274 results about "Spatial geometry" patented technology

The invention provides a supporting cable production monitoring method and system for 3D visual detection, and relates to the technical field of image processing and intelligent detection, and the method carries out multi-source fusion processing based on collected cable three-dimensional space image data, and comprises coordinate alignment, point cloud reconstruction and multi-scale feature extraction, and construction of a unified space geometric model. On the basis, the center line of the cable is extracted, coordinates of starting and ending points are calculated, and then geometric evaluation parameters such as the axial deviation rate and the straightness are obtained. The method has the advantages of high precision, high robustness and high universality, and is suitable for real-time detection and quality control of slender components such as cables and hoses in the industrial production process. According to the invention, the technical problems of inaccurate three-dimensional structure extraction, insufficient defect identification, difficult defect cause tracing and untimely early warning response in the prior art can be solved.

The invention provides an intelligent actual measurement and quantity management method and system for a building. The method comprises the following steps: capturing environmental parameters, material circulation paths and spatial geometric information of key parts of a building in a construction process in real time to obtain a measurement data set; a distributed ledger technology is combined with a homomorphic encryption algorithm, a graph theory analysis technology is applied to evaluate a dependency relationship among operation points of a construction site, and a data log is generated; according to the data log, using an augmented reality technology to superpose a BIM model, introducing a support vector machine algorithm to carry out automatic classification and risk assessment processing on deviation data between measured data and preset standard data, and generating a rectification suggestion report; and a closed-loop quality management process is formed by continuously collecting rectification effect feedback. According to the technical scheme, high transparency and efficient quality control in the construction process are ensured.

The invention provides an automatic operation process management method and device based on multi-sensor fusion, and relates to the technical field of automatic processes, and the method comprises the steps: constructing an instrument pose flow and operation field geometric model under a unified coordinate system through unified timestamp alignment and spatial geometry solution of multi-source sensor data; semantic segmentation and three-dimensional reprojection are combined to generate a shielding probability graph, cross-channel compensation reconstruction is carried out, and the image integrity is improved. And forming a conflict risk set through voxel field discretization and short-time prediction, and performing combined solution with standardized operation process constraints to generate a scheduling instruction and a safety time window. And finally, mapping the image, the pose and the physiological signal to a knowledge graph, and outputting consistency judgment and deviation correction suggestions in combination with a time sequence attention recognition process node. According to the method, the problem that the operation process management is not accurate enough due to the problems of view overlapping and the like of multi-source sensor data can be solved.

The invention relates to the technical field of three-dimensional modeling, in particular to a three-dimensional modeling system and method based on a laser radar, and the system comprises a point cloud boundary extraction module, a boundary error analysis module, a self-adaptive cutting repair module and a stitching structure optimization module. According to the method, three-dimensional coordinates, normal vectors, reflection intensity, distances and indexes of boundary points are called layer by layer, a Sobel operator and a Canny algorithm are combined to cooperatively recognize a boundary and an error region, then local region repair is completed based on least square plane fitting and spatial residual analysis, a tension vector is analyzed through dynamic planning, and stitching path adjustment is executed. On the cooperative basis of multi-type point cloud features, a spatial topological structure and boundary continuity dynamic modeling, the problems of local damage, connection errors and instable stitching paths of point cloud boundaries in complex scenes are solved, and the integrity of boundary structures, the coherence of stitching transition and the rationality of spatial geometric expression are remarkably improved.

The invention discloses a transformer substation construction site three-dimensional map key feature extraction and topological map construction method. Three-dimensional point cloud data and image data of a transformer substation construction site are acquired; preprocessing the obtained original point cloud data, and removing noise points; point cloud registration is carried out; point cloud registration is realized based on an ICP algorithm; generating a three-dimensional map of the color point cloud; key features of the generated three-dimensional map are extracted based on a Mama algorithm, and a topological map is constructed. The method overcomes the defect that topological relations lack semantic understanding and logic rationality due to the fact that topological maps are constructed only according to point cloud geometric features in the prior art, after the key points are extracted, environmental semantic information and actual application requirements are fully considered, topological mapping is carried out according to the key points, and the topological mapping efficiency is improved. The constructed topological map not only reflects the spatial geometrical relationship, but also can reflect the connection relationship conforming to the actual scene logic, thereby providing more reliable map model support for applications such as path planning, target positioning and the like.

