144 results about "Global grid" patented technology

Provided are a method, system and device for global path planning for an unmanned vehicle in an off-road environment. The method includes: obtaining satellite elevation data and a satellite remote sensing image of a current off-road environment; constructing a digital elevation model (DEM); determining slope and land surface relief of each grid in the current off-road environment; performing gray processing on the satellite remote sensing image to obtain grayscale values of the grids; determining traversal costs of the grids corresponding to different ground types; constructing a global grid map based on the slope and the land surface relief of each grid, as well as the traversal costs corresponding to the different ground types; determining a rugged terrain potential field and path costs; and searching for paths using a Bresenham's line algorithm and Theta* algorithm based on the rugged terrain potential field and the path costs, to generate a global path.

The invention relates to the technical field of ocean engineering digital twinning and three-dimensional visualization, and provides a method and system for generating dredging terrain twinning based on a right-angle triangular mesh, and the method comprises the steps: obtaining regular grid elevation unified to an engineering plane coordinate system or preprocessed sampling height data, determining a covered space range, reading the space range and density parameters, and calculating the total row number and the total column number of the grids based on the space range and the density parameters; generating regularly arranged vertexes in the covered space, and constructing a topological structure of an isosceles right triangle grid; dividing the global grid into a plurality of Chunk blocks according to a fixed size by taking a vertex as a unit, establishing a triangular index mapping relationship between global rows and columns and the Chunk blocks, filling three vertexes of an isosceles right triangle and elevation / height data in each Chunk block in parallel, and generating local VBO, IBO and AABB; and performing batch rendering and coloring according to a height color table on all Chunk blocks to realize visualization of the terrain.

The invention relates to the technical field of simulation, in particular to a simulation task resource allocation method and device, equipment and a medium, and the method comprises the steps: carrying out the global grid division of a current simulation task, obtaining a plurality of grid units, and extracting the key information of each grid unit, outputting a load index corresponding to each grid unit based on the target load prediction model, generating global load distribution data according to the load indexes of all the grid units, dividing the global simulation area into a plurality of sub-areas, and obtaining load prediction data of each sub-area; and according to the load prediction data of each sub-region, distributing the sub-tasks of each sub-region to a target computing unit. Therefore, the problems of insufficient fine-grained task division and high dynamic scheduling overhead in the prior art are solved, the overall calculation efficiency and the resource utilization rate are improved, and the system complexity and the synchronization delay are reduced on the premise of ensuring the simulation precision.

The invention relates to a complex instruction-driven navigation method based on cross-modal ontology collaborative active perception, which mainly comprises the following steps of: constructing a global grid map which is dynamically accumulated in real time in a navigation process, and constructing a local active perception semantic map; classifying three-dimensional points in the local perception semantic map, and screening to obtain candidate points based on a classification result; splitting the complex instruction into a plurality of sub-tasks and encoding, then performing space-time alignment processing on the sub-tasks and the features of the candidate points, calculating the correlation between different candidate points and each sub-task, and determining the multi-modal features of the candidate points; and inputting the multi-modal features of the candidate points and the global grid map features into a Transform model, obtaining a logic value set of the candidate points through an attention mechanism, and determining an optimal candidate point. Compared with the prior art, the method has the advantages that a multi-step fuzzy instruction navigation task can be completed in an unknown environment, and the problems of insufficient generalization ability in a new environment and limitation on fuzzy instruction processing of a conventional method are solved.

The invention discloses a wheeled robot path planning method for different scenes and a related device, and the method comprises the steps: obtaining environment data around a robot, building a global grid map, carrying out the preprocessing of the global grid map, carrying out the geometric feature recognition and angular point extraction of an obstacle, and fusing a multi-sampling strategy to generate a path search network. Path searching is carried out according to the target point and the pose planning, and a global optimal path conforming to robot driving is obtained; segments in the global optimal path are intercepted through the rolling window principle to serve as local paths to be input into a local path planning algorithm, a local optimal track is generated, and a speed instruction is output; and updating the map in the rolling window in real time, executing an obstacle avoidance task on the obstacle through the local optimal track, driving along the global optimal path again after obstacle avoidance, and moving to a target point according to a speed instruction. According to the method, the problems of large speed fluctuation, low quality of the generated path and calculation burden caused by increase of alternative path points in the current robot driving process are solved.

