134 results about "Spatial Projection" patented technology

The invention provides a space projection error analysis-combined 4D millimeter wave radar and visual camera automatic calibration method. The method comprises the steps of constructing a sensor internal reference model; designing a composite multifunctional calibration board and a three-dimensional adjustable holder, performing rigid geometrical relationship modeling, and automatically associating physics-features-coordinates; collecting multi-frame synchronization frame pair data, and performing time sequence fine grit alignment and interpolation compensation to obtain a space-time alignment frame pair sequence; extracting cross-modal spatial constraints of the features and automatically screening and matching point pairs to obtain a high-confidence point pair set; performing point-point constraint and point-point error, point-plane error and pixel reprojection error minimization to obtain a standardized error term; and constructing an overall objective function, and performing spatial constraint and time deviation estimation to obtain corrected external parameters and synchronization deviation. According to the invention, through a full-automatic standardized process, the probability of artificial participation and error occurrence is greatly reduced; and multi-modal and multi-scene high-precision calibration is supported, and the flexibility and robustness are greatly improved.

The invention relates to the technical field of three-dimensional imaging, in particular to a four-eye structured light stereoscopic vision imaging method, which comprises the following steps of: arranging four cameras and synchronously acquiring multi-view image data with structured light stripes; carrying out image preprocessing and stripe code identification on the obtained four-view-angle structured light image data, and extracting structured light stripe center line positions and corresponding space projection information under each view angle; generating three-dimensional point cloud data of the high-precision target sample by using parallax calculation and a three-dimensional reconstruction algorithm, and completing spatial registration and filtering optimization of point cloud; fusing the point cloud and the light intensity data by combining the reflection intensity information of the multi-view structured light stripes to generate a composite data set containing space and spectral information; and constructing a dense parallax field and executing three-dimensional consistency verification, and generating a high-fidelity three-dimensional reconstruction model with a complete topological relation and sparse shielding compensation capability. According to the invention, the problems of insufficient view angle coverage, shielding area information loss, difficult edge structure matching and the like of traditional stereoscopic vision imaging can be solved.

The invention relates to the technical field of vehicle vision calibration, and discloses a DMS camera calibration method based on computer vision. The method comprises the following steps: acquiring a multi-view original image sequence in a target vehicle cockpit, and synchronously acquiring a camera mounting position, a view angle, an inclination angle and an environment illumination intensity parameter; after distortion correction is carried out on the original image sequence, edge features of a calibration reference object in each frame of image are extracted through image recognition, and an initial calibration matrix containing a mapping relation between pixel coordinates and physical coordinates is generated; constructing a three-dimensional space projection model based on the initial calibration matrix, and adjusting rotation and translation parameters of the model by using an iterative optimization algorithm to enable the error between a virtual imaging position and an actual edge feature to be minimum; and extracting an internal parameter matrix and an external parameter matrix of the optimized model, fusing the internal parameter matrix and the external parameter matrix into a final calibration parameter, and writing the final calibration parameter into a DMS camera firmware storage area. According to the method, the DMS camera calibration accuracy and environmental adaptability are improved, and stable technical support is provided for driver state monitoring.

The invention relates to a trajectory prediction model robustness enhancement method based on dynamic subspace projection decomposition. Comprising the following steps: firstly, extracting hidden layer semantic features containing historical tracks and map topology through a multi-modal feature encoder; secondly, constructing a dynamic routing mechanism based on scene self-adaption, and calculating projection weights of input features on a plurality of expert subspaces; then, executing truncation projection operation based on orthogonal decomposition, retaining core semantics located in a low-dimensional space, and filtering out adversarial disturbance located in an orthogonal complementary space; and finally, introducing a feature consistency constraint training mechanism, taking the reconstructed features of the clean sample as anchor points, and compulsively aligning the purified features of the confrontation sample with the anchor points. Compared with the prior art, the method has the advantages that the robustness of the model in white box gradient attack, black box query attack and physical semantic deception scenes is remarkably improved through feature purification of a physical level and structured consistency constraint, and the prediction reliability of the automatic driving system is ensured.