The invention discloses a high-strength steel welding defect nondestructive detection and identification method based on multi-modal data fusion. The method comprises the following steps: welding data acquisition: acquiring a two-dimensional image and three-dimensional point cloud data of a high-strength steel welding part to form a data pair; performing data space alignment: generating a space-aligned image-depth map data pair; feature extraction and fusion: obtaining fusion features with spatial geometric information and two-dimensional visual information through feature extraction and fusion; defect identification and classification: identifying defect pixels, decoding and recovering space information of a defect area, calculating the three-dimensional size of the defect, taking the feature information associated with a connected domain of each pixel with the defect and the three-dimensional size as input, and automatically classifying defect categories through a pre-trained full-connection neural network classifier. According to the method, the welding defects of the high-strength steel can be accurately identified and accurately and quantitatively analyzed.

The invention discloses an artificial intelligence-assisted standard artificial temporomandibular joint automatic placement method. The method comprises the following steps: training a three-dimensional reconstruction model used for extracting a mandible and zygomatic bone zygomatic arch joint prosthesis placement area; based on an improved 3D U-Net neural network, carrying out segmentation extraction on the interested areas of the glenoid fossa and the mandibular branch, and obtaining a space geometric structure for prosthesis installation; the method comprises the following steps: extracting outer bone surface point cloud data of a zygomatic arch and a mandibular ramus on the basis of a space geometric structure of prosthesis installation, identifying anatomical key points, and generating a standard prosthesis fitting surface through geometric fitting and constrained optimization; determining the relative position relation between the maxillary joint fossa prosthesis and the mandibular branch prosthesis, and determining the installation direction, the hole position definition and the assembly reference point; and determining a contact area, a posture direction and a placement position of the prosthesis, and completing three-dimensional positioning and posture matching of the prosthesis in the patient model as a surgical planning scheme.

The invention provides a category-level 6D attitude estimation method based on geometric perception key points, and relates to the technical field of attitude estimation.The method comprises the steps that on the basis that RGB images and point cloud features are fused, a dynamic key point proposing module is designed to generate key points which are consistent in category and geometrically adaptive, so that the adaptability to intra-class deformation and weak texture targets is enhanced; secondly, introducing a spatial geometric attention module to model a spatial structure relationship between key points so as to optimize key point distribution; and finally, point cloud reconstruction and scale regression are simultaneously realized through a geometric perception reconstruction and scale estimation module under the prior condition of no CAD model, and end-to-end optimization is carried out by utilizing multi-task loss. Experimental results on REAL275, CAMERA25 and House Cat6D data sets show that the method provided by the invention is superior to the existing method in multiple indexes such as IoU and attitude precision, and shows stronger generalization and robustness in a real complex scene.

The invention relates to the technical field of automatic feature recognition, in particular to a part space geometric feature and process knowledge automatic recognition reasoning system, which comprises a model acquisition module for acquiring a B-Rep model of a part to obtain triangular patches in each plane in the B-Rep model; the curved surface segmentation module is used for calculating a region attribution degree and dividing a surface into a plurality of sub-regions; the curved surface evaluation module is used for calculating a discrimination coefficient and distinguishing all surfaces into process surfaces and auxiliary surfaces; calculating a coherence evaluation value and structural complexity of each process surface; and the feature recognition and process reasoning module is used for determining the sampling precision of each surface, discretizing the surfaces and the edges, constructing an attribute adjacency graph of coding B-Rep model information, and machining the part based on a machining feature recognition result of the attribute adjacency graph. According to the invention, the processing technology feature identification precision of the part is improved.

The invention relates to the technical field of computer vision and three-dimensional modeling, and discloses a 3DGS (three-dimensional ground structure) equipment monomer method based on dynamic segmentation of an SAM2 large model, which comprises the following steps of: calling a visual large model to segment a multi-view two-dimensional image to obtain a component contour mask bearing semantic information; the method comprises the following steps of: establishing a mask of a three-dimensional point cloud, establishing space mapping of the mask and the three-dimensional point cloud, executing structure segmentation on the point cloud under double dimensions of fusing geometry and semantics, and further generating a three-dimensional monomer model for each separated equipment component. The segmentation processing of the three-dimensional point cloud is no longer limited to fuzzy geometric inference, but is carried out under clear semantic affiliation, so that the accuracy and robustness of monomer separation in the component dense adjacent region are improved.

