1180 results about "Control point" patented technology

The invention discloses an intelligent optimization method based on lightweight language training data, which comprises the following steps of: constructing a self-attention mechanism by using a Transform architecture, giving an embedding matrix of an input sequence, n being the sequence length, d being the embedding dimension, representing Query, Key and Value matrixes, and controlling the product magnitude by using a scaling factor; a low-rank adapter is added beside an original weight matrix, a parameter update quantity is decomposed into a product of two small matrixes, and the original weight matrix is a sum of two low-rank matrixes introduced by LoRA. According to the method, an end-to-end personalized dialogue memory system is constructed based on a MiniMind framework, dynamic internalization and accurate recall of user habit information are realized on the premise that a local vector knowledge base does not need to be constructed through organic integration of a supervision fine tuning strategy and a LoRA technology, a dialogue memory coding mechanism is designed, and the memory efficiency is improved. User interaction data is directly mapped into an implicit memory unit of a model parameter space, a lightweight memory trigger-retrieval protocol is developed, key features are extracted through dialogue context, and long-term memory response is activated.

The invention relates to the field of navigation, and more particularly discloses a gradient optimization driven unmanned aerial vehicle real-time obstacle avoidance multi-stage trajectory planning method, which comprises the following steps of: in a trajectory initialization stage, firstly, searching a collision-free geometric path considering steering limitation of an unmanned aerial vehicle on an occupied grid map by utilizing an improved algorithm to generate an initial B-spline control point; then, in a trajectory optimization stage, constructing a multi-target trajectory optimization problem, introducing an obstacle avoidance constraint based on an Euclidean distance field map, and optimizing the initial control point set in combination with unmanned aerial vehicle parameters and optimization weights to obtain a trajectory meeting an obstacle avoidance requirement; and finally, for the optimized trajectory, performing dynamic feasibility evaluation based on unmanned aerial vehicle kinematics limitation in a trajectory correction stage, and if the trajectory does not meet the constraint, performing correction based on the minimum curvature constraint on the control point to ensure that the finally generated trajectory is not only obstacle-avoiding but also feasible in dynamics, and finally, determining that the trajectory does not meet the constraint. Therefore, the real-time obstacle avoidance capability of the unmanned aerial vehicle in a complex environment is effectively improved.

The invention relates to the technical field of three-dimensional modeling in engineering surveying, in particular to a point cloud building component modeling method and system based on feature extraction. Three-dimensional point cloud data of building components are obtained, a multi-scale local neighborhood calculation covariance matrix is constructed with each point as the center, eigenvalues are decomposed, an edge probability graph is generated, corresponding component categories are semantically output, and corresponding key feature point sets are screened; taking the feature point cloud as a control point, constructing a three-level B-spline surface model, and adjusting the corresponding spatial distribution density; a weighted complete graph is formed through a key feature point set, a non-planar area is identified and processed through a Kurtowski theorem, a QEM algorithm is applied to carry out lightweight processing on a three-dimensional model, screening and optimization are carried out through automatically extracting key feature points of building components, and a concise and accurate lightweight model is constructed based on feature point topological optimization and a graph theory algorithm. The automation degree and efficiency of modeling are improved, and the contradiction between model lightweight and precision is effectively solved.

The invention relates to the technical field of glass container structure optimization, in particular to a lightweight glass container structure optimization design method based on a three-dimensional simulation model. The method comprises the following steps: constructing a continuous curved surface model of the glass container; constructing a glass container geometric variant library based on the continuous curved surface model of the glass container; performing multi-working-condition simulation on the glass container geometric variant library, and performing stress distribution feature extraction to obtain a container stress distribution feature set; constructing a container forming process constraint set; and performing NURBS control point identification on the glass container according to the container forming process constraint set to obtain a constraint container NURBS control point set. On the premise of ensuring the mechanical property and manufacturing feasibility of the glass container, the lightweight design can be realized to the greatest extent.

The invention provides an automatic building design scene generation method and system based on artificial intelligence. According to the method, a geometric feature parameter library and a spatial topological relation parameter library of a special-shaped component are integrated, an artificial intelligence optimization engine is used for carrying out conjoint analysis, and a building scene dynamic form constraint map is created. The process comprises the following steps: acquiring three-dimensional data of a construction site by using laser point cloud scanning, and extracting real-time curvature gradient parameters and functional region connection node parameters from the three-dimensional data; and then matching verification is carried out on the parameters and corresponding threshold values and conditions in the dynamic form constraint map, so that a building scene self-adaptive correction parameter set is generated. And finally, building component processing track control points are adjusted based on the parameter set, and a construction instruction containing spatial form and functional topology linkage is formed. According to the technical scheme provided by the invention, the efficiency and flexibility of building design scene automatic generation can be improved.

