194 results about "Rasterisation" patented technology

The invention discloses a Gaussian representation SLAM method based on dense matching priori and factor graph constraint, which comprises the steps of inputting a current image and a key frame image, outputting a point graph corresponding to the image through a pre-trained model, returning a matching condition of two frame image points and respective point cloud information, and obtaining a point-level matching result based on a point-level matching result. The method comprises the following steps: constructing a joint optimization problem of a current frame and a key frame by taking a luminosity consistency error and a geometric projection error as targets, performing joint estimation on a camera pose and a point cloud of the current frame, realizing high-precision pose solution, generating point diagram data after Gaussian scene representation and rasterized rendering processing, and transmitting the point diagram data to a rear end for global optimization. And the rear end receives the pose and point cloud data, executes loopback detection to identify repeated key frames, and performs Gaussian rendering through an optimized key frame image to complete global dense three-dimensional reconstruction. The method effectively solves the problem of track drift and scene inconsistency caused by lack of pose priori and global geometric constraints in an existing system.

The invention provides a path planning method, electronic equipment and a computer program product. The intelligent agent realizes path planning based on a pulse neural network of width, and the path planning method comprises the steps that a target area is divided based on environment information of the target area and an optimization target, a rasterized map composed of different sub-areas is determined, the optimization target comprises calculation efficiency and environment adaptability of the intelligent agent, and the rasterized map is determined based on the calculation efficiency and the environment adaptability of the intelligent agent. Each sub-region corresponds to one pulse neural network sub-node, and the rasterized map comprises a starting point position, an ending point position and obstacle information; based on the environment feature vectors of the sub-regions of the rasterized map and the position information of the intelligent agent, the current state of the intelligent agent is determined, and the current state is determined based on the Markov decision process; and based on the current state of the intelligent agent and a path planning algorithm, performing path planning on the rasterized map, and determining a planned path.

The invention relates to the field of PCB detection, in particular to an AOI detection data processing system and method for a PCB, and the system comprises a visual processing module, a contour recognition module, a PCB alignment module, a region aggregation module and a defect detection module, the visual processing module is used for rasterizing each image pixel point, the contour recognition module is used for detecting a communication contour of the PCB, and the PCB alignment module is used for aligning the PCB alignment module. The PCB alignment module is used for aligning a PCB image with a standard image, the area aggregation module is used for identifying a defect view field and judging a qualified state, and the defect detection module is used for establishing a reinspection path and outputting a block defect rate. Production defects can be found in time, the probability of missing detection and false detection is reduced, the production quality of the PCB is improved, stable operation of an AOI system in a production environment is guaranteed, and the detection efficiency and accuracy are improved.

According to the intelligent navigation method and device for the inspection robot, a map fusion system is innovatively designed, and the environment is effectively expressed through multi-source data and rasterization processing. And an environment perception mechanism is constructed, and a reliable obstacle recognition model is established in combination with semantic analysis and trajectory prediction. Dynamic planning is introduced, and the accuracy of obstacle avoidance is ensured through interference analysis and state optimization. According to the method, the defects of the traditional technology in the aspects of map fusion, environment perception, dynamic planning and the like are effectively overcome, and technical guarantee is provided for the inspection robot.

The invention provides a document image-text integrated intelligent understanding and processing method and system, and relates to the technical field of artificial intelligence. Comprising the following steps: separating image-text elements and establishing context association; calling a graph vectorization engine, and executing intelligent vector conversion processing on the rasterized illustration; performing hierarchical classification, attribute endowing and structured reconstruction on the vector primitives in combination with text semantic analysis to generate vector entity objects with complete attributes; the text elements and the vector entity objects are jointly input into a pre-trained multi-mode large language model, unified knowledge expression containing vectors, topology, attributes and document contexts is generated, and applications such as question answering, editing, abstracting and reporting of image-text integration are supported. According to the method, the problems of graph semantic loss, difficulty in fine analysis and the like caused by vector-to-grid illustration in papers, reports and other types of documents are solved, the overall understanding depth and interpretability of AI for complex image-text documents are remarkably improved, and high-performance semantic understanding capacity is provided for document-based training and intelligent processing.

