased fitting efficacy. To address this, the current research achieves the precise fitting of sea surface height across expansive spatial ranges through a regional stitching methodology.

The effect of leader-team (in-)congruence in future orientation on leader’s participative leadership: the moderating role of leader workload

Purpose Prior studies have consistently treated participative leadership as a given leadership style. Conversely, this study aims to prove that participative leadership can be predicted by leaders and teams collectively, depending on leaders' work characteristics (i.e. workload). Design/methodology/approach A two-source survey was designed to collect data from a sample of 89 leader-team dyads in a trading company in a southeastern Chinese city. Polynomial regression and response surface analysis were used to test the hypotheses. Findings The leader showed more participative leadership when leader-team future orientation was congruent rather than incongruent; in the congruent situation, there was an inverted U-shaped relationship between leader-team future orientation congruence and participative leadership; in the incongruent situation, when the team's future orientation gradually exceeded the leader's, participative leadership first increased and then decreased; and leader workload positively moderated the relationship between leader-team future orientation congruence and participative leadership. Originality/value These findings theoretically respond to the call for investigating the influence of leader-team future orientation congruence on leaders’ behaviors, and in practice enlighten managers on how to encourage supervisors to involve employees in decision-making processes.

The mediating effect of bullying on parental–peer support matching and NSSI behaviour among adolescents

BackgroundBeing subjected to bullying is a significant risk factor for non-suicidal self-injury (NSSI) among adolescents. Parental support, peer support, and social connectedness play protective roles in mitigating NSSI in this population. However, the precise impact of the combined effects of parental and peer support on bullying and NSSI requires further investigation.MethodsThis study employed the Child and Adolescent Social Support Scale, Delaware Bullying Victimisation Scale, Social Connectedness Scale, and the Ottawa Self-Injury Inventory to survey 1277 Chinese adolescents. Polynomial regression analysis and response surface analysis were applied to examine the mediating role of bullying and social connectedness in the relationship between parental and peer support matching and NSSI.ResultsThe results indicate that parental support (r = 0.287, P < 0.001), peer support (r = 0.288, P < 0.001), and social connectedness (r = 0.401, P < 0.001) were protective factors against NSSI in adolescents. Conversely, bullying (r = 0.425, P < 0.001) acts as a risk factor for NSSI in this population. Adolescents with low parental and peer support experienced more bullying than those with high parental and peer support, while those with low parental but high peer support experienced less bullying than those with high parental but low peer support (R^2 = 0.1371, P < 0.001). Social connectedness moderated the effect between bullying and NSSI in this model (β = 0.006, P < 0.001).LimitationsDue to the under-representation of participants and lack of longitudinal data support, the explanatory power of causality between variables was limited. Future studies should include national samples and incorporate longitudinal studies to enhance the generalisability and robustness of the findings.ConclusionThis study reveals the influence mechanism of parental and peer support matching experienced by adolescents on bullying and NSSI and the moderating role of social connectedness. These findings enrich the developmental theory of adolescent NSSI and provide reference for the prevention and intervention of adolescent NSSI behaviour.

Social support and family resilience among Chinese people receiving maintenance hemodialysis: A polynomial regression and response surface analysis explaining psychological resilience.

Psychological resilience plays an important role in overcoming emotional distress among people receiving maintenance hemodialysis (MHD). This study aimed to investigate how social support and family resilience interact to influence psychological resilience among Chinese people receiving MHD. This was a prospective longitudinal study with three time points: baseline (T1), 3 months (T2), and 6 months (T3) later. A convenience sample of 252 participants (67.1% male; 57.6 ± 13.8 years of age) from Zhejiang Province, China, who completed baseline measures of social support, family resilience, and psychological resilience, were further assessed for psychological resilience at T2 and T3. Polynomial regression (PR) and response surface analysis (RSA) were used to analyze the data. At all time points, and in the case of agreement between social support and family resilience, the combined effect of both variables manifested as a positive linear association with psychological resilience. Instead, at baseline, and in case of disagreement, the same combined effect manifested as a negative linear relationship related to psychological resilience. The findings highlighted the importance of considering the conjoint influence of social support and family resilience when developing interventions to improve the psychological resilience of people receiving MHD.

The Association between Discrepancies in Parental Emotional Expressivity, Adolescent Loneliness and Depression: A Multi-Informant Study Using Response Surface Analysis.

Incongruent perceptions of parental emotional expressivity between parents and adolescents may signify relational challenges, potentially impacting adolescents' socioemotional adjustment. Direct evidence is still lacking and father-adolescent discrepancies are overlooked. This study employed a multi-informant design to investigate whether both mother-adolescent and father-adolescent discrepancies in perceptions of parental expressivity are related to adolescents' mental well-being, specifically focusing on loneliness and depression. Analyzing data from 681 families (mean age of adolescents = 15.5 years old, 51.2% girls, 40% only-children) in China revealed that adolescents tended to perceive paternal and maternal emotional expressivity more negatively than their parents, particularly fathers. Polynomial regression and response surface analysis showed significant links between parent-adolescent congruence and incongruence and adolescent loneliness. (In)Congruence between adolescents and mothers or fathers predicted later adolescent depression, mediated by adolescent loneliness and varied by the dimension of emotional expressivity. These findings provide insights into the roles of mothers' and fathers' emotional expressivity in shaping children's mental well-being during adolescence.