The invention discloses an automatic dovetail welding seam grinding control method based on robot visual positioning, and relates to the technical field of visual positioning. The method comprises the steps that after welding is completed, a dovetail welding seam image is collected and converted into a three-dimensional coordinate through a vision algorithm, and a three-dimensional point cloud is generated; smooth interpolation is performed on the three-dimensional point cloud through a B spline curve method to obtain a parameterized curve, and a control point set is optimized through a genetic algorithm to generate a global optimal polishing path; the polishing robot executes a task according to a path, a tail end sensor collects a real-time path and calculates a deviation value with a global path, and when the deviation value exceeds a preset threshold value, inverse kinematics is triggered to solve and correct the path; the hardness of the dovetail weld is measured through laser-induced breakdown spectroscopy, a comprehensive hardness value is obtained in combination with a matrix hardness database, meanwhile, a visual sensor collects the surface state, and polishing process parameters are dynamically adjusted according to the surface state; after the task is completed, the welding seam angle and flatness are detected. According to the method, the optimal path is generated through visual positioning, and automatic grinding of the dovetail welding seam is achieved.

The invention provides a cobblestone stratum bored pile construction and drilling parameter intelligent control method, and relates to the technical field of artificial intelligence and bored pile construction, and the method comprises the following steps: arranging a sound wave emission array at the end part of a drill bit to collect cobblestone distribution information, identifying a weak connecting band as a passable area, calculating an optimal obstacle avoidance track, and setting a posture control point; and drill bit displacement, slurry injection and drill rod deformation parameters are adjusted, so that the drilling tool can intelligently pass along the obstacle avoidance track. Large cobblestones can be effectively avoided, the drilling resistance is reduced, the drilling efficiency is improved, and equipment abrasion is reduced.

The invention relates to the technical field of low-altitude aircraft obstacle avoidance, and discloses an autonomous obstacle avoidance method and system for a low-altitude intelligent dynamic monitoring aircraft, and the method comprises the steps: carrying out the state vector construction of a position coordinate, a flight speed and a course angle of a low-altitude aircraft cluster, and obtaining a state space of the low-altitude aircraft cluster; performing Bezier curve calculation and genetic optimization on the control point sequence in the low-altitude aircraft cluster state space to obtain an optimal detection route parameter; performing geometric distance calculation and double-point removal processing according to the waypoint sequence of the optimal detection route to obtain a patrol airspace equation; performing multi-level reward function calculation through a hierarchical reinforcement learning framework to obtain a high-low layer decision network; time sequence differential learning and strategy gradient optimization are carried out based on the high-low layer decision network to obtain a distributed control strategy, so that global optimization control of the low-altitude aircraft cluster is realized, and stable operation of the low-altitude aircraft cluster in an unknown wind disturbance environment is ensured.

The invention discloses an acupuncture teaching auxiliary platform and method based on intelligent analysis. The method comprises the steps that S1, a preprocessing action signal data set is output; s2, obtaining a delay parameter set and an embedded dimension value; s3, forming a phase space reconstruction trajectory set; s4, generating an action track fragment object set; s5, constructing a bilateral preference sequence according to the dynamic similarity index and the stability difference index; s6, an improved stable marriage algorithm is executed on the basis of the bilateral preference sequence, and a comprehensive stability measurement index value is obtained; and S7, mapping a preset scoring interval according to the comprehensive stability measurement index value to generate a stability scoring result, and pushing the stability scoring result and the corresponding action gap information to the teaching platform to complete feedback. According to the invention, unstable paragraphs and control weak points existing in student operation can be accurately identified, and teaching intervention is more targeted.