The invention relates to the technical field of numerical control machining measurement and correction, and discloses a machining surface correction method for a numerical control milling center. The method comprises the steps of establishing an original point cloud of a processing surface and extracting a feature structure; analyzing each feature structure to form a structured description list; inputting the list into a geometric growth model, and generating a virtual feature structure set according to rule iterative evolution; extracting and rasterizing the contour and the height field, carrying out registration fusion with a reference plane equation, and carrying out variation calculation to obtain a smooth middle geometric surface; performing adaptive resampling on the intermediate surface to generate an intermediate point cloud; and finally, according to the spatial frequency distribution of a topological residual field formed by the difference between the original point cloud and the intermediate point cloud, adaptively determining a weight, and carrying out weighted mixing on the original point cloud and the intermediate point cloud to generate an optimized surface point cloud. According to the method, intelligent evolution of the machined surface features and frequency domain self-adaptive data fusion are achieved, and the correction machining precision and the surface forming quality are improved.

The invention discloses a new energy station operation index multi-dimensional comparative analysis display method and system, and belongs to the field of new energy station operation management and data analysis. The method comprises the following steps: fusing and standardizing multi-source heterogeneous data, collecting and cleaning multi-station data, and classifying and storing the multi-station data as a standardized data pool; rasterized multi-dimensional indexes are calculated, grids are divided, data are mapped, and grid-level and hierarchical multi-dimensional indexes are generated; performing dynamic weight and TOPSIS evaluation, constructing an evaluation model to calculate the score of a single station, extracting a core index intersection, and transversely comparing the ranking of the stations; the evaluation result is subjected to instantiation storage and hierarchical storage to guarantee data query and tracing; and performing multi-dimensional visual display, displaying the data by multiple terminals, and generating a decision report. The system comprises corresponding function modules. According to the method, the problems of data fragmentation, evaluation system deficiency, non-visual display and the like are solved, multi-station data integration, quantitative evaluation and visual decision making are realized, and the operation management efficiency is improved.

The invention discloses a rural residential area automatic layout method based on shape grammar and multi-objective optimization, and the method comprises the steps: firstly constructing a rasterized construction cost surface based on the slope data of a research area, a basic farmland protection area vector and an ecological protection red line vector, and then constructing a rasterized construction cost surface based on a traditional residential building sample library and survey data; a shape grammar rule base including a building foundation, courtyard topology, residence number configuration, style and feature control and public service facility coverage is constructed, rule parameters are iteratively optimized by taking a land intensification degree, an ecological interference degree, a style and feature coordination degree and a service coverage degree as optimization targets, an optimal solution set is obtained, and finally, a construction cost surface is taken as a guidance, so that the construction cost is optimized. Performing layout generation in the low-cost constructable area according to the optimal solution generation; according to the technical scheme provided by the invention, a high-implementability rural residential area layout scheme with intensive land utilization, ecological protection and regional style and appearance coordination can be generated under various natural and policy constraint conditions, and the layout generation efficiency is improved.

The invention discloses an indoor point cloud wall face segmentation method based on density constraint super voxels, and belongs to the technical field of point cloud data processing and three-dimensional space data analysis, and the method comprises the following steps: collecting point clouds, removing invalid points, dividing structural point clouds through a normal vector and a gravity direction pair included angle, and obtaining an included angle; the method comprises the following steps: obtaining a primary wall point cloud set through rasterization and combined constraint of density constraint and height constraint, optimizing super voxel segmentation by adopting an energy function, completing initialization, seed screening and adjacency relation construction, performing iterative growth and traversal screening by taking a super voxel with the minimum curvature as a seed to obtain a super voxel cluster, and obtaining an initial wall point cloud set; and finally, outputting a complete wall point cloud through binary mask expansion, label updating and point cloud elimination. According to the method, the phenomena of wrong segmentation and missing segmentation can be effectively inhibited in a complex indoor scene, and the method is suitable for point cloud wall segmentation of a multi-wall and multi-scale structure.

The invention discloses a global path planning method for a power converter valve inspection operation robot, and the method comprises the steps: obtaining the spatial point cloud data of a converter valve region through a three-dimensional structured light camera, and constructing a two-dimensional environment map containing obstacle expansion information through projection and rasterization; generating a snakelike or spiral full-coverage global theoretical path according to the scanning step length of the camera; in the inspection execution process, the feasibility of the path section is judged through discrete sampling and continuous collision detection; local obstacle avoidance adopts an improved A * algorithm, forward and backward bidirectional search is simultaneously executed in a limited local search area, and a dynamic heuristic function of a coverage potential item and a safety score item is introduced. And finally, splicing the local path and the theoretical path to form a global feasible inspection path. The method effectively solves the problem that the coverage rate and the obstacle avoidance efficiency are difficult to consider in a complex converter valve hall environment in a traditional method, and is particularly suitable for automatic inspection of equipment-intensive scenes such as an electric power converter valve hall.

