104 results about "Ellipsoid" patented technology

The invention discloses a volume cloud rendering method and system based on three-dimensional Gaussian splash, and the method comprises the steps: carrying out the feature matching and structure reconstruction of a volume cloud image through an SfM algorithm, obtaining a sparse point cloud in a scene, and representing the sparse point cloud as an anisotropic Gaussian ellipsoid; decomposing the illumination transmission process of the volume cloud into two parts of forward single scattering and internal multiple scattering based on a radiation transmission equation to obtain an illumination modeling formula embedded volume cloud rendering process; determining the contribution of each three-dimensional Gaussian ellipsoid to a rendering result according to the opacity index of the three-dimensional Gaussian ellipsoid, and dynamically cutting the low-contribution three-dimensional Gaussian ellipsoid by adopting a delay deletion strategy to reduce redundancy; a comprehensive loss function is constructed, so that the three-dimensional Gaussian model is focused on the volume cloud region and the structure detail reduction capability is enhanced; and outputting the optimized volume cloud rendering result and the three-dimensional Gaussian model. According to the method, the volume cloud rendering efficiency and quality are effectively improved on the premise of ensuring real-time rendering.

The invention discloses a three-dimensional scene reconstruction method and system based on monocular depth estimation, and belongs to the technical field of computer vision and three-dimensional reconstruction, and the method comprises the steps: carrying out the multi-scale feature coding of a monocular RGB image through a mixed attention depth coding module, and obtaining the hierarchical depth feature representation; carrying out autoregression depth decoding through a self-adaptive edge perception depth decoding module to generate an initial depth map; a depth confidence map is calculated through a geometric consistency constraint optimization module and is fed back to a coding module for iterative optimization, and a refined depth map is output; and three-dimensional Gaussian ellipsoid scene representation is constructed through the Gaussian ellipsoid scene reconstruction module. According to the invention, high-precision depth estimation and high-quality three-dimensional reconstruction are realized by constructing a depth-coupled closed-loop cooperative system.

Provided in the present invention is a reconstruction and driving method based on a multi-view motion video of a clothed human body. The method comprises: using a two-layer three-dimensional Gaussian representation to model a human body and corresponding clothes; defining geometric attributes of three-dimensional Gaussian ellipsoids for any face on coarse three-dimensional meshes of the human body and the clothes; at a reconstruction stage, transforming coarse triangular meshes of the clothes and the body from a canonical space to an observation space, and updating Gaussian geometric attributes; and on the basis of a camera pose and parameters of an input video, rasterizing a three-dimensional Gaussian representation of the observation space to an image space, and rendering a picture on the basis of a Gaussian splatting formula. Self-supervised training can be performed on a model by means of calculating the color difference between a rendered picture and a real picture and using same as an optimization objective; when reconstruction is completed and driving is performed, a geometric result of a current frame is used to calculate the position of the coarse triangular mesh of the clothes in the next frame; and the reconstruction-stage method and related parameters are used to render a driving picture in a new posture.

The invention discloses a degradation scene-oriented multi-residual fusion laser radar positioning method, which comprises the following steps of: firstly, performing state prediction by adopting an iterative extended Kalman filtering framework and an IMU (Inertial Measurement Unit), and constructing three complementary observation models of a global map matching residual, a local point-to-plane geometry residual and a luminosity residual; secondly, designing a degradation sensing mechanism based on a covariance ellipsoid, representing absolute and relative degradation degrees through a condition number and an information entropy respectively, realizing quantitative evaluation of system observability, and dynamically adjusting fusion weights of observation residuals; meanwhile, a self-adaptive weight strategy based on luminosity Jacobi intensity is introduced; and finally, performing anomaly detection through deviation comparison between the IMU predicted pose and the IEKF estimated pose, inhibiting pose jump, and ensuring continuity of a positioning time sequence. The method effectively overcomes the challenges of geometric constraint deficiency, positioning drift accumulation and the like of the LiDAR positioning system in the geometric degradation environment, does not need to adjust parameters for a specific scene, and improves the precision, robustness and real-time performance of global positioning in the degradation environment.