The invention discloses a diamond cutter path error compensation method based on cutter wear evolution, which comprises the following steps: S1, multi-modal sensor data acquisition and processing: in the machining process, key state information between a diamond cutter and a workpiece is acquired in real time through a multi-modal sensor; s2, tool wear modeling: key geometric parameters and evolution trend of tool wear are extracted from the collected and processed data, and tool wear modeling is carried out. And S3, artificial intelligence prediction of the abrasion loss: training a tool abrasion prediction model based on a deep learning network structure. And S4, tool path compensation is conducted, specifically, the predicted abrasion loss and the actual free-form surface model are combined, the tool path compensation amount and the compensated control point coordinates are calculated, a new machining path is generated, and dynamic compensation of tool cutting edge abrasion is achieved. And S5, system integration and closed-loop control: integrating the steps on processing equipment, and realizing real-time data interaction and synchronization through a unified data protocol.

The embodiment of the invention discloses a tray forking control method and device of an unmanned forklift and a medium, and relates to the technical field of path planning, and the method comprises the steps that multi-mode environment data in a target forking environment is collected in real time through a multi-mode sensor, and based on the multi-mode environment data, region segmentation is conducted on the target forking environment, and the target forking environment is obtained; constructing a dynamic risk map, wherein the dynamic risk map comprises a static obstacle, a dynamic obstacle and a tray target position; according to the dynamic risk map, an improved adaptive sampling search algorithm and a preset node expansion constraint condition are adopted to generate a global forklift path; b spline curve fitting is carried out on the global forklift path, a multi-source error compensation item is introduced into the track control point through a pre-obtained multi-source quantization error, a fitted forklift path is determined, and the target tray is forked through the fitted forklift path.

The embodiment of the invention provides a network security validity verification and quantitative evaluation method and system, and relates to the technical field of network security, and the method comprises the steps: obtaining global dynamic threat intelligence and a multi-dimensional global network security risk data source, and carrying out the preprocessing; constructing a global feature engineering system based on heterogeneous information network atlas and sequence analysis, forming a feature vector matrix, and mapping the feature vector matrix into an index state vector; inputting the feature vector matrix, the index state vector and the external environment information vector into an evaluation model, dynamically adjusting the weight of the feature vector matrix of each dimension, and outputting the validity score of each safety control point; based on the score, calculating a safety effectiveness index based on a time decay factor; identifying a weak link based on the index, and performing simulation verification to obtain a simulation attack actual measurement result; and an error vector is constructed based on the result and the validity score, and parameter adjustment and weight calibration are carried out. According to the scheme, the accuracy and the real-time performance of network security evaluation are improved.

The invention discloses an unmanned aerial vehicle cluster collaborative operation path planning method based on distributed computing power. The method comprises the following steps: constructing a space-time safety corridor composed of convex polyhedrons for each unmanned aerial vehicle; an initial connected track is generated in the corridor, invariant re-parameterization based on curvature and torsion is carried out, and optimization solution is carried out in an invariant space; the result is expressed as a curvature continuous spline curve, a target function containing bending energy and path cost is constructed with control points and node time as variables, multiple constraints are applied, and complementary curvature constraints are established; minimizing the target function under constraint to obtain a smooth track; when an obstacle or a near conflict is detected, local re-optimization is carried out; and the edge nodes are responsible for constraint synchronization, independent optimization of each unmanned aerial vehicle and rolling updating of the flight path. According to the method, the stability of path planning and the energy utilization efficiency are improved by combining distributed computing power collaboration, geometric invariant re-parameterization and complementary curvature constraint.

The invention provides a multi-axis linkage engraving equipment control algorithm optimization method, which belongs to the technical field of engraving equipment, and comprises the following steps of: decomposing a model into a plurality of curved surface segmentation segments according to a curvature change rate, and performing NURBS curve parameterization processing on each segment to generate control point coordinates and weight coefficient data; a dynamic weight adjustment model is adopted to dynamically calculate a path planning weight coefficient according to a tool cutting force value, a surface roughness demand value and a machining efficiency index value, a minimum spanning tree path algorithm is utilized to carry out path connection sequence planning, and a layered interpolation operation framework combining preprocessing interpolation calculation and real-time interpolation compensation is established. And the optimized interpolation coordinate data is converted into an axis control instruction sequence containing a position instruction, a speed instruction and an acceleration instruction, and the technical problem that the interpolation calculation precision and the real-time performance are difficult to balance when the multi-axis linkage carving equipment is used for machining a complex curved surface is solved.