The invention relates to the technical field of perception fusion, and discloses a tug fusion enhanced perception method based on target tracking and obstacle recognition, which comprises the following steps: processing an AIS, an optical fiber compass, a Beidou RTK, a laser radar, a millimeter wave radar and a panoramic camera on a tug to establish a ship coordinate system; and collecting message data of the AIS and combining with the MMSI information to screen the target ship to obtain the initial position of the target ship. And predicting the state sequence of the target ship to obtain the position, speed and heading information of the target ship. And carrying out target identification on the image, outputting identification results of semantic levels of the ship, the buoy and the quay wall, and carrying out space projection alignment with radar data. And fusing the processed results to obtain a fusion result, and performing early warning according to the fusion result. According to the method, the target ship relative pose resolving precision and the obstacle recognition reliability are improved, the sensing link time delay is shortened, and the driver blind area risk is reduced.

The invention discloses a spatial projection regularization method for sound source localization and sound field reconstruction and a related device, and belongs to the technical field of sound source localization. Specifically, according to the method, an equivalent source method model is utilized, and an external radiation sound field of a sound source to be measured is simulated through a series of virtual sources. Then, according to the first sound pressure transfer matrix from the virtual source arrangement surface to the holographic measuring point plane and the sound pressure of the holographic measuring point, a space projection regularization algorithm is used for solving the inverse problem, and therefore the equivalent source intensity is obtained; and then, reconstructing an external radiation sound field of the sound source to be detected by using the second sound pressure transfer matrix and the equivalent source intensity. And finally, by taking the maximum sound pressure amplitude as a standard, screening field points in an external radiation sound field so as to determine the position of the sound source to be detected. According to the space projection regularization algorithm, truncation processing of the vector space is carried out with the projection size of the measurement information in the vector space as the criterion, real information is reserved, and noise interference is restrained to the maximum extent.

The invention provides an automatic space coordinate registration method and device based on a 3D Gaussian splash model, and the method takes RTK data as a strong constraint to be embedded into SFM optimization, and achieves the deep fusion. During coordinate registration, coarse registration and fine registration are combined, scale and global alignment is solved through coarse registration, and detail optimization is achieved through appearance-geometry double constraints in fine registration; finally, a differentiable optimization framework is put forward, the differentiable rendering characteristic of the 3DGS is utilized, joint optimization and deep coupling are carried out on the space projection loss and the normal vector constraint loss of the fine registration loss function and the 3D Gaussian rendering loss function, the registration error directly guides Gaussian parameter adjustment, meanwhile, the model rendering effect reversely constrains the registration precision, and the precision of the 3D Gaussian rendering is improved. And cooperative improvement of registration precision-model details is realized. The 3D Gaussian splash model is not only a result of coordinate registration, but also a participant of registration optimization, and the problems that a traditional method depends on manual registration, and the cross-coordinate system deviation is large are solved.

The invention provides a precision machining and 3D printing mixed manufacturing execution system, and relates to the technical field of data processing, and the system is used for dividing a three-dimensional model into a configuration area and a finishing area, generating a layer-by-layer closed contour path, obtaining configuration path data, extracting a boundary segment close to the finishing area, and obtaining a configuration path data set; calculating a space projection vector on a finishing target surface to obtain primary finishing path data; calculating a boundary torsion value; superposing interference offset in a historical sample path to a primary finishing path; calculating an interference amplitude index; the fitting path data and the configuration path data are subjected to path connection and unified processing according to the manufacturing sequence, and a mixed execution path instruction is obtained. Precise machining and 3D printing are integrated, and path overlapping, empty cutting or unnecessary machining is avoided.

The invention discloses a power distribution system harmonic source positioning method based on subsystem division, and aims to improve the accuracy and anti-interference capability of harmonic source identification in a power distribution system. According to the method, firstly, an obtained voltage signal is preprocessed, frequency domain feature information is extracted, a subspace projection operator is constructed through singular value decomposition, and effective extraction of each harmonic component in the signal is achieved. Then, carrying out subsystem division on the power distribution system according to the position of the tail end measurement point, for each subsystem, respectively injecting simulated harmonic current into each candidate node by adopting a virtual harmonic injection method, and calculating the response of the node to the tail end voltage; and comparing a simulation result with a measured value, constructing an error vector, screening out a node with the minimum error as a backup harmonic source node, and finally positioning the harmonic source node through zero setting of a connection node and a correction strategy of the most downstream node. The method is suitable for a multi-node and multi-source coexistence large-scale power distribution network harmonic suppression scene.