The invention discloses a robot sensing method based on field landform semantics and topographic geometric features, and the method comprises the steps: firstly building and training a semantic segmentation network, and obtaining the semantic information of each landform in an environment; and laser point cloud information is obtained. Secondly, fusing landform semantics with laser radar point cloud information to obtain semantic point cloud, rasterizing the semantic point cloud, determining semantic features of grids according to semantic information in the semantic point cloud after rasterizing, and constructing a semantic feature cost map and a terrain geometric cost map; and finally, based on the terrain geometric cost map, tracking the change of the dynamic obstacle in time by using a ray tracing method, eliminating false height caused by the dynamic obstacle, fusing the semantic feature cost map and the terrain geometric cost map by using an environment traffic cost model, and quantifying the traffic cost of each position in the field complex environment. According to the invention, the robot can better understand the field environment, and the perception is more accurate.

The invention provides a vehicle turning path planning method and device for irregular land parcels, and is applied to the technical field of path planning, and the method comprises the steps: carrying out the initialization of a pheromone field based on the boundary data of a geographic information system and internal obstacle data, and constructing a rasterized map for representing a passable region; based on the current state of the vehicle, determining the minimum distance of obstacles in the surrounding environment of the target vehicle; based on the real-time movement speed, the minimum turning radius of the target vehicle is determined; determining a dynamic corridor parameter of the target vehicle based on the minimum distance and the minimum turning radius of the surrounding obstacle; based on the dynamic corridor parameters and the pheromone field of the rasterized map, generating a turning point probability density field of the target vehicle, and sampling the turning point probability density field to obtain a turning point set; and constructing a turning path of the target vehicle based on the turning point set, and determining the turning cost of the turning path. According to the invention, Pareto optimization of energy consumption and efficiency in a complex scene can be realized.

The invention provides an unmanned field sugarcane concentrated transportation vehicle operation path planning method and system, and belongs to the technical field of farmland operation path planning, and the method comprises the steps: obtaining a marked aerial photography field image; constructing a grid map boundary environment model by marking edge detection and boundary extraction of an aerial field image, graph completion and rasterization processing; on the basis of an expansion algorithm, obstacle pixels in the grid map boundary environment model are traversed through structural elements, and a regularized obstacle contour aligned with the grid boundary is generated; constructing a grid map based on the grid map boundary environment model and the regularized obstacle contour; and on the basis of a semi-spring artificial potential field method and an A * algorithm, according to obstacle distribution, topographic features and operation targets in the grid map, generating an optimal path satisfying the operation of the sugarcane concentrated transportation vehicle. According to obstacle distribution, topographic features and operation targets, mechanical limitation of the minimum turning radius is taken into consideration in path planning, meanwhile, path optimality is guaranteed, errors are reduced, and the transportation efficiency and operation safety of the sugarcane concentrated transportation vehicle are improved.

The invention discloses an unmanned aerial vehicle autonomous navigation system based on a rasterized world model, and relates to the technical field of unmanned aerial vehicle control. According to the system, observation information of an unmanned aerial vehicle is input into a trained rasterized world model through an observation acquisition module; through cooperative work of a sequence model, a multi-modal self-encoder, a hidden space dynamics predictor, a multi-modal information prediction head and a grid predictor in a rasterized world model, a cyclic variable containing historical information, a prediction hidden state vector and a prediction local grid map are provided for an agent model. And action decision making is carried out based on the data through an intelligent agent model so as to accurately output the actions of the unmanned aerial vehicle. According to the system, by introducing the rasterized world model, multi-modal observation information can be effectively fused, and a three-dimensional structure of a local environment is predicted in real time, so that the spatial perception capability of an intelligent agent model to a complex environment is enhanced, and the decision-making performance of the intelligent agent model is improved.