Enhancing OpenEP: atrial conduction velocity and conduction velocity heterogeneity quantification through EP Workbench

Abstract Background Alterations in atrial conduction velocity have been implicated in the pathogenesis of atrial arrhythmias, with conduction velocity thought to be slower and more heterogeneous in areas promoting atrial fibrillation. However, clinical studies of conduction velocity are challenging since there are no available platforms that provide researchers and clinicians with the ability to quantify conduction velocity and analyse conduction heterogeneity from electroanatomic mapping data. Purpose In this paper we sought to address these limitations by enhancing the OpenEP Python library by (1) automating calculations using previously-published conduction velocity estimation algorithms; (2) providing an interactive graphical representing of conduction velocity and conduction heterogeneity and (3) implementing a histogram analysis tool to quantify conduction velocity and enable the identification of slow conduction regions. Method Two well-known and previously published methods for calculating cardiac conduction velocity, Triangulation and polynomial surface fitting, were implemented. Conduction velocity estimation was improved further by excluding regions with wave collisions and focal discharges. These regions were identified using the divergence of conduction velocity vector fields, with positive divergence representing focal sources and negative divergence representing areas of collision. Finally, calculated conduction velocities using electrogram data were interpolated over the surface mesh via Radial Basis Function (RBF) interpolation method. All algorithms were implemented in the OpenEP Python library (openep-py), with visualisation tools provided in the complementary graphical interface, EP Workbench. Results An extensible "Analysis" feature was created in openep-py, to provide conduction velocity and divergence calculations which are fully customisable through the graphical interface based on user preferences. The EP Workbench desktop application displays resulting cardiac surface maps to depict calculated conduction velocity and divergence fields, together with conventional activation and voltage maps (Figure 1). The histogram analysis tool can be used to identify regions of slow conduction velocity from electroanatomic mapping data. Using a threshold of &amp;lt;0.3m/s, two slow conducting channels are visualised on the posterior wall of a test case (Figure 2). The tool is not specific to conduction velocity and may also be used to quantify other data types in EP Workbench. Finally, computed conduction velocity and divergence values and surface maps are stored in the standard OpenEP data structure, allowing further analysis following data export. Conclusion We have extended OpenEP to provide a comprehensive set of tools for conduction velocity calculation and analysis which will facilitate investigation of the structural and functional basis of conduction velocity alterations in disease states.

How does response to work communication impact employees’ collaborative performance? A view of the social connectivity paradox

Contemporary digital work practices increasingly necessitate prompt responses by employees to work-related communication. The impact of employees’ response behavior to work communication (RBWC) on collaborative performance remains underexplored. To address this gap, we propose a theoretical model integrating the theories of person-environment fit, social support, and conservation of resources. RBWC is conceptualized as the degree of communication response (in)congruence, representing the (mis)fit between rapid response expectations and the employee's ability to respond rapidly. We investigate the diverse effects of various states of response congruence on collaborative performance, mediated by the social connectivity paradox manifested as social support and social overload, while grounding this work on social support theory. The results from surveying 268 professionals and employing polynomial regression and surface response analysis demonstrate that different response congruence states significantly influence the social connectivity paradox and subsequently impact collaborative performance. Social support mediates the relationship between response congruence and collaborative performance, while social overload mediates the linear association between response ability and collaborative performance. Theoretical and practical implications are discussed.

Interplay of Adolescents' and Parents' Mindsets of Socioeconomic Status on Adolescents' Stress-Related Outcomes.

The reciprocity and variation of values and beliefs are dynamic features of the parent-child relationship. Parents and adolescents may hold congruent or incongruent views regarding the malleability of socioeconomic status (mindset of SES), potentially influencing adolescents' psychological and physiological stress outcomes, as reflected in stress perceptions and the hypothalamic-pituitary-adrenal (HPA) axis functioning. The current study investigated how patterns of parent-adolescent congruence and incongruence in mindset of SES were associated with adolescents' perceived stress and diurnal cortisol patterns four months later. A total of 253 adolescents (Mage = 12.60, 46.2% girls) and their parents (Mage = 40.09 years, 59.5% mothers) participated in this study. Polynomial regression analyses and response surface analyses showed that adolescents perceived lower levels of stress when they themselves or their parents reported a stronger growth mindset of SES. Additionally, adolescents with a stronger growth mindset of SES also exhibited a steeper diurnal cortisol slope. Moreover, parents' mindset significantly interacted with adolescents' mindset to influence adolescents' diurnal cortisol patterns such that when adolescents hold weaker growth mindset of SES, those with higher parental growth mindsets had significantly higher cortisol awakening response and steeper diurnal cortisol slope. Furthermore, adolescents who showed incongruence with their parents but had averagely stronger growth mindsets of SES reported a significantly steeper diurnal cortisol slope than those who had averagely weaker growth mindsets with their parents. The findings point to the beneficial impacts of the growth mindset of SES on stress-related outcomes among adolescents, as well as the significance of considering both parents' and adolescents' mindsets when exploring these associations.