The invention discloses a real-time virtual environment view layout algorithm based on spherical space guidance. The algorithm comprises the following steps that an original view is acquired and preprocessed; abstracting into a circular structure and completely mapping to a constructed spherical view projection structure; weight analysis is carried out, a preset threshold value is compared, a high-weight standard view set and a low-weight standard view set are divided, and dynamic batch layout optimization processing is carried out on the high-weight standard view set; constructing a space pressure function field for the low-weight standard view set, and determining a target position by using a space pressure field guiding method; smooth movement from the current position to the target position is achieved through a Bezier curve interpolation method; and when the viewpoint or view angle change exceeds the threshold value, re-calculating the layout until the change amplitude is smaller than the threshold value, and generating a final layout. According to the method, the spherical space projection and the adaptive mechanical model are combined, the large-scale view layout is optimized, the method has the advantages of being efficient, stable and real-time, and the data visualization effect in the virtual environment is improved.

The invention provides a regional electromagnetic intelligent evaluation method and system based on spectral entropy weighting, and the method comprises the following steps: collecting electromagnetic spectrum data and the motion state of a patrol vehicle, and constructing a virtual aperture data matrix through the motion information; space covariance analysis and subspace projection are carried out on the matrix, multipath scattering interference is separated and eliminated, and a pure field intensity sequence is obtained through reconstruction. By calculating the normalized spectrum entropy of the Doppler power spectrum of the pure field intensity sequence, an inverse proportion weight coefficient representing the signal confidence is generated; and weighting the weight to a pure field intensity sequence, and mapping the pure field intensity sequence to a geographic space. And dynamically adjusting the density of the evaluation grid according to the field intensity gradient, and finally carrying out weighted centroid calculation based on inverse proportion weight to obtain a regional electromagnetic environment evaluation result. According to the method, the technical problem that a regional evaluation result is not accurate due to the fact that multipath components cannot be separated and single-point data quality cannot be evaluated in traditional mobile patrol is solved.

The invention relates to an industrial code reading control method and a high-speed response system based on device collaborative optimization, and the method comprises the steps: synchronizing image data and three-dimensional coordinates of a plurality of visual devices, and generating a multi-view image sequence with a unified timestamp; extracting two-dimensional bounding box coordinates of the target object to establish a motion trail prediction model; constructing a space projection relation by combining the three-dimensional coordinates of the equipment; fusing the multi-view data to solve the three-dimensional position and attitude of the target object; calculating illumination, object distance and motion blur coefficients in real time based on pose parameters, and dynamically adjusting exposure time, gain and focal length of each device; acquiring an image by using the adjusted equipment, detecting a code system area, and performing geometric correction to generate a standardized image; and outputting a code reading result after decoding. And through multi-device collaborative optimization and dynamic parameter adjustment, the decoding success rate and efficiency under complex working conditions are remarkably improved.

The invention relates to the technical field of unmanned aerial vehicles, and discloses a detection method and an electronic device based on a mooring platform unmanned aerial vehicle, and the method comprises the steps: obtaining visible light, infrared, laser radar, positioning and inertial measurement data; constructing a local geographic coordinate system and realizing space projection and time sequence synchronization of multi-modal data; performing dynamic weighted fusion on each modal feature through a multi-modal cross attention fusion network to generate a high-dimensional semantic feature map; and performing target detection and thermal anomaly discrimination based on the feature map. The electronic device comprises a multi-modal sensing unit, a space-time alignment module, a time synchronization module, a multi-modal fusion module and a target discrimination module. According to the invention, through a unified space-time alignment and adaptive fusion mechanism, high-precision and high-robustness comprehensive detection can still be realized under severe conditions such as dark light, haze or shielding, and long-time stable operation is guaranteed by relying on a mooring platform.

The invention relates to the technical field of construction progress monitoring, in particular to a construction progress multi-dimensional dynamic monitoring method based on the Internet of Things and BIM, and the method comprises the following steps: obtaining a component number and a planned time period through the BIM, collecting an action label, a three-dimensional coordinate and space projection matching time, and generating a component behavior set through DBSCAN clustering; the method comprises the following steps: slicing an action sequence to calculate frequency and coverage proportion; classifying component states to generate progress deviation; matching the deviation with a Hungary algorithm to calculate a coupling map; extracting a mechanical track and path included angle, normalizing and correcting the included angle to generate a deviation sequence, and grading track segments to generate a dynamic monitoring index set. According to the method, time-space association is established based on component numbers and coordinate projection, a classification model is constructed by using time slice coverage to identify progress deviation, task chain coupling is analyzed through bidirectional matching, a deviation sequence is generated through included angle correction, a delay amount and coverage rate evaluation system is established, and progress deviation tracing and abnormal early warning are achieved.