The invention relates to the technical field of geographic multi-dimensional data management, and provides a rasterized geographic information construction method based on Gaussian projection, which comprises the following steps: carrying out zoning projection processing on the earth surface, and converting a geodetic coordinate system into a rectangular plane coordinate system by adopting Gaussian-Kruger projection; further dividing the projection zone into a plurality of longitude and latitude zones, and distributing a unique identifier EarthID for each longitude and latitude zone; in each latitude and longitude zone, taking the central point as a reference, and calculating the offset Axoffset and Ayoffset of the grid in the latitude and longitude directions; the position of each grid is uniquely determined according to the EarthID, the Axoffset and the Ayoffset; grid coordinates are converted into geodetic coordinates through an inverse calculation method, and visual display of the grids on the map is achieved. According to the method, the problems of unified expression, efficient management and flexible application of the multi-scale geographic space data are effectively solved, and powerful technical support is provided for space-time big data analysis in the fields of smart cities, traffic planning, emergency command and the like.

A system generates initial Gaussian elements defined by parameter sets that include, for each Gaussian element a spherical harmonics (SH) coefficient array, a learnable parameter vector, and a learnable weight vector. The system performs a training process comprising rasterizing current Gaussian elements to generate a rendered image of the scene as viewable from a current camera position, wherein for each Gaussian element of the current Gaussian elements that intersects the camera ray, the system determines an opacity value for a location based on a view-dependent scaling value that depends on the current camera position, a position vector, and the learnable parameter vector.

The subject technologies relate to rasterizing depth in Gaussian Splatting. An example method facilitates rasterizing depth in Gaussian Splatting and includes rasterizing a depth map associated with a group of Gaussian splats representative of a three-dimensional object, the rasterizing of the depth map including determining spatially varying depths within a Gaussian splat of the group of Gaussian splats. The method further includes rasterizing a surface normal map associated with the group of Gaussian splats, and reconstructing a three-dimensional model of the three-dimensional object based on the depth map and the surface normal map associated with the group of Gaussian splats.

Methods and systems for identifying stormwater management opportunities in accordance with embodiments of the invention are disclosed. In one embodiment of the invention, a method for identifying stormwater management opportunities comprises gathering spatial data for a region; rasterizing the spatial data into a set of raster data layers; forming a plurality of benefit maps using subsets of the set of raster data layers, wherein the plurality of benefit maps corresponds to a plurality of benefit categories; generating an opportunity map by combining a subset of the plurality of benefit maps using weights corresponding to the plurality of benefit categories; and displaying the opportunity map on a user interface.

The application relates to a camera perception range generation method for a target detection task, which establishes a pinhole imaging camera model containing camera distortion, a target model and a target field of view environment plane model, and is divided into a standard version and a simple version according to application needs. In the standard version, a gridded target is projected into an image to generate a target bounding box, a target detection minimum bounding box threshold is set, and the perception range of the camera is drawn based on the threshold; in the simple version, the camera model is simplified, and the perception area is generated according to the effective detection range expression of the simple model. The camera effective perception range generation method designed by the application can quantize the effective pixel threshold value of the target detection algorithm into the perception range under the camera field of view plane, select the standard and simple models according to application needs, draw the perception area of the camera according to the camera internal and external parameters, improve the camera installation and arrangement efficiency, and effectively guide personnel to select and install the camera according to the target detection demand.

The invention relates to the technical field of field intensity prediction, in particular to a medium-wave broadcast-based field intensity prediction method and system, and the method comprises the following steps: obtaining the environment space information of an emission source for medium-wave broadcast, and constructing an environment model of the emission source based on the environment space information; rasterizing the target area of the emission source based on the prediction model to form a plurality of grid receiving points; predictive control information is configured for the emission source based on the predictive model, and the predictive control information comprises a vernier and a selection frame chain corresponding to the vernier; driving the verniers to sequentially move in the target area along the propagation direction; the field intensity value of the vernier at each position is predicted based on the selection frame chain of the vernier, the grid points meeting the preset field intensity condition are connected to form the field intensity range contour, the field intensity range and the field intensity values of the grid points in the field intensity range are output to serve as the final prediction result, and the accuracy of field intensity prediction can be effectively improved.