The embodiment of the invention provides an underwater scene three-dimensional reconstruction method based on three-dimensional Gaussian sputtering and related equipment, and belongs to the technical field of computer vision. The method comprises the following steps: performing feature point analysis on each real two-dimensional image to obtain a sparse point cloud set; a three-dimensional Gaussian ellipsoid of each point cloud in the sparse point cloud set is initialized to represent a three-dimensional underwater scene, and the three-dimensional Gaussian ellipsoid is used for representing Gaussian distribution of the position, the covariance matrix, the color and the opacity of the point cloud; selecting a plurality of three-dimensional Gaussian ellipsoids located in a corresponding camera view cone based on the target camera pose, and performing two-dimensional projection rendering according to the plurality of selected three-dimensional Gaussian ellipsoids to obtain a rendered two-dimensional image; and updating the three-dimensional Gaussian ellipsoids in the point cloud space according to the rendered two-dimensional image and the real two-dimensional image with the same target camera pose to obtain a plurality of three-dimensional Gaussian ellipsoids accurately representing the underwater scene. According to the invention, the accuracy and efficiency of underwater scene three-dimensional reconstruction can be improved.

The invention discloses an unmanned aerial vehicle autonomous flight control method and a related device. The method comprises the steps of obtaining environment map information and unmanned aerial vehicle information; based on the environmental map information and the unmanned aerial vehicle information, obtaining a global optimal path by using a fusion dynamic exploration path planning algorithm; taking each path section in the global optimal path as a center to generate a plurality of ellipsoid areas covering the path sections, converting the boundary of each ellipsoid area into a convex polyhedron formed by a plurality of hyperplanes, and connecting the convex polyhedrons in series according to the sequence of the path sections to obtain a safe flight corridor; in the trajectory optimization process, the safe flight corridor is used as a constraint basis of space feasibility, it is ensured that the trajectory is always located in the safe flight corridor, and space constraints are determined; and carrying out trajectory tracking by adopting a DLQR controller based on the spatial constraint. According to the invention, efficient cooperation of path planning and trajectory tracking is realized.

The invention relates to the technical field of computer vision and robot positioning, and discloses a dynamic 3DGS-SLAM method and system based on Gaussian pyramid and adaptive densification. The method comprises the following steps: generating a semantic mask through real-time dynamic target detection so as to distinguish a static background from a dynamic object; constructing a 3D Gaussian map model of the scene; rendering images in parallel on a full-resolution view and a down-sampling resolution view by adopting a motion perception Gaussian pyramid rendering method, and fusing rendering results by utilizing a dynamic mask so as to eliminate motion edge artifacts; a self-adaptive densification strategy based on a monotonic attenuation function is adopted, the initialization radius of the Gaussian ellipsoid is dynamically adjusted based on the training progress, and high-density initialization and progressive redundancy pruning are executed to optimize the geometric fidelity; and finally, performing coarse-to-fine camera pose optimization, and outputting a precise pose and a high-fidelity static map. According to the method, the problems of tracking drift and rendering artifacts under dynamic interference are effectively solved, and the positioning precision and the rendering quality are improved.

The invention discloses a multi-view image Gaussian reconstruction method and system guided by LiDAR point cloud. The method comprises the following steps: step S1, realizing accurate registration of LiDAR point cloud and a multi-view image in the same earth-centered earth-fixed coordinate system through GNSS constrained aerial triangulation, and uniformly carrying out center-of-gravity normalization to ensure space consistency and numerical stability; s2, estimating surface normal and scale parameters based on the local geometric features of the LiDAR point cloud, constructing a Gaussian ellipsoid consistent with the local geometry, and realizing Gaussian ellipsoid initialization of geometric perception; and S3, generating a sub Gaussian ellipsoid according to the Gaussian gradient and the tangent plane direction, and improving the modeling density and geometric continuity of the detail region through local encryption and parameter inheritance. According to the method, the fusion of LiDAR point cloud high-precision geometry and multi-view image texture information is realized, the geometric precision, the structural integrity and the detail expression capability of three-dimensional reconstruction are effectively improved, and the method is particularly suitable for high-precision live-action three-dimensional modeling of unmanned aerial vehicle multi-view images.