The invention discloses a key structure parameter design method for a main driving bearing of an ultra-large type shield tunneling machine, and relates to the field of design of the main driving bearing of the ultra-large type shield tunneling machine. The key structure parameter design method comprises the following steps: acquiring a rock-soil CT image of a stratum, a crack distribution image and working parameters of the shield tunneling machine, and extracting a rock hardness gradient, a crack direction angle and a soil layer non-uniformity index; generating geologic feature data; establishing a circumferential load prediction model according to the geological characteristic data, and calculating an equal angle value and an overturning moment to obtain dynamic load spectrum data; constructing a contact angle distribution function based on the dynamic load spectrum data, and generating asymmetric contact angle three-dimensional curve data; seamless butt joint with CAM is achieved through space projection transformation, the performance of the bearing is finally embodied, finite element analysis shows that stress distribution is more uniform, the service life of the bearing is prolonged, and cutting force and material loss are reduced through technological parameter optimization.

This application belongs to the field of coherent diffraction imaging technology, specifically disclosing an ultra-low dose coherent diffraction imaging method and apparatus. Based on a blind source separation strategy, this application uses principal component analysis to process the acquired diffraction signals, performing noise separation and updating in reciprocal space. This effectively separates mixed noise energy into noise components, thus avoiding crosstalk to the reconstruction process and significantly improving the convergence stability and robustness of coherent diffraction imaging when reconstructing diffraction signals with extremely low signal-to-noise ratios under ultra-low exposure doses. Simultaneously, this application constructs noise components separately for each scanning position and correlates noise components at different positions through low-dimensional spatial projection, achieving non-stationary noise separation. This enables more effective handling of random noise caused by the low quantum efficiency of ultra-short band detectors, thus maintaining extremely high noise robustness and reconstruction accuracy even under ultra-low exposure doses, achieving an effective improvement in resolution.

This invention discloses a hierarchical continuous attractor network based on intrinsic time constant gradients, belonging to the fields of artificial neural networks and cognitive computing. The network includes a spatial input extraction module, multiple continuous attractor layers, a spatial projection module corresponding to each layer, and a wave packet decoding module. Each layer has a preset and fixed time constant during initialization, and the time constants of each layer monotonically increase from the bottom layer to the top layer. The same external spatial input is projected to each layer in parallel. The bottom layer tracks instantaneous spatial changes with a shorter relaxation time, while the top layer accumulates slowly varying spatial statistics with a longer relaxation time. The cyclic connection weights of each layer are initialized with translation-invariant functions to form a continuous attractor manifold, and are fine-tuned online by superimposing Hebbian enhancement and weight decay. This invention can form multi-timescale spatial representations, improving the stability and precision of representations in high-frequency spatial regions.

The application discloses a kind of variable working condition diagnosis methods of rotary reducer based on multi-view transfer, belong to fault diagnosis technical field.The method is first to the multiple visual vibration data collected is preprocessed and constructs variable working condition data set;Through fourier transform, extract each visual spectrum feature;Typical correlation analysis is used to construct embedding class discriminant transferable feature objective function, combined with maximum mean difference technique reduces the distribution difference between training and testing field, and introduces multi-view consistency constraint;Through generalized feature decomposition, solve common subspace projection, extract multi-view features with discriminant and transferability;Finally, nearest distance classifier is used to realize the fault diagnosis under variable working condition.The application effectively solves the problem that rotary reducer has poor generalization ability due to data distribution difference under variable working condition, improves the accuracy and reliability of fault diagnosis.

The invention provides a vehicle positioning method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining first position coordinates of a target vehicle in a satellite coordinate system at a plurality of different moments in a preset time period through a satellite; through a preset transformation matrix, converting each first position coordinate into a second position coordinate in a pixel coordinate system; based on the projection relation between the target vehicle in the pixel coordinate system and the current driving road, whether the second position coordinate at the current moment is reserved or not is determined; if the second position coordinates are reserved, taking the second position coordinates at the current moment as the position of the target vehicle in the preset time period, so as to display a position identifier corresponding to the target vehicle in a map; and if not, deleting the current second position coordinate. Based on the space projection relation between the vehicle and the road, the vehicle positioning deviation is corrected, so that the vehicle position is accurate, and the vehicle positioning visual display is more accurate.