The invention discloses a transparent glass pose detection method and system based on multi-modal data and a glass grabbing method, and relates to the technical field of glass pose detection. Geometric distortion characteristics of a glass contour are captured by using a camera, a relative pose relationship between the geometric distortion characteristics and a camera plane is analyzed, and a mechanical arm is driven to be roughly adjusted to a roughly parallel pose; based on distance information collected by an ultrasonic sensor array, a glass plane equation is fitted through space geometric solution, the normal vector direction and distance parameters of glass are accurately obtained, and closed-loop fine adjustment of the pose of the mechanical arm is achieved. The detection bottleneck that a transparent medium is difficult to reflect an optical signal is broken through, high-precision pose detection can be realized without installing auxiliary equipment on the surface of the glass, and the damage of a contact mark to the surface of the glass is avoided. The detection reliability is remarkably improved through multi-modal data complementation, meanwhile, a low-cost sensor is adopted to replace high-precision laser equipment, and industrial-grade precision and economical efficiency are both achieved.

The invention provides a line migration and modification scheme optimization evaluation method based on a multi-dimensional constraint condition, and the method comprises the steps: obtaining the position information of an urban underground pipeline, extracting the buried depth of an unlabeled pipeline and an intersection point according to the position information of the underground pipeline, carrying out the labeling, and obtaining the pipeline distribution data containing a three-dimensional coordinate and the buried depth deviation; pipeline horizontal distance information in the preliminarily optimized layering scheme is extracted, whether the distance meets the safety requirement or not is judged through a space geometry algorithm, and if not, horizontal distance parameters are adjusted, and adjusted horizontal distance parameters are obtained; acquiring damage degree data of the protection layer, and if the damage degree exceeds a preset threshold value, establishing a pipeline layout model with real-time response by dynamically updating a vertical layering standard and a horizontal spacing parameter; and according to the optimized pipeline collaborative distribution scheme, calculating a pipeline space utilization efficiency index, and carrying out iterative updating on the pipeline layout model to obtain a pipeline layout optimization result adapted to the dynamic environment.

The present invention relates to a spatio-spectral fusion method for non-paired hyperspectral and SAR images with dual-domain alignment, including: upsampling the hyperspectral image and performing feature extraction, performing Gaussian blur and feature extraction on the SAR image; approximating the radiation distribution of the SAR features to the radiation distribution features of the hyperspectral image; adjusting the spatial geometric information of the SAR features; extracting the change information between the image features, and predicting the low-spatial-resolution hyperspectral image through information injection; fusing the low-spatial-resolution hyperspectral image and the original SAR image after alignment to obtain the final high-spatial-resolution hyperspectral image. The beneficial effects of the present invention are: the present invention improves the spatio-spectral fusion accuracy of hyperspectral and SAR images, providing reliable support for subsequent applications.

The invention discloses a target coordinate positioning system and method based on a multi-view panorama camera, and relates to the technical field of target coordinate positioning, and the method comprises the steps: evaluating the spatial geometrical relationship between different camera units; performing target object detection on the image to obtain an undetermined target object in the image, and screening the undetermined target object in the image in combination with a historical image; evaluating the comprehensive cost between the target object of the image and candidate matching objects in other images, constructing a target cost matrix between the image and other images, and solving the target cost matrix; and according to the target object matching data among the images, performing image feature fusion on the images to obtain a fused image, obtaining and collecting the three-dimensional coordinates of the target object in the fused image to obtain target coordinate data in the fused image, so that more target objects can be detected, and the detection accuracy is improved. And accurate positioning of the target object can be realized.

The invention provides a finite element analysis method and system for geometric design of a flow regulating valve, and relates to the technical field of data processing.The method comprises the steps that 1, spatial geometric feature analysis is conducted on each data point in a discrete contour coordinate dataset, the principal curvature value of each data point on the sealing surface of a metal diaphragm is solved, and the principal curvature value of each data point is calculated; determining a point with the maximum average curvature value on the sealing surface of the metal diaphragm as a core morphology reference point; step 2, establishing a local coordinate system by taking the core morphology reference point as an original point, screening four sealing state points from the discrete contour coordinate data set, solving a corresponding space plane equation, and calculating a space intersection line between the space plane and the sealing surface of the metal diaphragm; according to the method, through accurate positioning of the core reference point, definition of the analysis sub-domain, grid division, mechanical solution, leakage rate calculation and parameter optimization, the dynamic particulate matter problem is effectively improved, and the sealing performance and the micro flow adjusting precision are improved.