An EUV collector (24) is used in an EUV projection exposure system. The EUV collector (24) is designed to guide EUV useful light (3) from a source area (19) to a collecting area (26). The EUV collector (24) has at least one reflective surface area (28) which has the shape of a segment of an ellipsoid with two ellipsoidal focal points (F1, F2). The source area (19) is located in the region of one of the ellipsoidal focal points (F1), and the collecting area (26) is located in the region of the other ellipsoidal focal point (F2). The reflective surface area (28) has a maximum collecting angle S2 greater than 120° for useful light beams emanating from the source area (19). Alternatively or additionally, the reflection surface area (28) has at least two detachably connected reflection surface sub-areas, each representing sub-areas of a shape of a section of an ellipsoid with two ellipsoid focal points (F1, F2).

The invention discloses a power distribution scene reconstruction method and device based on three-dimensional Gaussian sputtering, and belongs to the technical field of scene three-dimensional reconstruction, and the method comprises the steps: obtaining a plurality of visible light images of a power distribution scene; performing three-dimensional reconstruction on the plurality of visible light images by using a motion structure recovery algorithm to obtain camera parameters corresponding to the visible light images and sparse point clouds of the power distribution scene; performing densification processing on the sparse point clouds based on the camera parameters corresponding to the visible light images by using a monocular depth estimation model to obtain dense point clouds of the power distribution scene; constructing a plurality of initial three-dimensional Gaussian ellipsoids based on the dense point cloud; performing parameter optimization on the plurality of initial three-dimensional Gaussian ellipsoids based on the plurality of visible light images to obtain a plurality of optimized three-dimensional Gaussian ellipsoids; and generating a three-dimensional reconstruction result of the power distribution scene based on the plurality of optimized three-dimensional Gaussian ellipsoids. Therefore, by implementing the method and the device, the problem of low accuracy of three-dimensional reconstruction in the prior art can be solved.

The invention relates to a three-dimensional model reconstruction method and device based on a Gaussian sputtering model. The method comprises the following steps: acquiring a scene image of a sparse view angle of a target scene, and determining initialization parameter information of a Gaussian ellipsoid according to the scene image through a motion recovery structure technology and a Gaussian sputtering model; determining a priori depth, a color loss function and a gradient smoothing loss function through a monocular depth model according to a scene image; determining a reference depth according to the scene image through a multi-view three-dimensional depth estimation algorithm; determining a depth consistency loss function according to the prior depth and the reference depth; and updating the initialization parameter information through a Gaussian sputtering model based on a depth consistency loss function, a color loss function and a gradient smooth loss function, determining updated parameter information, and generating a three-dimensional model of the target scene according to the updated parameter information. The reliability and robustness of the three-dimensional model can be improved through depth prior constraint information and a dynamic gradient control method.

The invention belongs to the field of three-dimensional scene reconstruction, and particularly relates to a three-dimensional Gaussian reconstruction method based on feature matching and multi-view consistency, and the method comprises the steps: obtaining a feature matching graph and a reliable matching mask graph between image pairs; constructing a surface fitting constraint loss function, and minimizing a component along the z-axis direction in the three-dimensional Gaussian ellipsoid zoom vector to enable the three-dimensional Gaussian ellipsoid zoom vector to become a two-dimensional Gaussian plane; calculating an unbiased depth value of each pixel based on a two-dimensional Gaussian plane normal and a camera line-of-sight direction; calculating a depth re-projection error of the current view angle and the adjacent view angle according to the filtering feature matching graph, and constructing a depth consistency loss function; comparing normal directions of the current view angle and the adjacent view angle according to the filtering feature matching graph, and constructing a normal consistency loss function; and weighting the surface fitting constraint loss function, the depth consistency loss function and the normal consistency loss function to obtain overall optimization loss, and performing back propagation to finally obtain a three-dimensional reconstruction result. The geometric accuracy of a reconstruction result is remarkably improved.