The present disclosure relates to a map processing method and device in a simulation system and electronic equipment, and belongs to the technical field of map processing. The map processing method in the simulation system comprises: acquiring a map in at least one format; processing the map according to a rasterized map format to obtain a target map; the rasterized map format comprises a topology layer and a geometry layer; the topology layer comprises a logical structure of a road, and the road comprises a plurality of lanes; the geometry layer comprises a geometry shape description of the plurality of lanes; and the target map is imported into an automatic driving simulation system for automatic driving simulation task processing. The present disclosure can realize fast import and lightweight operation of a third-party map.

The embodiment of the invention discloses a display device and an image drawing method, and the method comprises the steps: responding to an image display instruction, creating a background canvas according to a preset layout and a preset number of rows and columns, and calculating the size and position coordinates of a grid in a to-be-drawn grid; according to the size and position coordinates of the checks in the to-be-drawn grid, a plurality of checks matched with the preset row and column number are drawn on the background canvas, and a grid canvas is generated; a target image indicated by the image display instruction is zoomed to obtain a first image, and the size of the first image is an integral multiple of the size of the grid; partitioning the first image to obtain a plurality of image blocks in rasterized distribution, the image blocks having the same size and shape as the checks; obtaining a to-be-filled image block in the pattern area of the first image; mapping the to-be-filled image block to the grid canvas to obtain a to-be-filled grid mapped by the to-be-filled image block; and after filling the to-be-filled grids, displaying a grid image so as to complete the grid transformation of the image.

The application discloses a weak coverage area grid clustering method and device, and the method comprises the following steps: performing slicing processing on a raster map to obtain a plurality of map slices; calculating the weak coverage probability of each map slice; screening the map slices to be clustered from the plurality of map slices according to the weak coverage probabilities of the plurality of map slices, performing clustering processing on the grids in the map slices to be clustered to obtain a weak coverage clustering cluster; collecting the update coverage data corresponding to the plurality of map slices, and updating the raster map according to the update coverage data and the weak coverage clustering cluster. The application realizes the management and processing of different slices by screening the map slices to be clustered, and does not need to perform complete traversal clustering and updating on the entire raster map, thereby saving the computing resource, effectively improving the update speed of the raster map, and solving the problems that the current clustering operation requires a large computing power and the real-time update map operation consumes a large amount of resources.

The application discloses a safe landing area detection method, device, equipment, medium and product of a UAV, relates to the field of autonomous navigation and safety of a UAV, and comprises the following steps: inputting a visual image into a monocular metric geometry estimation model to obtain metric point cloud data, a surface normal and an effective mask in a camera coordinate system, and transforming the metric point cloud data, the surface normal and the effective mask into a world coordinate system according to pose information; filtering the effective mask to obtain effective point cloud; when the number of the effective point cloud meets a threshold value, performing rasterization processing to obtain a grid unit and calculate geometric features; inputting the visual image into an instance segmentation model to obtain a dangerous area mask, and mapping the dangerous area mask to each grid unit, and combining the geometric features and a ground reference height to determine a safety probability; determining an optimal landing area based on the safety probability, and calculating the center coordinates and the radius of the minimum circumscribed circle of the optimal landing area. The application improves the autonomous safe landing capability of the UAV in an unknown complex environment.

The invention discloses a method for rapidly identifying and positioning a vacuum film air leakage point in vacuum preloading engineering based on artificial intelligence assistance. The method comprises the steps that S1, system initialization and self-inspection are carried out; s2, the unmanned aerial vehicle adopts a rasterized route to cover the whole vacuum preloading site, and cruises the whole area through a back-and-forth parallel sweeping method; s3, sound signals are collected in real time through an audio collection module, and the collected sound signals are uploaded to a signal processing unit; s4, preprocessing sound data, extracting an MFSC coefficient from a preprocessed sound signal, inputting the MFSC coefficient into the well-trained convolution-cycle-attention mechanism hybrid neural network model, and distinguishing gas leakage sound and noise; s5, when the signal processing unit detects suspected air leakage sound, triggering the unmanned aerial vehicle to hover and circle, further determining the position of an air leakage point by utilizing array orientation, and then performing film repairing; meanwhile, the ground monitoring station receives the position and air leakage alarm information of the unmanned aerial vehicle in real time and visually displays the information on an interface.