The invention provides a GIS buffer generation method and system based on fuzzy semantics and geographic constraints, and belongs to the technical field of geographic information systems.The method comprises the steps that fuzzy descriptors, membership values and geographic entity types are input into a pre-trained language-space mapping model, and basic distance parameters are obtained; querying a spatial database based on the geographic entity keywords, obtaining geometric features associated with the geographic entities, and calculating feature lengths corresponding to the geometric features; correcting the basic distance parameter based on the intention direction, the membership value, the geographic entity type and the feature length expressed by the fuzzy description word to obtain a geographic distance threshold; generating an initial two-dimensional buffer polygon based on the geographic distance threshold and the spatial geometric features of the geographic entity; and querying a digital elevation model to obtain topographic data based on the initial two-dimensional buffer region polygon, and generating a three-dimensional buffer region curved surface through a gradient sensitive interpolation algorithm. According to the invention, the accuracy of generating the GIS buffer area is improved.

The invention provides a five-axis rotary workbench workpiece positioning method and device. The invention provides a method. Comprising the steps that a five-axis rotating workbench is controlled to drive a workpiece to sequentially rotate under different poses, and original workpiece point cloud data under the different poses are collected; determining a plurality of groups of matching point pairs based on a target point cloud and a source point cloud in the original workpiece point cloud data, and registering the source point cloud to a target point cloud coordinate system by using a point cloud registration algorithm to obtain registered workpiece point cloud data in a unified coordinate system; establishing a pose transformation matrix between a camera coordinate system and a five-axis rotary workbench coordinate system by combining mechanical pose information of the five-axis rotary workbench and adopting a hand-eye calibration method based on the registered workpiece point cloud data; and based on the pose transformation matrix, converting the registered workpiece point cloud data into a five-axis rotating workbench coordinate system, and determining the pose of the workpiece in the five-axis rotating workbench coordinate system in combination with the spatial geometric features of the converted workpiece point cloud data.

The invention discloses a nipple protection area three-dimensional reconstruction method and system based on super-resolution, and relates to the technical field of image processing, and the method comprises the steps: obtaining a two-dimensional slice image of a nipple protection area through a medical image device; performing preliminary three-dimensional structure estimation on the two-dimensional slice image to obtain spatial geometric constraints; constructing a super-resolution network based on three-dimensional structure guidance for the two-dimensional image according to geometric constraints; and dense high-precision point clouds are generated through multi-view stereo matching for three-dimensional reconstruction. According to the method, two-dimensional image enhancement and three-dimensional structure constraint are fused through a three-dimensional structure guided super-resolution method, so that the detail information of the image is enhanced while the three-dimensional reconstruction precision of the nipple protection area is improved; and by adopting innovative structure consistency loss and depth constraint loss, the structure continuity and the space consistency of the reconstruction model are effectively improved, and the problem of three-dimensional structure distortion possibly occurring in a traditional method is solved.

The invention provides a point cloud completion method and system based on a high-dimensional feature field and structured tensor decomposition, and belongs to the field of artificial intelligence. Comprising the following steps: encoding geometric information carried by sparse point clouds through a space geometric encoder, and distributing the geometric information to three mutually orthogonal two-dimensional feature planes and a three-dimensional feature grid to jointly form a high-dimensional feature field in which space local information is reserved; for any query point in the space, combining the space coordinates of the query point and the local features sampled in the high-dimensional feature field as input, driving a decoder based on structured tensor decomposition, and reconstructing the geometric attribute value of the query point; a continuous geometric field function implicitly defines a three-dimensional surface after completion, and point cloud completion is completed by sampling the function and extracting a zero contour surface of the function. The technical problems that when sparse and incomplete point cloud data are processed, due to information bottleneck and lack of geometric priori, the complementation quality is poor, and macrostructures and microscopic details are difficult to consider at the same time are solved.

The application discloses a target coordinate positioning system and method based on a multi-view panoramic camera, relates to the technical field of target coordinate positioning, and comprises the following steps: evaluating the spatial geometric relationship between different camera units; performing target object detection on images to obtain to-be-determined target objects in the images, and screening the to-be-determined target objects in the images in combination with historical images; evaluating the comprehensive cost between the target objects in the images and candidate matching objects in other images, constructing a target cost matrix between the images and the other images and solving the target cost matrix; performing image feature fusion on the images according to the target object matching data between the images, obtaining a fused image, obtaining the three-dimensional coordinates of the target objects in the fused image and collecting the three-dimensional coordinates to obtain target coordinate data in the fused image, so that more target objects can be detected, and accurate positioning of the target objects can be realized.