The present application relates to the technical field of computer vision, and particularly relates to a three-dimensional scene reconstruction rendering method and system. The present application generates a corresponding 3D Gaussian ellipsoid for each sparse point cloud of a scene to be reconstructed; obtains a re-projection area of each 3D Gaussian ellipsoid on a two-dimensional image at different viewing angles; takes each re-projection area as the center, and sets all re-projection areas within a certain pixel distance range as adjacent re-projection areas of the re-projection area; based on the sum of the Gaussian kernel function values from the center of the re-projection area of each 3D Gaussian ellipsoid on the two-dimensional image at different viewing angles to the centers of each adjacent re-projection area of the area, the edge intensity, the local variance, the normalized gradient amplitude, and the absolute value of the dot product of the gradient vector and the normal vector, calculates the split control function value of each re-projection area; compares the split control function value of each re-projection area with the size of a set threshold, and controls the 3D Gaussian ellipsoid to split. The present application improves the three-dimensional scene reconstruction rendering precision.

The invention discloses an indoor scene three-dimensional reconstruction method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a multi-view image of an indoor scene, and obtaining a plurality of three-dimensional Gaussian ellipsoids based on the multi-view image; obtaining semantic features of each three-dimensional Gaussian ellipsoid; parameters of the three-dimensional Gaussian ellipsoids are optimized based on a loss function, semantic categories are extracted based on semantic features, attribute alignment is carried out on the three-dimensional Gaussian ellipsoids of the same semantic category, and a reconstruction view after three-dimensional reconstruction is generated; and geometric completion and texture completion are performed on the reconstructed view based on the semantic features to obtain a new view, so that the problem that accurate three-dimensional reconstruction of an indoor scene cannot be realized in the prior art can be solved.

The invention relates to a water invasion volume quantitative identification method based on a semi-ellipsoid radial seepage model, and belongs to the technical field of oil reservoir engineering. The method comprises the following specific steps that dimensionless time tD and pressure increment delta pj of an oil well are calculated; calculating dynamic reserves without water invasion according to the dynamic data of the oil well and a flowing substance balance equation; calculating a water invasion coefficient; the water invasion volume is obtained. The invention relates to a novel method for calculating invasion volumes of different types of water bodies invaded into an oil reservoir by radial flow edge and bottom water by utilizing a semi-ellipsoid geometric model of a Van Everdex-Hust equation principle, which can solve the problem of quantification of the invasion volumes of the water bodies at any moment in the water invasion process of the edge and bottom water oil reservoir. The influence of unstable seepage on the water invasion process is considered, the basic law of fluid flowing in the water invasion process is met, meanwhile, the water invasion coefficient calculation method which does not need to estimate the size of an oil reservoir is provided, and the overall error is small.

The invention relates to the technical field of three-dimensional reconstruction, and discloses a three-dimensional scene reconstruction method and device, equipment, a storage medium and a program product, and the method comprises the steps: carrying out the initialization of a three-dimensional Gaussian ellipsoid based on an obtained fuzzy image sequence and an event sequence, and obtaining an initial Gaussian ellipsoid; constructing a loss function based on a clear picture sequence obtained by rendering the fuzzy picture sequence through the initial Gaussian ellipsoid and geometric constraints of an event-ungenerated area corresponding to the fuzzy picture sequence and the event sequence; taking the minimum value of the loss function as an optimization target, and adjusting the parameter information of the initial Gaussian ellipsoid to obtain a target Gaussian ellipsoid; and performing three-dimensional scene reconstruction based on the target Gaussian ellipsoid to obtain a target three-dimensional scene. Therefore, three-dimensional reconstruction is carried out in combination with a fuzzy picture sequence obtained by a traditional camera and an event sequence obtained by an event camera, the reconstruction effect of a three-dimensional scene is improved, geometric constraint is added to guide and adjust a Gaussian ellipsoid, and the reconstruction effect of the three-dimensional scene is further improved.

The invention relates to the field of remote sensing image processing and terrain correction, and particularly discloses a radar geometric field-driven SAR distortion information adaptive neighborhood propagation identification method, which comprises the following steps of: S1, acquiring a Golden digital elevation model of a research area and a pixel-by-pixel ellipsoid incident angle graph generated by SAR satellite precision orbit parameters and imaging geometry, and carrying out geometric unified processing on the Golden digital elevation model and the pixel-by-pixel ellipsoid incident angle graph; s2, calculating a terrain parameter, an effective slope angle, an R geometric response field and an R field directivity gradient based on the unified raster data; s3, main distortion region classification is carried out according to the effective slope angle and the pixel-by-pixel ellipsoid incident angle; s4, defining an adjacent gradient and constructing a self-adaptive threshold value and a shadow self-adaptive threshold value; and S5, performing passive region propagation from the boundary of the main distortion region, and generating a final classification grid map after space overlapping correction. According to the method, the defect of blind propagation of the existing method is overcome, and high-precision automatic identification of SAR geometric distortion under complex terrains is realized.