The invention belongs to the field of robot technology and computer vision, and particularly relates to an instant positioning and mapping method based on multi-source sensor information efficient fusion optimization. The method comprises the following steps of: firstly, adding effective gradient change characteristics for a weak texture environment by actively projecting infrared speckle textures; improving the contrast ratio of the weak texture region image by combining a homomorphic filtering method; then, utilizing an AGAST adaptive feature extraction method to enhance the feature detection sensitivity and stability in a low-light environment; high-frequency motion information provided by an IMU sensor is fused with environment visual features obtained by a camera, a comprehensive nonlinear optimization model is constructed, system state errors are accurately modeled, noise and uncertainty influences are effectively reduced, and optimal solution of the system state is achieved. And finally, on the basis of the probability grid sub-graph and the probability model, effective depth information is obtained by combining internal reference of the camera and a visual field range, and construction, directional expansion and dynamic updating of a global grid map are finally realized.

The invention discloses a topological network global optimization method based on graph reinforcement learning, and relates to the field of computational geometry and grid optimizing.The method comprises the steps that a topological optimization process is modeled into a Markov decision process, a topological network containing singular points and angular points is converted into heterogeneous graph representation, and a graph state is constructed; selecting a topology editing action by a reinforcement learning agent fused with the graph neural network based on the current graph state; after executing the action, updating a topological structure and a graph state, and calculating an instant reward based on the global grid quality index change; training intelligent agents in batches through experience playback and time sequence differential learning, so that the intelligent agents learn a mapping strategy from a graph state to an optimal action; and applying the trained policy network deployment to automatic optimization of the new topology. According to the method, full-process automation of topological optimization is achieved, non-local negative effects of local modification are effectively avoided, a global optimal optimization strategy is learned, the grid quality and optimization efficiency are remarkably improved, and the method is suitable for simulation grid generation of aircrafts.

The invention relates to the technical field of electric digital data processing, and discloses a 3D intelligent stocktaking method and device, and the device comprises a 4D millimeter wave radar disposed at the top of a stock bin, S1, obtaining the data of a corresponding coverage area detected by the 4D millimeter wave radar; s2, preprocessing the acquired data; S3, processing the preprocessed data by a point cloud data grid filtering algorithm to obtain point cloud data on grids on a global grid map; s4, checking the integrity of the data, and if blank grids exist in the global grid map, filling the grids of the blank data in the global grid map by using a point cloud smooth interpolation algorithm to form a final smooth point cloud; and S5, reconstructing the surface of the material, and constructing a three-dimensional diagram of the surface of the material according to the final smooth point cloud determined in the step S4. Through the 4D millimeter wave radar and various algorithms, the real-time and all-around monitoring of the material bin is realized, and accurate three-dimensional material level imaging is provided.

The invention discloses a concrete member crack measurement method based on a convolutional neural network, and relates to the field of concrete crack detection, and the method comprises the steps: carrying out the marking, size clustering, image enhancement, coordinate transformation and other preprocessing operations of a concrete member image, and constructing a detection model architecture; wherein the backbone network adopts a pre-trained ResNet-50 network to extract multi-scale features of the image; the box neck and the box head are used for generating local crack box output; the grid neck and the grid head are used to generate a global fracture grid output. In a model training process, local box output and global grid output are optimized by adopting a joint loss function, and prior category information of crack size clustering is introduced to guide learning of a detection model. In the reasoning stage, an image to be detected is input into the trained detection model, box output and grid output are obtained, and a final crack detection result is obtained through post-processing such as non-maximum suppression. And aiming at low crack detection precision under a complex background, the detection precision is improved.

The invention discloses a robot moving path planning method and device, electronic equipment and a storage medium. The method comprises the following steps: receiving a first control instruction for a robot, and obtaining an actual position of the robot and a global grid map of a preset activity area of the robot; determining a target advancing path according to the first control instruction, the actual position and the global grid map, and controlling the robot to move along the target advancing path; in the advancing process of the robot, space information of the robot is collected through a data collection module installed on the robot, and the space information comprises environment information and pose information; and determining an environment state vector according to the space information, and updating the target advancing path of the robot according to the environment state vector and the global grid map, so that autonomous navigation and dynamic path planning of the robot can be realized, and the moving efficiency, the environment adaptability and the target arrival accuracy are improved.