Quadratic surface preserving parameterization of unorganized point data

Finding parameterizations of spatial point data is a fundamental step for surface reconstruction in Computer Aided Geometric Design. Especially the case of unstructured point clouds is challenging and not widely studied. In this work, we show how to parameterize a point cloud by using barycentric coordinates in the parameter domain, with the aim of reproducing the parameterizations provided by quadratic triangular Bézier surfaces. To this end, we train an artificial neural network that predicts suitable barycentric parameters for a fixed number of data points. In a subsequent step we improve the parameterization using non-linear optimization methods. We then use a number of local parameterizations to obtain a global parameterization using a new overdetermined barycentric parameterization approach. We study the behavior of our method numerically in the zero-residual case (i.e., data sampled from quadratic polynomial surfaces) and in the non-zero residual case and observe an improvement of the accuracy in comparison to standard methods. We also compare different approaches for non-linear surface fitting such as tangent distance minimization, squared distance minimization and the Levenberg Marquardt algorithm.

Members' goal orientation and working alliance in group therapy: A response surface analysis.

Research suggests that a client's achievement goal orientation and alliance are important for positive treatment outcomes. However, it is currently unknown how a member's goal orientation and alliance in tandem relate to members' improvement in group therapy, despite conceptual wisdom regarding the additive effect of a high alliance and a mastery or approach goal orientation. Therefore, this study sought to examine the congruence between members' goal orientation and the member-group alliance on members' perceived improvement in group therapy. Data for this study came from 99 clients across 10 interpersonal process groups. Polynomial regression and response surface analysis were used to test the congruent and discrepant effects of members' goal orientation (i.e., approach-performance, avoidance-performance, and mastery orientation) and group alliance on their perceived improvement in group therapy. As hypothesized, members who reported congruent high group alliance and high mastery orientation or approach orientation compared to congruent low alliance and low mastery or approach orientation reported high levels of improvement in group therapy. Regarding discrepant effects, discrepant high alliance and low avoidance orientation compared to low alliance and high avoidance was positively related to improvement in group therapy, and discrepant high alliance and low approach orientation compared to low alliance and high approach was positively related to improvement in group therapy. Last, discrepant high alliance and low mastery and low alliance and high mastery were positively related to improvement in group therapy, suggesting a compensatory effect between mastery orientation and alliance on improvement. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Simple modulation of Lissajous MEMS laser beam scanning with reconfigurable structured light patterns for 3D imaging

Structured light 3D imaging systems commonly employ panel-based projectors or 1-axis MEMS mirrors with beam expander lens to project multi-frame barcodes or dot clouds, addressing challenges posed by objects with multi-scale feature sizes. However, these methods often result in large system volumes due to the required projection multi-lens modules, high hardware costs, or limited light pattern generation capabilities that hindering measurement precision enhancement. This paper introduces an innovative approach to reconfigurable spatial light pattern projection using a single bi-axial MEMS mirror with Lissajous scanning. In contrast to the pixel-by-pixel pre-defined image patterns encoding of conventional 2D laser beam scanning, the proposed method simply aligns the MEMS bi-axial resonance frequencies with laser pulse modulation, enabling the projection of diverse structured light patterns such as stripes, lines, dot matrices, and random dot clouds, which can adapt to different 3D imaging algorithms demands. It eliminates the need for multi-frame encoding and streamlines data caching, simplifies digital logic hardware. A prototype 3D imaging system was developed to demonstrate the mathematical model for laser modulation and the technical feasibility based on the proposed principle. Beyond its lens-free essence, the system supports focal-free optics and a compact projection form factor, which accommodates to a broad range of projection distances and field-of-views based on object’s location. 3D depth map of polynomial surface and blocks objects are extracted through single-frame pattern projection with a relative high accuracy. The presented modulation theory for diverse structured light pattern generation opens avenues for versatile and compact 3D imaging applications of LiDAR and robotic 3D vision.

Geometric calibration of the linear-array whiskbroom optical satellites based on look-angle corrections

Linear-array whiskbroom optical satellites are equipped with scanning mirrors and compensation mirrors. They rotate and scan imaging with the satellite flight orbit as the rotation axis, and geometrically splice the scanned images along the orbit, achieving a balance between large width and high resolution of remote sensing images. The addition of scanning mirrors and compensation mirrors necessitates multiple reflections for the imaging ray to reach the focal plane. Hence, the calibration of the geometric aspects for linear-array whiskbroom optical satellites will be an intricate procedure. A geometric calibration model based on look-angle corrections is established according to the imaging characteristics of linear-array whiskbroom optical satellites. All errors are corrected using correction quantities, and cubic polynomial surfaces are used to fit correction quantities. The proposed geometric calibration method based on the look-angle corrections has a sensor positioning precision of better than 1.0 pixels for the calibrated image.