The invention discloses a lightweight multilayer radar echo reconstruction method based on Gaussian splashing, and relates to the technical field of meteorological radar data processing. The method comprises the following steps: preprocessing and standardizing multi-layer radar echo data; dividing the data into space sub-blocks and independently executing Gaussian initialization; constructing a multi-scale lightweight encoder, and fusing spatial context information of adjacent sub-blocks while extracting local features of the sub-blocks; constructing a customized decoder, and reconstructing the implicit vectors into Gaussian ellipsoid parameters with physical constraints according to an attribute dynamic selection path; executing multi-layer micro rendering to generate a simulation image; and calculating composite loss and back-propagating optimization model parameters. According to the method, through sub-block context coding and parameterized Gaussian representation, the problem of discontinuous sub-block boundaries is effectively solved while the high-resolution radar data storage and calculation cost is remarkably reduced, and high-fidelity and physically reasonable radar echo three-dimensional reconstruction is realized.

This invention discloses a robot trajectory learning method and system based on surface dynamic motion primitives. The method includes: acquiring multiple teaching trajectories, parameterizing and rotating the trajectory sampling points to construct a reference coordinate system; learning trajectory features in the u and v directions based on the DMPs framework, and generating a static surface through Gaussian smoothing and weighted averaging; modeling obstacles using ellipsoids, designing dynamic obstacle avoidance coupling terms embedded in the DMPs formula to enable real-time bending of the surface for obstacle avoidance; learning velocity and acceleration information through classical DMPs, and combining it with parameter mapping of the starting / target position of the new task to generate an obstacle avoidance trajectory and control the robot's motion. This invention solves the problems of traditional DMPs being unable to directly learn surfaces, having lag in obstacle avoidance response, and losing spatial information, improving the robot's trajectory adaptability and real-time obstacle avoidance capability in semi-structured environments, and ensuring assembly accuracy and safety.

The invention describes a sphere measuring device (10) for optically determining at least one shape parameter (F) of an at least partially reflective sphere (12), wherein the sphere measuring device (10) comprises: a light source (14) for emitting coherent light (16) with a first central wavelength (λ1), a beam splitter (22) arranged to generate measuring light (16.M1) and reference light (16.R1), a measuring arm mirror (24) arranged to reflect at least a portion of the measuring light (16.M1) onto at least a portion of the sphere (12), and a reference arm mirror (30) configured to reflect at least a portion of the reference light (16.R1), wherein the sphere measuring device (10) is configured to superimpose at least a portion of the light (16.R2) reflected by the reference arm mirror (30) with at least a portion of the light reflected by the measuring arm mirror (24). (16.M2) in an interference area (34) such that interference occurs, a detector (40) which is arranged to detect at least one measurement brightness value (I. n ) in at least part of the interference range (34) and is designed such that, based on the measured brightness value (I n ) the at least one shape parameter (F) of the sphere (12) is determinable, wherein the measuring arm mirror (24) has a concave rotational ellipsoid section (26) which is designed such that the sphere (12) can be placed within the rotational ellipsoid section (26) with its center point (M) in a first focal point (B1) of the rotational ellipsoid section (26), namely in a measuring position, and the light source (14) is designed such that a light source point (20) of the light source (14) is located in the second focal point (B2).

The application discloses a method for calculating critical submerged water depth of a side-type water inlet based on a CSSS method. A point sink spherical critical surface model is constructed, and a conservation relationship between an effective working area and a radial flow velocity is established based on a continuity equation. For complex boundary working conditions, a dimensionless criterion is introduced to determine the effectiveness of the spherical assumption, and when the spherical assumption is invalid, an anisotropic ellipsoid correction is started, and a coordinate stretching equivalent method is used to calculate a limited effective area. A physical correction coefficient is constructed by using a potential flow geometric component and a dynamic loss component to replace pure statistical regression. A dynamic safety margin is calculated in combination with a vortex evolution time scale. The application solves the problem of prediction distortion of the critical water depth under a complex flow field, and improves the physical precision and operation safety of engineering design.