This application relates to the field of plasma physics technology and provides an asymmetric inversion method and apparatus based on a matching mechanism for plasma diagnostics. The method acquires plasma magnetic flux data, observation lines, and measurement integral values. The magnetic flux data is preprocessed to obtain preprocessed magnetic flux data. Based on the preprocessed magnetic flux data, a closed magnetic surface uniquely matched to each observation line is determined. A lower triangular matrix is ​​constructed based on each observation line and the closed magnetic surface. An inversion equation is constructed based on this lower triangular matrix and the measurement integral values. Finally, the inversion equation is solved to determine the parameter distribution values ​​of the plasma. This method achieves three-dimensional spatial projection of the observation lines and magnetic flux, rapidly determining the position of the closed magnetic surface using geometric relationships, thus improving computational efficiency. Simultaneously, it accurately establishes a one-to-one correspondence between the closed magnetic surface and the observation lines, making the ill-posed problem in solving the matrix equations a unique solution, improving the success rate of solving using the stacking method, and significantly reducing computational errors.

The invention relates to the technical field of mixed reality and immersive display, and discloses an immersive scene experience system and method based on mixed reality superposition projection, and the system comprises an experience module which is formed by a plurality of projection curtains in a surrounding manner, and an experience space is formed in the plurality of projection curtains; the projection module is used for constructing a holographic projection scene; the MR glasses device is used for displaying a virtual image and space interaction; the space positioning module is used for generating a space model and forming an NFC label identifier in the space model; the control module is used for receiving position information of the MR glasses in the projection space; and controlling a playing picture of the projection module and / or the MR glasses device according to the position information. Compared with a traditional mode, the integration degree between the virtual image and the holographic projection scene is higher; meanwhile, the user triggers a virtual event or operates a virtual object in a scene through a gesture, and dynamically adjusts the content of a virtual image according to real-time sensor data, so as to keep synchronization with the action of the user.

The application relates to the technical field of building component detection and provides a building component quality detection method and system. The method comprises the following steps: constructing an M-layer assembled component model group based on construction information; after a first-layer building is formed according to a first-layer model entity ID construction, a real-time model is generated through point cloud scanning; P defects are positioned through space projection comparison of the first-layer model; after dynamic compensation, W defects are positioned through comparison of a second-layer model construction; and the assembled construction and quality detection compensation are recursively executed until the quality detection of the M-layer building component is completed. The application solves the technical problems that the traditional building component quality detection relies on manual measurement, real-time quality monitoring and dynamic compensation cannot be realized layer by layer, defects are accumulated and the detection efficiency is low, and the technical effects that the automatic identification of component quality defects is realized through real-time comparison of a three-dimensional point cloud model, quality defects are dynamically compensated through recursive iteration, and the accuracy and efficiency of building component quality detection are improved.

The invention discloses a method for precisely measuring a workpiece angle based on a laser displacement sensor, and relates to the technical field of workpiece angle measurement, and the method comprises the following steps: building a world coordinate system, calibrating the laser displacement sensor, and recording a zero compensation parameter; planning a scanning path, and collecting three-dimensional coordinate data of non-collinear measurement points on the surface of the workpiece; three non-collinear measurement points are selected to construct a spatial vector; creating a virtual projection plane parallel to the laser axis, calculating a normal vector of the virtual projection plane, and projecting a space vector to the plane; the included angle of the two vectors is analyzed in a projection plane through a formula, and coplanarity limitation is avoided; and outputting an angle measurement result to a human-computer interface to provide a direct basis for subsequent process decision. According to the method, the virtual projection plane is constructed, and the measurement points can be randomly distributed in a three-dimensional space under a space projection analysis mechanism, so that the adaptability of a measurement scene is expanded, the problem of measurement failure caused by workpiece clamping deviation or surface defects can be avoided, and the detection robustness is improved.

This invention relates to artificial intelligence, and particularly to a supply chain demand forecasting method based on condition-guided temporal diffusion and multimodal fusion. The method includes: acquiring multimodal business samples containing historical sales data with missing masks and graphic descriptions; obtaining cross-modal aligned feature vectors through feature extraction and spatial projection to construct a static multimodal conditional representation; under this guidance, performing inverse denoising sampling using a temporal diffusion network to obtain reconstructed temporal features; generating a measure signal to fill uncertainty through multiple sampling variance calculations, inputting it into a dynamic gating network to adaptively allocate fusion weights, and obtaining global cross-modal attribute features; finally, generating demand forecasting results and performing end-to-end training based on a joint loss function of prediction error and diffusion noise prediction loss. This invention effectively overcomes the problems of supply chain cold start and stockout gaps, significantly improving prediction accuracy and model robustness in extremely sparse scenarios.