The invention provides an MPM-based three-dimensional slope deformation analysis method and system, and the method comprises the steps: firstly obtaining the spatial geometric structure data of a slope region, constructing a three-dimensional material point model based on the spatial geometric structure data, discretizing a slope material into a material point set containing position coordinates and physical attribute information, and carrying out the discretization of the material point set; establishing a background grid system covering the material point set, then performing interaction calculation on the material point set and the background grid system, solving a kinetic equation on background grid nodes to obtain motion state parameters, mapping the motion state parameters back to material point updating information, generating a material point state set containing deformation characteristics, and finally performing deformation calculation on the material point state set. And finally, based on the position coordinate variable quantity and the physical attribute change parameters in the material point state set, analyzing the deformation trend and the potential instability area of the three-dimensional slope, and generating a slope deformation analysis report containing deformation gradient distribution and a stress concentration area, so that the geometric and stratum information of the slope can be comprehensively considered, and the deformation process can be accurately simulated.

The invention discloses a method for evaluating indoor laser radar scanning mapping precision, and aims to solve the problems that an existing evaluation technology depends on an expensive true value system and precision evaluation is difficult in a large scene. According to the method, complex equipment is not needed, and only several groups of wall surfaces with good parallelism need to be selected in an indoor space conforming to building specifications. A series of space geometric constraints with known true values can be quickly obtained by pasting reflection markers on the wall surfaces and measuring the distance between the parallel wall surfaces by using high-precision distance measuring equipment. According to the method, the process operation is simple, the cost is extremely low, and the mapping precision is accurately evaluated by quantifying the key indexes.

Disclosed in the present invention are a calibration method and calibration system for intrinsic parameters for a workspace measurement and positioning system, comprising: pre-calibrating initial intrinsic parameters of a transmitting station by means of a plurality of photoelectric receiving devices; fixing the transmitting station on a three-axis rotary table, and selecting a control point position for placing the photoelectric receiving device; adjusting the distance between the photoelectric receiving device and the three-axis rotary table multiple times, adjusting the pitch angle of the three-axis rotary table, and recording, by the photoelectric receiving device, a time interval after each rotation; on the basis of changes in distance and time, simulating the initial intrinsic parameters, and obtaining the deformation situations of light planes; and on the basis of the obtained deformation situations of the light planes, re-calibrating the transmitting station, calculating spatial geometric parameters of each light plane under a transmitting station coordinate system, and obtaining intrinsic parameters under a new model. In the present invention, the profile of a light plane mounted on the transmitting station is first calibrated by means of the high-precision three-axis rotary table, and then a proper light plane model is selected to fit an actual laser surface, thereby improving the angle measurement and coordinate measurement precision of the workspace measurement and positioning system.

The invention discloses an intelligent control method of a numerical control dotting and ruling machine for mold machining, and particularly relates to the field of numerical control machining control. The method comprises the following steps: establishing a three-dimensional point cloud model containing surface microscopic curvature distribution and a local stress-strain relationship by acquiring a space geometric model and material physical parameters of a target mold workpiece; performing grid division on the point cloud model, extracting curvature features and local elastic modulus of each grid unit, and constructing a parameter matrix; in combination with the initial track of the preset tool path, modulating by adopting a self-adaptive control algorithm to generate a corrected path; in the machining process, a control vector is constructed based on the corrected path and the dotting depth and the scribing force which are fed back in real time, an execution mechanism is driven to conduct closed-loop control, and dynamic compensation of each dotting and scribing action is achieved; the method can effectively solve the problems of uneven dotting depth, lineation deformation and quick tool abrasion in the machining process of complex curved surfaces or high-strength materials, and the machining precision and stability are remarkably improved.

The invention discloses a roller rotating speed detection method and system based on an optical flow method. According to the scheme, on the basis of organic fusion of two-path image optical flow analysis and spatial geometry modeling, the detection of the rotating speed of a roller is realized under the condition of not depending on a physical sensor or any physical mark; non-contact detection is carried out on the rotating speed of the coal mining machine roller in the underground coal mine directly based on the operation video image of the coal mining machine roller, and the efficiency of high robustness and friendly visualization can be achieved.