The invention discloses a global path planning method based on a global road network and a local grid map, and the method comprises the steps: controlling a vehicle to drive on an expected path in advance, recording path points, building a global grid map, and generating a global road network set according to the recorded path points; according to the position relation between the starting point and the path point closest to the starting point in the global road network set and the position relation between the target point and the path point closest to the target point in the global road network set, path segmentation planning is carried out, path splicing is carried out on planned paths, smoothing processing is carried out, and a global path is generated. According to the method, the advantages of the autonomous path planning algorithm and manual intervention are brought into full play, mutual complementation is achieved, the strong computing power and adaptability of the autonomous path planning algorithm are fully utilized, valuable early-stage knowledge and experience provided by manual intervention can be used for reference, and therefore the actual use requirement is better met.

The invention relates to an intelligent robot path planning and optimizing method and device based on a fusion ant colony algorithm, equipment and a medium. The method comprises the following steps: acquiring a global grid map and a dominance evaluation function, and initializing an artificial potential field and an ant colony; placing the ant colony at the starting point grid for searching to obtain an ant colony path space after each search; if the ant colony path space does not meet the iteration ending condition, re-placing the ant colony at the starting point grid for searching until the ant colony path space meets the iteration ending condition; and if the ant colony path space meets an iteration ending condition, generating a global optimal path based on an optimal collision-free path in the ant colony path space. By the adoption of the method, global optimal target guidance of the ant colony algorithm can be determined through the advantage evaluation function, and the search efficiency is improved based on the improved heuristic function combining the iteration parameters and the artificial potential field.

The invention provides a full-automatic semi-structured grid generation system and method suitable for complex geometry, and the method comprises the steps: employing a top-down reverse grid generation strategy, enabling a space adaptive Cartesian grid generation module to divide a computational domain into regular unit (square (2D) and hexahedron (3D)) grid units based on a Cartesian coordinate system; generating a surface grid by using an imprint-partition mapping method; and generating a boundary layer grid module by using a construction method. Based on the technical scheme of the invention, seamless connection of the Cartesian grid, the boundary layer grid and the surface grid is realized, boundary layer analysis precision and global grid generation efficiency and quality are considered, and the method has good universality, robustness and engineering adaptation capability. And the problem of poor calculation precision near the boundary caused by a Cartesian grid non-skin body is effectively solved. Grid transition is freer, topological compatibility does not need to be strictly guaranteed, and self-adaptive encryption optimization of any area can be better achieved.

The invention discloses a structure configuration generation method, device and equipment and a readable storage medium, and is applied to the technical field of computers, and the method comprises the steps: carrying out the decoupling processing of a global grid model, and obtaining an order reduction model and a structure optimization model; applying an external load and a boundary condition to the reduced-order model, and solving to obtain a displacement load; and inputting the displacement load, the design constraint and the manufacturing constraint into a pre-trained structure configuration optimization model to obtain a generated optimal structure configuration. According to the method, the calculation scale of the structure configuration optimization model is greatly reduced, the calculation efficiency is improved, and the grid resolution in the to-be-optimized target structure area is improved, so that the high-fidelity structure configuration is generated; unnecessary materials can be reduced on the premise that the safety of a train is not influenced; on the premise of keeping the geometric features of the target structure region to be optimized similar, a high-fidelity structure configuration can be generated for any size, external load and boundary conditions, and the universality in a global parameter space is realized.

The invention relates to the field of power distribution network black start, in particular to a hybrid V2G facility driven power distribution network grading black start control method, which comprises the following steps: after a configuration network loses power, judging whether a V2G facility is in place or not, if so, setting the selection priority of a grading black start power supply, and if not, setting the selection priority of the grading black start power supply; wherein the black-start power supply comprises a V2G facility, a diesel generator, a distributed new energy source and a thermal power generating unit; sequentially entering first-stage black start, second-stage black start and third-stage black start, and implementing black start control strategies of corresponding stages; if all the target nodes recovered at the current level are recovered, entering next-level black start; wherein the control targets of the first-stage black start, the second-stage black start and the third-stage black start are as follows: focusing a core looped network branch node, and ensuring that a core load and a power supply auxiliary machine supply power; main branch nodes are expanded, and part of residential areas and industrial and commercial areas are recovered; and carrying out multi-source collaborative frequency modulation and global grid-connected recovery. Compared with the prior art, the method has the advantages of realization of graded black start, rapid and stable recovery and the like.