The invention discloses a Grignard dual-bias antenna device and a focusing method based on a positioning tool. The device comprises an antenna device and the positioning tool. The antenna device comprises a main reflecting surface, an auxiliary reflecting surface, a feed source, a bracket, a feed source adjusting plate and an adjusting structure, the front face of the auxiliary reflecting face is an intersection face of an ellipsoid and a cone, the front face of the main reflecting face is an intersection face of a paraboloid and a cone, the perifocus of the ellipsoid coincides with the focus of the paraboloid, the far focus of the ellipsoid coincides with the phase center of the feed source, the main reflecting face is connected with the support, and the auxiliary reflecting face is connected with the support and the positioning tool through an adjusting structure. The reference of the device is simple and reliable, the processing and assembling precision is improved, and the focusing operation is simple. According to the device, four groups of boss surfaces are arranged on two sides of the main reflecting surface, and three groups of boss surfaces are arranged on two sides and the bottom of the auxiliary reflecting surface, so that a new entity reference surface is formed, antenna processing and assembling reference determination are facilitated, and processing and assembling precision is improved.

This invention relates to the field of 3D reconstruction technology, and discloses a dynamic pedestrian 3D reconstruction method based on adaptive prior fusion, comprising: acquiring a video frame sequence and initializing a Gaussian ellipsoid; generating a clean kinematic human body mask and an accessory mask; acquiring accessories based on the accessory mask and calculating the global transformation matrix of the accessories; extracting temporal information, instance embedding features, and visual features, concatenating them, and inputting them into an adaptive guidance module to obtain conditional feature vectors and reliability confidence scores, and predicting the non-rigid residual deformation of the Gaussian ellipsoid; calculating the final state of the Gaussian ellipsoid based on the non-rigid residual deformation; inputting the Gaussian ellipsoid in the final state into a differentiable rasterizer to generate a 2D rendered image; calculating the joint loss function and optimizing the Gaussian ellipsoid; and generating a 3D reconstructed image of the dynamic pedestrian based on the optimized Gaussian ellipsoid and the global transformation matrix. This invention can improve the accuracy of dynamic pedestrian 3D reconstruction.

The invention relates to the technical field of radiation field calculation, and relates to an improved non-uniform radiation field grid division method and system. Comprising the following steps: carrying out initial uniform grid setting on a radiation field calculation area; performing N-time sparse processing on the initially set uniform grid; calculating the distance from the center point of each sparse grid to the ellipsoid surrounded by the source item, and determining the weight multiple of the grid according to the distance; traversing all source items and grids in sequence; carrying out refining processing on all the grids with the weight multiples greater than 1 according to the corresponding multiples; and summarizing and outputting all grid intersection points, namely a final radiation field calculation dot matrix. According to the radiation field change rule of the area near the source item, the judgment basis of whether the grid needs to be refined is improved, and whether the ratio of the distance from the grid center point to the ellipsoid surrounded by the source item to the source linearity is smaller than 1.5 is modified from whether the grid is an extension grid, so that grid division near the source item is more reasonable, and the accuracy of grid division is improved. And the calculation efficiency and the calculation precision of the radiation field are better considered.

The application relates to a three-dimensional model reconstruction method and device based on a Gaussian sputtering model. The method comprises the following steps: acquiring sparse-view scene images of a target scene, and determining initialization parameter information of a Gaussian ellipsoid according to the scene images by using a motion recovery structure technology and a Gaussian sputtering model; determining prior depth, a color loss function and a gradient smoothing loss function according to the scene images by using a monocular depth model; determining reference depth according to the scene images by using a multi-view stereo depth estimation algorithm; determining a depth consistency loss function according to the prior depth and the reference depth; updating the initialization parameter information based on the depth consistency loss function, the color loss function and the gradient smoothing loss function by using the Gaussian sputtering model, determining updated parameter information, and generating a three-dimensional model of the target scene according to the updated parameter information. The reliability and robustness of the three-dimensional model can be improved by using a depth prior constraint information and a dynamic gradient control method.