The application relates to an artificial intelligence technology and discloses a building construction method based on a BIM technology, which comprises the following steps: extracting a building image feature set of images in an original building image set based on a gray level co-occurrence matrix algorithm and a wavelet transform method; performing type clustering on the building image feature set by using an alternating optimization clustering algorithm; labeling the clustering results based on cable information to obtain a standard building image clustering set; performing rasterization processing on a target building image; matching a target rasterized image with a clustering cluster in the standard building image clustering set; selecting a target cable from the labels corresponding to the clustering cluster that succeeds in the matching; performing cable path planning in the target rasterized image based on the target cable by using an improved ant colony algorithm; and arranging the target cable according to the path planning result. The application further discloses a building construction device based on the BIM technology and electronic equipment. The application can improve the efficiency of cable arrangement.

The invention relates to the technical field of thermal printing equipment control, in particular to a dynamic temperature-adjusting thermal printing method and equipment based on an upper computer and a USB bridging chip. The method comprises the steps that original printing content and operation parameters are obtained, field naming standardization, data type unification and default value filling processing are carried out, and a standardized structure is generated; based on the bound physical resolution of the printing head, configuring a rasterization step length and a line buffer size, and generating a printing dot matrix and a basic control parameter set; the concentration, the temperature, the speed and the voltage are correlated and sorted, a temperature adjusting field is generated, and a control signal sequence and dynamic pulse width configuration are obtained through dynamic pulse width calculation; and finally, configuring USB-to-GPIO bridging chip pin mapping, initializing a bus session, setting an output mode, and generating an updated operation parameter set. Fine dynamic temperature adjustment of the printing head is achieved, the printing quality consistency and the equipment reliability are effectively improved, overheating damage is avoided, meanwhile, the hardware architecture is simplified, and the cost is reduced.

This invention relates to the field of vibration reduction control technology, specifically to an online adjustment method for wheel hub vibration reduction based on multi-source sensor data fusion. The method includes: simultaneously acquiring and aligning image sequences and point cloud data of the road ahead using visual sensors and lidar; constructing a rasterized elevation model using a terrain segmentation algorithm to extract road surface geometric features; generating a multi-source physical state matrix by combining vehicle dynamic parameters acquired by an inertial unit, and inputting this matrix into a classifier with an embedded spatiotemporal cross-attention mechanism to output driving scenario commands; triggering an electromagnetic adjustment link for flat road conditions, and optimizing motor control parameters online through a PID parameter mapping network; and triggering a mechanical compensation link for pulse impact road conditions, simultaneously outputting suspension damping coefficients and motor reverse compensation torque commands through frequency domain decoupling calculations, thus achieving dynamic adaptive vibration reduction in all scenarios.

This invention relates to the field of image processing technology, and particularly to a method and system for detecting surface defects in parts based on image processing. The method includes: acquiring a physical image of the part to be tested; performing a reverse indexing of design data using the product manufacturing code to obtain a vector design file; performing pixel-level raster rendering of the vector design file to generate an ideal marker image; completing deformable elastic registration between the ideal marker image and the physical image to obtain an elastic deformation field and a marker region mask; performing global anomaly semantic interpretation on the physical image; obtaining candidate domains for defects in the marker region through cross-domain filtering; stripping the candidate domains to obtain connected domains for defects in the unmarked region; performing inverse deformation mapping of the connected domains of the candidate domains based on the elastic deformation field; measuring the local similarity with the ideal reference domain to obtain the local fit; comparing with a preset judgment threshold to identify character defect information; marking connected domains that do not meet the threshold as surface defect connected domains; and merging the two types of defect connected domains to obtain the surface defect detection result.

The application discloses a kind of global path planning methods for power converter valve inspection operation robot, obtains the spatial point cloud data of converter valve area using three-dimensional structured light camera, constructs two-dimensional environment map containing obstacle inflation information by projection and rasterization;According to the snake shape or spiral shape global theoretical path of full coverage generated by camera scanning step;During inspection execution, the feasibility of path segment is judged by discrete sampling and continuous collision detection;Local obstacle avoidance uses improved A* algorithm, simultaneously executes forward and backward bidirectional search in the limited local search area, and introduces the dynamic heuristic function of coverage potential item and safety score item.Finally, the local path and theoretical path are spliced, and the global feasible inspection path is formed.The application effectively solves the problem that the coverage rate and obstacle avoidance efficiency of traditional method are difficult to consider under complex converter valve hall environment, and is especially suitable for automatic inspection in equipment-intensive scenes such as power converter valve hall.