The invention belongs to the technical field of farm automatic inspection and positioning mapping, and discloses a farm inspection robot positioning mapping method based on laser and vision assistance. The method comprises the following steps: firstly, converting depth image data shot with similar depths into point cloud coordinates, and then converting the point cloud coordinates into laser data through an inverse projection method; then acquiring information of an unstructured region of the farm from an image shot by the depth camera by using an ORB-SLAM technology, and converting the information into a sparse three-dimensional point cloud map; converting the three-dimensional point cloud map into a grid map through point cloud mapping for subsequent map fusion; besides, a single-line laser radar is used for scanning the environment to obtain information of a structured part in the farm environment, and a Gmapping technology is used for establishing a laser radar map; and finally, fusing the laser radar map and the grid map subjected to visual conversion by adopting a Bayesian fusion technology to obtain a global grid map. According to the invention, an accurate and comprehensive map can be established in an indoor poultry breeding environment.

A method detects a spatial arrangement of a physical object by assigning an attribute to a selection of uniquely identifiable global grid elements of a reference grid network. The method includes providing a global reference grid network with a geographical reference point defined vector-object-independently and global grid elements, which are adjacent to one another without overlap and are uniquely identifiable within the global reference grid network and are georeferenced with regard to a provided reference coordinate system, providing a vector object with at least one vertex, to which a geographical coordinate of the geographical reference coordinate system is assigned, determining and selecting those global grid elements that overlap with the vector object, and assigning an object attribute linked with the vector object or a further attribute to the grid elements selected and storing the selected grid elements with assigned attributes.

The invention discloses a plane design element importance detection method, system and equipment based on weak supervision training and a medium. The method comprises the following steps: manually marking a data set of a global grid sequence; dividing the graphic design into a global grid and a local grid through weak supervision training; obtaining a prediction sequence and a relative weight by using the local sequence prediction model and the global sequence prediction model; the relative weight of the text and the visual feature Vt is obtained through a weight adaptive model; calculating importance indexes of the graphic design elements; the system, the equipment and the medium are used for implementing the method. By introducing a strategy of combining division of a global grid and a local grid of plane design and a multi-scale sequence prediction model, a training process is optimized, and efficient sequence prediction is realized; the importance detection of the design elements can be carried out in an efficient, accurate and low-cost mode, and a more feasible solution is provided for the wide field of plane design.

The application provides a distributed remote sensing interpretation vector post-processing method based on a grid DCEL topology. The method comprises: performing grid slicing on global grid data to obtain grid data of a plurality of grid units; constructing a bidirectional edge connection table topology based on the grid data of each grid unit respectively; performing elimination processing, thinning processing and smoothing processing on the topology of each grid unit respectively; merging the topology of each grid unit to obtain a global topology; and exporting the global topology as vector data. In this way, a high-performance grid topology engine based on a distributed architecture can be provided, a DCEL topology structure can be constructed from grid data, and distributed computing can be supported through a topology level merging algorithm; the grid is used to construct the topology, thereby reducing the steps of grid vectorization, and the grid-based topology construction method can naturally support distributed computing.

The invention relates to the technical field of seismic exploration, and particularly discloses a seismic wave field forward modeling method and device under an undulating surface, and the method comprises the steps: obtaining a surface model function of the undulating surface; embedding the surface model function into the difference grid model by using an immersed boundary method to obtain a finite difference grid model; calculating space positions of spanned nodes, pseudo spanned nodes, corresponding projection points and fractional nodes in the finite difference grid model; calculating the wave field value of the global grid node based on a finite difference grid model to obtain the wave field value of each node in the global integer grid nodes; utilizing a parabola interpolation method to determine wave field values at fractional nodes corresponding to the spanning nodes and the pseudo spanning nodes; and on the basis of transmission absorption boundary conditions, according to the wave field values of the fractional nodes corresponding to the spanned node and the pseudo spanned node, updating the wave field values at the spanned node and the pseudo spanned node to obtain a seismic wave forward modeling result. According to the scheme, the accuracy and efficiency of the seismic wave field forward modeling method are improved.