The invention discloses a sand and dust particulate matter dry sedimentation analysis method based on spheroid morphology correction, a storage medium and equipment, and belongs to the technical field of atmospheric environment simulation. Based on a meteorological field and an emission source, an air quality model is constructed; for a particulate matter dry sedimentation module in the air quality model, the final sedimentation velocity is corrected, and a morphology factor-final sedimentation velocity coupling equation is established; and outputting concentration particle size spectrum distribution and space-time distribution based on the corrected particulate matter dry sedimentation module. According to the method, the settlement calculation model which better conforms to the characteristics of the sand and dust particles is introduced into the numerical mode, the simulation precision is improved, the forecasting capacity of the sand and dust process is further improved, and the method has good practicability.

The invention discloses an unstructured industrial scene rapid three-dimensional reconstruction method based on semantic Gaussian sputtering, and the method comprises the steps: estimating a camera pose from a multi-view RGB image through one-time forward propagation by employing an industrial scene adaptive VGGT model, and generating an initial 3D Gaussian ellipsoid; meanwhile, a pre-trained visual language model is adopted to extract multi-scale 2D semantic features so as to distinguish instance-level and component-level features of the tool; on the basis, combined optimization and adaptive control are carried out on the Gaussian ellipsoid by combining RGB luminosity loss, component-level semantic loss and semantic-geometric regularization loss; and finally, a three-dimensional Gaussian sputtering model containing instance and component-level semantic information is constructed. According to the method, the problems of poor three-dimensional reconstruction quality, low speed and semantic deficiency caused by high light reflection, weak texture and the like in an unstructured industrial scene are effectively solved, and support is provided for precise operation of a robot.

The invention relates to a three-dimensional reconstruction technology, in particular to a physical rendering image generation method based on material estimation and illumination estimation, which comprises the following steps: adding three types of material parameters of primary color, metallic degree and roughness for each Gaussian atom; completing color synthesis of the current frame through a differentiable Gaussian rasterization process; constructing a material-to-spherical harmonic coefficient material estimation network, taking the Gaussian ellipsoid material, the visual angle and the position as input, and embedding the material attribute into the spherical harmonic coefficient; constructing an ambient light estimation network to obtain current ambient light information, and taking an SH coefficient, a position and an observation view angle of a Gaussian ellipsoid as input to obtain a dominant incident direction and light intensity under the view angle; a Disey physical coloring model is adopted, primary colors obtained through projection are directly used as diffuse reflection primary colors in a pixel domain, and a physical rendering image is generated in combination with the metallic degree, the roughness, the normal and incident light. According to the method, the material information of the object can be obtained on the basis of rapid explicit rendering, and the method does not depend on external prior.

The invention discloses a method for calculating the critical submerged water depth of a side water inlet based on a CSSS method. According to the method, a point sink spherical critical plane model is constructed, and a conservation relation between an effective working area and a radial flow velocity is established based on a continuity equation. For a complex boundary working condition, a dimensionless criterion is introduced to judge the effectiveness of a spherical hypothesis, anisotropic ellipsoid correction is started during failure, and a coordinate stretching equivalent method is utilized to calculate a limited effective area. A potential flow geometric component and a dynamic loss component are adopted to construct a physical correction coefficient, and pure statistical regression is replaced. And calculating a dynamic safety margin in combination with a vortex evolution time scale. According to the method, the problem of critical water depth prediction distortion in a complex flow field is solved, and the physical precision and operation safety of engineering design are improved.

The invention relates to the technical field of underwater acoustic transducers, in particular to a composite material for improving directional fluctuation of an arc-shaped transmitting array and a manufacturing method, a radiating surface of the piezoelectric composite material is of a special-shaped structure, and the number of effective piezoelectric particles of the piezoelectric composite material is uniformly decreased from the center to the edge. The manufacturing method comprises the following steps: cutting the front side and the back side of the piezoelectric ceramic and filling a flexible material to form an independent particle supporting structure; carrying out bending forming and filling a rigid material for shaping; and finally, precisely finishing the edge of the radiating surface along the specific ellipsoid curve. According to the invention, distribution of active materials of the radiating surface is structurally adjusted, complex circuit weighting is not needed, edge directivity intensity can be effectively inhibited, directivity fluctuation of a transmitted wave beam is obviously reduced, sonar imaging quality is improved, and the method has the advantages of simple process and good consistency.