The invention discloses an assembly type laminated slab installation guiding system and method for a public building special-shaped formwork system, and relates to the technical field of constructions.The assembly type laminated slab installation guiding system comprises a data acquisition module, a calculation decision module, an installation guiding module and a geometric compensation connection module; the system comprises a point cloud acquisition module, a point cloud processing module, a BIM processing module, a point cloud processing module, a BIM processing module, a point cloud processing module, a BIM processing module, a field-BIM coordinate correspondence and output of original measurement data and quality indexes, a calculation decision-making module, a component optimal installation attitude and tolerance distribution and generation of installation instruction parameters, and an installation guiding module, which projects an installation instruction to a field in laser, total station and AR modes, and the geometric compensation connecting module is connected with an edge compressible layer through an adjustable bracket and an oval groove hole to achieve XYZ and angle fine adjustment, reliable locking and post-grouting curing are achieved on the premise that the bearing requirement is met, and the device has the advantage of being high in accuracy.

Methods and systems are described for analyzing images. One or more machine learning models may be trained based on a plurality of images. The one or more machine learning models may comprise a model representing a feature in a scene. The one or more machine learning models may be trained to map input image coordinates to vectors of spline control points. Images may be reconstructed removing the feature from the scene.

To provide a video encoding / decoding method for performing intra-prediction on the basis of availability of a reference pixel so as to improve encoding performance.SOLUTION: An intra-prediction method for a color copy mode checks a reference pixel region designated to obtain correlation information, determines a reference pixel processing setting based on a determination of availability of the reference pixel region, and performs intra-prediction according to the determined reference pixel processing. In addition, a candidate list for motion information prediction of the current block is generated, a control point vector of the current block is derived based on the candidate list and a candidate index, a motion vector of the current block is derived based on the control point vector of the current block, and inter prediction is performed on the current block.SELECTED DRAWING: Figure 14

The invention relates to the technical field of water conservancy project quality management, in particular to a BIM-based water conservancy project construction quality digital acceptance management system, which is used for solving the problems that BIM and OWL ontology cannot be fused, semantic modeling and multi-source data association of quality control points and time state attributes are difficult to realize, and the construction quality of a water conservancy project is influenced in the prior art. BIM model information cannot be dynamically updated, intelligent construction suggestions cannot be generated, and the intelligence, precision and automation level of water conservancy project construction quality management and control is reduced. According to the method, BIM and OWL ontologies are fused through the water conservancy component quality intelligent control module, semantic modeling and multi-source data association of quality control points and time state attributes are achieved, and the intelligence, precision and automation level of water conservancy project construction quality control is remarkably improved by dynamically updating BIM model information and generating intelligent construction suggestions.

The invention relates to the technical field of turning machining, and discloses an ultra-precision turning machining control method and system and a storage medium. The method comprises the steps that a laser contourgraph detects geometric parameters and abrasion data of a turning tool, and a tool health degree index is calculated; performing error compensation based on the health degree index to obtain a feeding control parameter; cutting force signals are collected, and technological parameters are optimized through a multi-target genetic algorithm; arranging a temperature sensor array, and adjusting cooling control according to process parameters; and generating a track control point and performing interpolation processing to obtain a motion control sequence. According to the method, the problem that the machining precision is unstable due to the fact that the cutter state cannot be quantitatively evaluated in real time in traditional turning is solved, and the precision control capability and machining quality consistency of ultra-precision turning are improved.

The invention discloses a welding seam self-adaption B spline curve fitting method for a 3D dense out-of-order point set, and aims at solving the problem of complex curved surface welding seam track generation in robot welding and breaking through the limitation of the prior art through a three-stage self-adaption fitting mechanism. The method comprises the following steps: firstly, self-adaptive screening and projection sorting are carried out by utilizing a straight line fitting error, so that the disordering problem of discrete points of a quadratic curved surface intersection line is effectively solved, and the strong dependence of a traditional method on a CAD model is overcome; secondly, in combination with a region growing method guided by an end tangent vector, robust conversion from an out-of-order point set to an ordered control point is realized through dynamic neighborhood search and projection value sorting, and path continuity of an open / closed curve is guaranteed; and finally, mean sampling quadratic fitting is adopted, control point distribution is optimized while noise is restrained, and a smooth B-spline track meeting the movement requirement of the welding gun is generated. According to the method, direct fitting of the 3D dense out-of-order point set under the model-free condition is achieved for the first time, and the generation efficiency and adaptability of the irregular welding seam track are remarkably improved.