The application provides a multi-line structured light three-dimensional reconstruction frame point cloud real-time de-stacking and fusion method, and relates to the technical field of line structured light three-dimensional reconstruction. The distribution characteristics of the spatial position of the point cloud are utilized, a global grid structure is established through the position of the multi-view frame point cloud during three-dimensional reconstruction, the corresponding domain point set of each frame point cloud is solved, and the normal feature estimation is performed according to the distribution characteristics of the neighborhood points. The overlapping condition of the point cloud is detected according to the global grid structure, the cylindrical neighborhood structure of the overlapping frame point cloud is established, and the point cloud fusion is realized through the weighted sum of the point cloud vector direction of the target point and the fusion neighborhood point set and the normal vector feature. The algorithm can meet the system stability requirement in the three-dimensional reconstruction, improves the quality of the final point cloud model, greatly improves the measurement adaptability of the multi-line structured light three-dimensional reconstruction in the complex environment, and effectively improves the multi-line structured light three-dimensional reconstruction precision.

The present application relates to the technical field of marine engineering digital twin and three-dimensional visualization technology field, provide a kind of based on right triangle grid's dredging topography twin's generation method and system, comprising: obtaining regular grid elevation or sampling height data after pre-processing that have been unified to engineering plane coordinate system, determine the space range covered read space range and density parameter, based on space range and total row number and total column number of calculated grid;In the space covered, generate regularly arranged vertex, construct the topological structure of isosceles right triangle grid;With vertex as unit, several Chunk blocks are divided into global grid with fixed size, establish the triangular index mapping relationship of global row and Chunk block, the three vertices of isosceles right triangle and elevation or height data are filled in each Chunk block in parallel, generate local VBO, IBO and AABB;Batch rendering and coloring according to height color table are executed to all Chunk blocks, and the visualization of topography is realized.

The present application discloses an AGV path planning method, device and medium based on cold and hot degrees, which relates to the technical field of logistics management and is used for planning the AGV path. Aiming at the problem of traffic jams that are prone to occur currently, an AGV path planning method based on cold and hot degrees is provided. The passing cold and hot degrees of each grid are calculated through historical passing data to represent the passing frequency of the AGV passing through the grid, and then the global grid map is divided into multiple regions with different levels in the form of passing cold and hot degrees. Therefore, when performing path planning for logistics tasks, path planning can be carried out according to the preset task priorities. The more important the task is, the shortest path planning can be carried out in the regions with more passing cold and hot degree levels to obtain the optimal path. The expected traffic conditions are taken into consideration to more reasonably plan the AGV path, effectively reducing the occurrence probability of traffic jam problems, and thereby improving the operation efficiency of the AGV system.

The application discloses a kind of wind power three-row column variable pitch bearing injection and drainage hole simulation analysis method.For the problems of numerous variable pitch bearing injection and drainage holes, difficulty in meshing the overall finite element model and difficulty in convergence, the method first creates an overall mechanical analysis model without injection and drainage holes, uses spring element to equivalent rolling body, carries out overall finite element analysis, extracts the maximum load and inclination angle of roller;Then, according to the maximum load position, a submodel with injection and drainage holes is established, considering the profile modification and inclination angle of solid rollers, the grid of key parts is refined;Finally, the stress of injection and drainage holes and the contact stress of raceway are obtained through submodel analysis to evaluate the influence on bearing carrying capacity.The application avoids the problem of calculation divergence caused by global grid refinement, can effectively analyze the stress of injection and drainage holes, and provides reference for bearing structure design and optimization.

The invention provides a method for efficiently and parallelly generating a 10 billion-level unstructured grid at a ten-thousand-core level, which adopts an MPI parallel architecture to realize ten-thousand-core-level calculation, and averagely distributes calculation tasks to each process through a dynamic load balancing technology; a hierarchical communication and memory access mode is designed, grid data are stored in a plurality of process memories in a distributed mode, and limitation of a single-machine memory is effectively overcome; developing a self-adaptive interface matching algorithm, performing local reconstruction on an unmatched grid region, and ensuring that the requirement of local grid quality is met; global grid number reconstruction and boundary condition analysis algorithms are optimized, and a dynamic block hash table technology is adopted to efficiently process 10 billion-level grid matching. According to the method, the technical bottleneck of generation of the complex geometry 10 billion-scale unstructured grids is broken through, efficient generation of the 10 billion-scale unstructured grids is achieved on a domestic supercomputing platform, tests show that generation of 3 billion unit grids can be completed within several hours, and the speed is increased by more than one magnitude compared with a traditional method.

