581 results about "Point location" patented technology

The invention relates to the technical field of computer vision and industrial automation, in particular to a shoe sole three-dimensional gluing contour extraction system and method based on vision single-line laser, and aims to solve the problems that virtual calibration target spots cannot be accurately generated based on shoe sole geometry, the positions and sizes of the target spots are difficult to determine by combining curvature extreme values and principal component analysis in the prior art, and the production cost is low. The problem that a double-branch deep learning model cannot be adopted to fuse feature prediction transformation, and the re-projection error is increased is solved; a virtual calibration target spot is automatically generated based on sole geometry through a feature fusion calibration module, a grid is generated through point cloud processing and Poisson reconstruction, the position and size of the target spot are determined by combining a curvature extreme value and principal component analysis, a corresponding relation is established by utilizing two-dimensional and three-dimensional feature matching, initial alignment is realized through ICP and re-projection error optimization, and the target spot position and size are determined. A double-branch deep learning model is adopted to be fused with feature prediction transformation, iterative optimization is carried out through space consistency errors, and re-projection errors are reduced.

The invention discloses an automatic river network grading and river topological relation identification method based on a graph theory, and relates to the technical field of hydrological geographic information. The method comprises the following steps: acquiring and cleaning a vector river network, a key point location and DEM data of a target drainage basin; constructing an initial river network graph model based on the line element connection relationship; integrating DEM topographic evidence and graph theory connection features, constructing and solving a global potential energy field equation containing topographic driving and boundary constraint, and calculating flow potential energy attributes of nodes of the whole network to determine a flow relationship; based on the flow direction relation, identifying topology abnormal structures such as strong connectivity components in the network, and performing ring breaking processing by using direction confidence to generate a ring-free directed network structure; and performing river grade division based on a topology transfer rule, and associating the key point location to a river network skeleton. According to the method, through global potential energy field solving and topological optimization, the problems that the flow direction of the plain micro-geomorphic area is difficult to recognize and complex loops cannot be graded are solved, and automatic construction of the river network topology is achieved.

The invention discloses an abnormal detection method and system for a splayed anti-loosening line of a rail train, and relates to the technical field of rail traffic detection, and the method comprises the steps: image collection and processing: shooting an image of a fixed point region containing the anti-loosening line, and preprocessing the image to obtain a target image; line integrity judgment: extracting a bolt, a bolt marking line and an anti-loosening line through an analysis model to form a target area graph, and judging whether the anti-loosening line is complete or not according to line segment continuity and form; performing line deformation depth analysis, and synchronously obtaining the position of an anti-loosening line intersection point and deformation data through the model in combination with the loosening angle of the bolt marking line when the line deformation is complete; performing line deformation safety judgment, setting a safety threshold group based on historical data, and comparing deformation data to output a signal; after line deformation abnormity judgment and comparison signal receiving, actual data are compared with theoretical data output by the mechanical model, and abnormal or normal signals are output. The anti-loose line full-dimension high-precision detection is achieved, automation and real-time performance are improved, and train operation safety is guaranteed.

The invention discloses a multi-protocol hardware communication adaptation module based on an energy storage system and a configuration method, the module comprises a protocol template library, an intelligent mapping engine and a model generator, and the method comprises the following steps: storing structured protocol point location information through the protocol template library; an intelligent mapping engine is used for shielding the isomerism of Modbus, MQTT, IEC104 and other underlying protocols, and a unified data interface is provided; intelligent matching among different protocol terms is realized by adopting a natural language processing technology through a semantic level mapping unit; and finally, generating a target data model by a model generator through one key. The method effectively solves the problems that when the energy storage system integrates multi-manufacturer equipment, protocol configuration depends on manpower, efficiency is low, errors are prone to occurring, and expansibility is poor.

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 discloses a method for automatically calculating the waviness of an aircraft profile in an MATLAB environment, and the method comprises the steps: 1, obtaining the plane section point location data of the waviness of the aircraft profile based on the reverse point cloud data of the aircraft profile; and step 2, automatically calculating the airplane profile waviness in the MATLAB environment, including plane classification of point location data, three-dimensional coordinate system conversion, two-dimensional wave crest and wave trough point location calculation, wave crest and wave trough point coordinate system reverse conversion, waviness calculation and form report output on the point location data of the plane cross section obtained in the step 1 through a program in the MATLAB environment. Therefore, automatic calculation of the airplane appearance waviness is completed. According to the invention, the problem that the existing detection mode for the airplane profile corrugation is difficult to have convenient operability, detection precision and detection efficiency at the same time is solved.