The invention relates to a collision detection processing method and device, equipment and a medium. The method comprises the following steps: in response to a collision detection event triggered in a game scene, determining a first time window corresponding to the event based on a first thread; on the basis of a first timestamp corresponding to the first time window, acquiring spatial geometric information corresponding to all colliders contained in a detection range corresponding to the collision detection event; the second thread performs collision detection on each collision body according to the spatial geometric information, and returns a corresponding collision detection result to the first thread; and in response to a trigger event that the first time window reaches the second time stamp, the first thread determines whether collision occurs between the colliders based on the collision detection result. According to the method and the device, the collision detection calculation task is separated to the independent threads to be executed at the first timestamp, and the collision detection result is uniformly processed at the second timestamp, so that the accuracy and the stability of collision judgment logic are ensured while the game running efficiency is remarkably improved.

The invention relates to the field of geometric error correction, in particular to a space geometric error measurement method and device for correcting a motion platform in real time. The method comprises the following steps: carrying out space geometric correlation analysis and standard space coordinate system drawing-up based on the sensor array; carrying out motion platform measurement based on the standard space coordinate system, and carrying out sampling time difference elimination processing to generate a time sequence synchronization data stream; performing motion platform space pose deviation calculation based on the time sequence synchronization data stream to obtain a six-degree-of-freedom comprehensive error vector; error source separation is carried out based on the six-degree-of-freedom comprehensive error vector, error compensation calculation is carried out, and an error source correction library is constructed; and performing multi-axis linkage error compensation according to the error source correction library to generate a geometric error compensation report. According to the invention, through real-time calculation and correction of the pose error of the motion platform, the measurement precision of the motion platform is improved.

The invention provides a method for intelligently extracting key geometric features of a target object through a three-dimensional laser scanner, and belongs to the technical field of actual measurement of an internal forming surface of a wind tunnel body. Constructing an association degree matrix by using a minimum spanning tree algorithm in a graph theory, calculating three clustering center values based on K-means clustering analysis, determining a boundary threshold value, starting a scanning precision adaptive strategy, dynamically adjusting scanning parameters through a feature extraction optimization model, extracting key geometric features by using a geometric feature recognition algorithm, and carrying out feature extraction on the key geometric features; spatial context information is automatically extracted by using a Transform attention mechanism, and finally a key geometric feature extraction result of the target object is output through sequential processing of six parallel computing units, so that the technical problem of insufficient geometric feature extraction precision of three-dimensional laser scanning point cloud data in a complex environment is solved.

The invention relates to the technical field of defect detection imaging, and discloses a high-precision three-dimensional imaging method and system based on continuous magnetic flux leakage data. Collecting surface magnetic flux leakage signals of a measured target to form an initial signal set, and extracting feature vectors by using a convolutional neural network model; separating three-dimensional space data, and obtaining initial three-dimensional position coordinates of the defect through an iterative mapping algorithm; mining spatial geometric features, determining potential geometric boundaries, and fusing data to construct a refined position model; extracting a detection subset, correcting a shape error, constructing a space reconstruction grid, filling holes, and obtaining a complete three-dimensional shape representation; and through precision calibration and signal matching verification, a high-precision three-dimensional image is output. According to the method, the defect positioning and shape reconstruction precision can be effectively improved, the imaging integrity and accuracy are guaranteed, the problems of fuzzy positioning and shape distortion of traditional magnetic flux leakage imaging are solved, and the defect detection requirements of a complex detected target are met.

The invention provides a ground laser positioning mountainous area multi-machine lifting cooperative control method and system, and relates to the technical field of cooperative control, and the method comprises the steps: 1, calculating a first real-time pose of an aircraft through a laser positioning signal transmitted by a laser positioning base station; according to the image data of the three optical identification points, calculating spatial three-dimensional coordinates of the three optical identification points to define a spatial geometric curved surface patch, and decomposing the curved surface patch into a strong signal manifold and a weak signal homotopy group; 2, taking the optical identification point of the central point of the upper edge of the front end surface of the load structure as a spatial reference origin, and connecting the two optical identification points of the left vertex and the right vertex of the lower edge of the rear end surface to form a first spatial vector and a second spatial vector; through laser positioning signal partitioning, load pose multi-source fusion optimization and dynamic compensation control of the Lyapunov potential function, the method adapts to signal shielding and attenuation scenes of mountainous complex terrains, inhibits load swing, reduces the risk of obstacle scraping and collision, and improves the safety of multi-machine lifting.