Provided is a numerical control device for improving cycle time and machined surface quality. The numerical control device (1) comprises: a machining program reading unit (10) that generates, on the basis of a read machining program, a tool center point sequence indicating a path of a center point of a tool of a machining tool; an interpolation control unit (11) that interpolates the tool center point sequence generated by the machining program reading unit (10); a kinematic conversion unit (12) that performs coordinate-conversion on the tool center point sequence interpolated by the interpolation control unit (11) to obtain a control point sequence indicating a path of a control point by which the position of the tool is determined; a smoothing application unit (13) that performs smoothing by performing smoothing processing on the control point sequence, obtained by the kinematic conversion unit (12), with predetermined parameters; and a drive control unit (14) that controls driving of a machining tool A on the basis of the control point sequence smoothed by the smoothing application unit (13).

The invention relates to the field of automatic control, and discloses an intelligent control dispensing method and system based on automatic optical detection, and the method comprises the steps: obtaining multi-source real-time data of a dispensing production line, carrying out the feature recognition processing through a preset feature extraction model, and obtaining the dynamically updated production state information; then interference filtering processing is carried out to obtain an effective data set, when it is detected that quality fluctuation exceeds a preset range, an alarm is triggered, deviation identification information is generated, self-adaptive parameter optimization processing is carried out in combination with equipment characteristics and historical operation records, and a control instruction is generated; a control instruction is issued to an execution unit through a double-channel transmission mechanism, transmission delay is monitored in real time, and channels are automatically switched; when the output deviation exceeds the tolerance range, a compensation instruction is generated, parameters of the feature extraction model are updated based on the novel quality fluctuation features, and the dispensing control process is iteratively optimized through closed-loop control. According to the method, the dispensing precision and the production efficiency can be remarkably improved.

The invention discloses a notch position blade profile tolerance point taking device, system and method, and the method comprises the steps: enabling an actual measurement point cloud to be aligned with a theoretical model through progressive spatial registration, carrying out the initial coarse registration, and dynamically adjusting a root mean square error threshold value and a curvature change rate threshold value based on curvature sensitivity analysis, so as to achieve the self-adaptive segmented interruption control; a three-dimensional Hash mapping engine is constructed to store original point cloud data, an incremental data access mode and an iterative data structure are combined, a historical transformation matrix stack, a B spline control point and an 8-bit state register are included, and data processing integrity and high efficiency are ensured; a genetic algorithm is adopted to optimize segmented B-spline surface fitting, and contours of an air inlet edge and an air outlet edge are synchronously optimized through transverse segmentation and longitudinal segmentation; and finally, composite convergence verification is passed. According to the method, through dynamic threshold regulation and control and a hybrid optimization strategy, the detection precision and the calculation efficiency of the complex curved surface are remarkably improved.

The invention relates to the technical field of blasting construction, and particularly discloses a tunnel back break intelligent control method which comprises the following steps: S1, scanning a tunnel face to be blasted to generate high-precision point cloud data; s2, constructing a tunnel face BIM model according to the high-precision point cloud data, and performing space coordinate registration; judging whether blasting is carried out for the first time or not, and if blasting is not carried out for the first time, displaying a blast hole of last blasting on the tunnel face BIM model; s3, receiving input of blast hole space coordinate data of the blasting, and creating blast holes of the blasting on the tunnel face BIM model according to blast hole space coordinates; s4, installing an intelligent laser projector in the tunnel; s5, a reference control point is arranged on the arch crown of the tunnel, projection parameters are calculated, and blast holes of the blasting on the tunnel face BIM model are projected to the actual tunnel face; and S6, drilling is conducted according to the projection, explosives are installed, and blasting is conducted. By the adoption of the technical scheme, the blast hole layout change can be accurately positioned, and the blasting precision is improved.

The invention provides a projection coordinate direct conversion error correction method based on a neural network and related equipment, and relates to the technical field of coordinate conversion. The method comprises the following steps: acquiring projection coordinates under a first reference system to be converted; for the projection coordinates to be converted under the first reference system, obtaining the projection coordinates of the projection coordinates under the second reference system through polynomial fitting; inputting the projection coordinates in the first reference system and the projection coordinates, obtained by fitting, in the second reference system into a trained neural network model to judge whether a conversion error is within a preset error range; and if the conversion error is not in the preset error range, correcting the projection coordinate under the second reference system obtained by fitting according to the error statistic corresponding to the control point set. According to the method, the projection coordinate conversion precision under different reference systems can be improved on the premise of consuming less time resources and computing resources.