The invention relates to a cluster scheduling method and system for multi-unmanned aerial vehicle cooperative detection of hoisting equipment, and the method comprises the steps: obtaining detection object information from a detection request when the detection request of a user side is received; calling a preset equipment three-dimensional model based on the detection object information, and generating a detection task based on the equipment three-dimensional model; performing demand analysis on the detection task, and outputting task demand information; a cooperative detection strategy is generated based on the task demand to generate a cooperative flight route, the unmanned aerial vehicles of the corresponding model and number are called, and the multiple unmanned aerial vehicles are controlled to cooperatively execute the flight task according to the generated cooperative flight route; and based on a preset communication link, receiving detection data acquired by the unmanned aerial vehicle, mapping the detection data to a corresponding detection point location in the equipment three-dimensional model, and sending the detection data to a user side. The method and the device have the effect of improving the efficiency and the accuracy of large-scale equipment detection.

The invention relates to the technical field of capacitive touch, and discloses a capacitive touch signal self-adaptive compensation method and device. The method comprises the following steps: collecting original capacitance signal grid data in an initial contact stage, and constructing a dynamic contact quadtree; on the basis of the quadtree, a first point position prediction algorithm of contact dynamics perception is operated, and stable coordinate prediction mapping with confidence is constructed; and executing multi-mode first point decision and touch event generation based on the mapping, outputting a touch event and feeding back the touch event to an operating system. According to the method, initial contact signal features are captured through the dynamic contact quadtree, stable coordinate prediction mapping and multi-modal decision are combined, the problem of jumping coordinates in the initial touch stage of an existing system is solved, the touch accuracy of scenes such as vehicle-mounted center control and industrial HMI is improved, the operation risk is reduced, and the application value of the capacitive touch technology is expanded.

The invention relates to the technical field of intelligent traffic, in particular to a training method and system for a vehicle track frame filling model, and the method comprises the steps: training a pre-trained Transform network based on a plurality of pieces of sheltered historical track data, and obtaining a trained vehicle track frame filling model; the training process comprises the following steps: obtaining a prediction result corresponding to each shielded time step; obtaining map constraint loss based on prediction results of all shielded time steps and a preset tunnel center point position matrix; obtaining position loss, speed loss and course angle loss based on the time step data of the prediction result corresponding to all the shielded time steps and the time step data in the historical trajectory data; based on the map constraint loss, the position loss, the speed loss and the course angle loss, model parameters are adjusted, and a vehicle track frame compensation model is obtained. The method has the beneficial effect that the frame supplementing track of the vehicle is more reasonable, smoother and smoother.

The invention discloses an OHT track node automatic identification and path planning method and system, and relates to the technical field of OHT tracks, and the method comprises the following steps: identifying track node positions based on vehicle motion track feature analysis, point cloud geometric clustering processing and a multi-mode verification method combining visual and magnetic features; performing semantic recognition according to the node positions to obtain node types, and constructing a track topological graph according to the node types; a candidate path set is generated through the track topological graph, and local optimization is conducted on the task execution sequence of the candidate path set and the vehicle matching relation; based on a local optimization result, performing synchronous adjustment on path selection and task allocation, and outputting an integrated scheduling scheme; according to the method, high-precision node positioning, semantic classification, structured track topology construction and integrated optimization of multi-vehicle path and task scheduling can be realized, and the operation efficiency, the scheduling reliability and the resource utilization rate of an OHT system are remarkably improved.

The invention provides a water leakage point positioning method and device based on resistance gradient calculation, and the method comprises the steps: obtaining a total resistance value and a tail end resistance value of a water leakage induction rope, and reading a preset resistivity parameter per unit length; calculating the distance of a water leakage point based on the total resistance value, the tail end resistance value and the resistivity parameter per unit length; according to the mapping relation between the length of the induction rope and the physical position established in the installation and debugging stage, the distance of the water leakage point is converted into the physical position described by corresponding 3D coordinates or characters; the physical position information is combined with real-time monitoring data to generate alarm prompt information containing a specific water leakage point location, and the alarm prompt information is output to a monitoring interface, so that accurate positioning of the water leakage point can be realized, the fault response time is remarkably shortened, and through a multi-thread data acquisition and dynamic alarm judgment mechanism, the real-time performance and the alarm accuracy of the system are improved; and the false alarm and repeated alarm frequency is reduced.