The invention provides a map construction method, a controller, a self-moving device and a storage medium, and the method comprises the steps: obtaining point cloud data collected by the self-moving device through a first sensor in a moving process based on a map construction task; the first sensor is arranged at a preset position of the self-moving device, and the preset position is used for satisfying extraction of structured features based on the point cloud data; determining pose information of the self-moving device according to the point cloud data, a constructed global grid map and structured features in the global grid map; the global grid map is a map of a mapping area corresponding to the mapping task; the structured features are used for representing edge information in a real environment, the established map is determined according to pose information at the end of mapping, a mapping method based on the grid map is combined with the structured features in the environment, geometric constraints are provided by using the structured features, the problem of angle drift of the grid map in long-term mapping is solved, and the mapping accuracy is improved. And the mapping precision is improved.

The invention belongs to the field of computational electromagnetism numerical simulation, and particularly relates to a non-uniform conformal FDTD method based on a sub-grid technology. According to the method, non-uniform conformal geometric correction is introduced into the sub-grids, so that high-precision fitting of a curved surface boundary is realized, step approximation errors are reduced, and the calculation precision of field quantities near the boundary is improved; according to the method, bidirectional coupling transfer which simultaneously meets line integral conservation and flux conservation is established on a main-sub grid interface, and a conservation relation required by a non-uniform conformal FDTD method is prevented from being damaged, so that interface numerical value reflection is effectively inhibited, energy non-physical errors are reduced, and long-term stability is improved; and fine grids are only adopted in the local fine structure neighborhood and are matched with time sub-cycle propulsion, so that global grid encryption and limitation of global time step length to a minimum unit are avoided, and the storage and calculation time overhead is remarkably reduced while the precision is ensured. According to the method, geometric modeling precision, interface stability and calculation efficiency are considered, and the method has high engineering application value.

A data processing service generates for iteratively applying a geospatial function to geospatial data. The generated code includes at least a first iterative loop and a second iterative loop. The data processing service compiles the generated code to generate compiled code that vectorized at least the second iterative loop. The data processing service receives a request from a client device to perform one or more data processing operations including applying the geospatial function to a data table of geospatial cell indices. The data processing service compiles the request into one or more tasks including at least a vectorized operation based on the compiled code and executes the one or more tasks by at least invoking the vectorized operation on the set of worker nodes.

This invention relates to the field of electronic digital data processing technology, specifically to computer-aided engineering calculation and numerical simulation data processing technology. This invention discloses a design method for determining the maximum hanging weight of an ultra-thin lifting beam. In incremental iterative solutions, the equivalent stress gradient and strain energy density are extracted in real time to calculate local instability characteristic values. When the rate of change of element strain energy density exceeds a threshold, a mesh reconstruction mechanism is triggered. The nodal displacement field and stress field are extracted as initial boundary conditions. The coarse mesh is split into a fine mesh, and the coordinates of newly added nodes are smoothly interpolated based on the minimum potential energy principle. The local and global mesh degrees of freedom are coupled and assembled to continue nonlinear buckling analysis iterations until the load-displacement curve shows an extreme point. The corresponding load is then extracted as the maximum hanging weight. This invention avoids stiffness matrix singularities and computational divergence caused by distortion of the fixed mesh in local instability regions, ensuring the computational convergence of determining the maximum hanging weight.

The embodiment of the invention provides a zenith troposphere delay prediction method, a zenith troposphere delay prediction device and electronic equipment. The method comprises the following steps: acquiring multi-source heterogeneous data; performing alignment on the multi-source heterogeneous data to obtain global grid data; according to the global grid data, zenith statics delay ZHD and zenith wet delay ZWD are modeled to obtain a ZHD long-period prediction model and a ZWD short-time prediction model; according to the global grid data, constructing a correction model which changes along with the elevation in the vertical direction; and according to the ZHD long-period prediction model, the ZWD short-time prediction model and the correction model, performing ZTD prediction on a to-be-measured station. And the prediction accuracy of the ZTD is improved, so that support is provided for improving the stability and precision of GNSS positioning.