The invention discloses a power transmission line foundation pit three-dimensional laser radar equipment error self-correction control method, and relates to the technical field of power transmission line construction, and the method comprises the following steps: firstly, defining the distance from three-dimensional laser radar equipment to a target point, a horizontal included angle and a vertical included angle based on a Cartesian coordinate system; determining an initial coordinate of the target point; secondly, selecting a reference control point, removing noise and gross error points, correcting offset in the vertical direction, and finely processing point cloud data; thirdly, defining errors in the X-axis direction, the Y-axis direction and the Z-axis direction, and establishing an error correction model; and finally, based on the observation value and an error correction model, carrying out self-correction on the target coordinate, and carrying out correction through an environment feature self-adaptive error weight distribution mechanism. According to the method, closed-loop iterative optimization is performed through a multi-level data verification mechanism, the measurement precision is ensured, the operation efficiency is improved, the environmental adaptability is enhanced, and the method is suitable for power transmission line foundation pit division operation under complex terrains.

The invention discloses a high-frequency motor drive multi-rate control method for time sequence disturbance compensation, and the core principle of the method is that low-rate disturbance compensation and a reference tracking trajectory are improved and converted into a time sequence processing process matched with a high-rate control instruction; specifically, a single disturbance compensation value which can be known only at a sampling moment Ts is expanded into time sequence prediction of disturbance changes on N control points in the future through a generalized proportional-integral observer; meanwhile, a low-frequency single reference instruction is constructed into a smooth high-frequency reference trajectory covering N control points through a Lagrange interpolation method, and closed-loop correction of disturbance compensation and reference tracking is achieved on each high-frequency control point Tc. The problem that open-loop prediction errors are continuously accumulated and spread due to mismatching of information updating rates in traditional multi-rate control is fundamentally solved, and therefore high-precision robust control over the high-frequency motor driving system is achieved.

The invention relates to a node semi-rigid modeling-based complex curved surface reticulated shell multi-objective form optimization method. According to the method, through integration of parametric modeling, numerical simulation and a multi-objective optimization algorithm, efficient optimization design of the irregular boundary free-form surface latticed shell structure is achieved. The control point coordinate matrix of the NURBS curved surface is used for generating a geometric model of the complex curved surface reticulated shell, and high-quality grid division is automatically generated; semi-rigid mechanical behaviors of nodes are simulated through combination of a rigid beam and a spring in a numerical model, semi-rigid characteristics of the nodes are integrated into a rod piece unit, and the mechanical performance of the structure is accurately evaluated; and a non-dominated sorting genetic algorithm is adopted, the minimization of the total strain energy of the structure, the minimization of the total weight of the structure and the maximization of the minimum node configuration degree serve as objective functions, and the multi-objective form optimization design of the complex curved surface reticulated shell is completed. The method is suitable for a single-layer latticed shell structure with any node form and any special-shaped contour boundary, and has wide applicability and good transportability.

The invention discloses an unmanned ship path planning method and system based on an improved A * and time elastic band algorithm, and belongs to the field of path planning. Performing global path search in the grid map based on a guide quantity improved A * algorithm to obtain an initial global path; and then path smoothing processing is carried out twice, so that the planned path better meets the unmanned ship kinematics characteristics and meets the unmanned ship full-size collision-free navigation requirement at the same time. In the process that the unmanned ship sails according to a global path, an improved TEB algorithm is adopted to carry out local path planning, and a B spline curve is adopted to replace a traditional piecewise linear trajectory, so that the number of control points is reduced, the trajectory smoothness is improved, and the constraint capability on dynamics is enhanced. And in the aspect of trajectory tracking control, unmanned ship trajectory tracking control of optimal control and model prediction control is realized.

The invention discloses a three-dimensional path multi-stage planning method for a low-altitude unmanned aerial vehicle. The method comprises the following steps: inputting a three-dimensional terrain model and a starting point of path planning; initializing a three-dimensional path based on a cubic B-spline curve, and constructing an optimization model; performing active subspace identification and space mapping on the optimization variable space; executing an improved particle swarm algorithm in the active subspace, and periodically rewarding optimal fitness particles in the population; performing multi-stage refinement on the optimized three-dimensional path, and executing mode search algorithm optimization on the encrypted path control points; and obtaining an optimized global optimal three-dimensional path.