The application discloses a PCBA foreign matter detection method based on a multi-resolution subspace projection, acquires a to-be-detected board and a standard reference board image, determines an adaptive down-sampling multiple based on a minimum foreign matter physical area, performs image registration with the aid of a mask to eliminate geometric deformation, extracts a multi-resolution feature map through a pre-trained deep convolutional neural network, calculates feature differences, and uses a dynamic threshold to screen a preliminary candidate point set, constructs a local principal component subspace of a local neighborhood of a reference image, performs first-stage screening by calculating the orthogonal projection error of a test feature vector in the space, maps remaining candidate points to a multi-scale feature space and splices them, constructs a global multi-scale principal component subspace, performs second-stage screening through a global projection error, and outputs a final result selection, and through the implementation of the application, the problems of a high-definition image computing power bottleneck and a high false alarm in comparison are solved, the application has zero-sample generalization capability, and sample-free training can accurately detect tiny foreign matters.

The invention discloses a four-dimensional variation assimilation method and system based on hidden space projection and a super set. The method comprises the following steps: projecting a high-dimensional model state to a low-dimensional hidden space by using a pre-trained depth auto-encoder; secondly, generating super set members far exceeding the traditional scale through rapid reasoning of a depth generation model; constructing a flow-dependent background error covariance matrix in the hidden space based on the super set; combining a stream dependent background error with a static statistical background error, constructing a hybrid four-dimensional variational assimilation objective function in a hidden space, and performing optimization solution; and finally, reconstructing the optimal analysis hidden variable back to the original high-dimensional state space. According to the method, the calculation dimension is greatly reduced through the hidden space projection, the flow dependence information is greatly enriched through the super set, the static statistical stability and the flow dependence adaptability are combined through the mixed background error covariance, and therefore the assimilation precision and the forecasting skill are remarkably improved while the calculation efficiency is kept.

The present application belongs to the field of computer vision and artificial intelligence, and particularly relates to a four-dimensional dynamic scene representation and reconstruction method, system and device based on structural equivalence prior, aiming at solving the problems of poor spatio-temporal consistency, large calculation cost and low long sequence reconstruction accuracy in dynamic scene reconstruction. The present application comprises: decomposing the input four-dimensional voxel sequence into multiple two-dimensional feature planes containing spatial projection and spatio-temporal coupling; introducing structural equivalence prior to fuse the plane features, generating unified and continuous spatio-temporal latent space representation by establishing the internal correlation between spatial geometric gradient and time evolution; finally, using a decoding module containing residual connection to decode the latent space representation, and recovering the high-fidelity four-dimensional dynamic scene layer by layer. The present application effectively improves the consistency and accuracy of dynamic scene reconstruction by establishing an explicit spatio-temporal coupling relationship, while taking into account the calculation efficiency, and has broad application prospects in the fields of autonomous driving, augmented reality, etc.

The invention discloses a geographic road network topology consistency self-checking and repairing method based on a multi-mode large language model. The method comprises the following steps: obtaining geographic road network vector data, a high-resolution satellite remote sensing image, a vehicle GPS track sequence and a street view image of a key position of an area to be detected; extracting each modal feature by using a multi-modal encoder, and projecting the modal features to a unified language marking space through a space projection operator to realize semantic alignment; the aligned multi-modal features are input into a multi-modal large language model for self-check reasoning, and a diagnosis report containing road network topology errors is output; converting the diagnosis report into a solution diagram by using the model, and calling a code generation module to automatically write a repair code script; and executing the repair script to modify the road network data, feeding back the modified data to the model for closed-loop verification of anti-factual reasoning and virtual traversal semantic verification, and updating the production library after verification is passed. According to the invention, the accuracy of road network topology automatic repair is improved.

To provide a space projection device which achieves quality improvement in a space projection image.SOLUTION: A space projection device 100 includes: an optical medium 20 for diffusing projection light P1; and a light guide optical system 30 for guiding projection light (space projection light P2) diffused by the optical medium 20 so as to form an image at a space image formation part 40. The light guide optical system 30 includes a retroreflective member 32. The retroreflective member 32 includes a concave-convex structure 320 for suppressing a ghost image M.SELECTED DRAWING: Figure 1