The invention relates to the technical field of point location labeling, in particular to a self-adaptive load balancing point location labeling method and system based on image processing, and the method comprises the following steps: obtaining an image source division region, extracting an edge pixel number texture direction number color channel standard deviation, generating region detail redundant structure distribution information, and monitoring node state data. The method comprises the following steps: constructing a node resource load state mapping set, matching according to a regional detail redundancy ratio and a node state, establishing a task allocation relationship, extracting a boundary gray derivative, screening a boundary stable candidate point location set, calling point location coordinates, sending the point location coordinates to corresponding nodes, executing target verification, writing in an image frame, and generating a labeling result. Quantitative extraction is performed on distribution among image region edge pixels, texture directions and color channels, and task assignment is accurately paired in combination with image structure complexity and node states, so that resource mismatching and processing retardation are avoided, and task distribution accuracy is improved.

The invention discloses a practical training platform three-dimensional scene mass data loading optimization method, and relates to the technical field of computer graphics and three-dimensional visualization. Passive response of data loading is converted into active pre-judgment through an orbit prediction model and prospective visible area calculation, and the real-time performance of data loading is improved. The rendering lag caused by the rapid change of the satellite track is obviously reduced; the combination of the predicted position and the camera vision cone ensures that the point location is scheduled before the vision field is switched; secondly, GPU resource utilization is optimized through dynamic attribute increment updating and a dirty marking mechanism; static and dynamic attribute buffer areas are separated, only change data are updated, the CPU-GPU communication overhead is reduced, the frame rate fluctuation problem caused by batch updating is solved, and the system is still kept smooth under ten-thousand-level point location dynamic updating; in addition, the collaborative design with terrain rendering eliminates point location dislocation during terrain detail level switching through monitoring and double-buffer correction, and improves visual consistency.

The invention belongs to the technical field of computer vision, and particularly discloses a monocular 3D object detection method for realizing depth enhancement based on a visual basic model, electronic equipment and a readable storage medium, and the method comprises the steps: S1, building a data set: employing a monocular camera to collect a pavement scene, and obtaining an RGB image in the pavement scene; s2, image preprocessing: preprocessing the RGB image for subsequent feature extraction and depth estimation; s3, performing feature extraction by adopting a dual-backbone network: performing visual semantic feature extraction on the preprocessed RGB image by using DINOv2; performing depth feature extraction on the preprocessed RGB image by using a DPT head; s4, generation of depth perception query points: inputting the visual semantic features and the depth features into a DETR network to generate the depth perception query points; and S5, target detection output: using an MLP-based detection head to obtain information of the category, the size, the center point position, the depth, the 3D size and the direction of the object.

The invention discloses a high-precision adaptive numerical simulation method and system for solving a nonlinear integral-differential equation, and relates to the technical field of computer simulation and numerical calculation. Comprising the steps of setting simulation conditions; constructing a grid space based on the computational domain; constructing a global cubic spline interpolation function based on the solutions on the grid points; if the updated grid point location exists, calculating a right-end integral item by using an adaptive numerical simulation integral algorithm; calculating a heuristic solution and an error estimation value; dynamically adjusting the tentative step length and updating the time according to the estimated value and the ODE tolerance; checking gradient and curvature distribution of solutions, encrypting grids for areas with violent solution changes, and sparse grids for areas with smooth solution changes; using a global cubic spline interpolation function to demap the old grid space to the adjusted new grid space; and iteratively executing the steps, and outputting an integral solution in the computational domain. And finally, collaborative improvement of integral simulation calculation in precision, efficiency and stability is realized.

The invention discloses a fully mechanized coal mining face multi-protocol equipment simulation linkage control system and a working method. The control system comprises a presentation layer, a business logic layer and a data layer. The working method comprises the following steps: S1, selecting equipment needing to be simulated and issuing the equipment to the business logic layer; s2, an equipment simulation module obtains point location information of the selected equipment, and a linkage rule read-write module obtains equipment linkage control rule information; s3, the device simulation module calls a point location read-write module of a corresponding protocol according to the read device point location information, and point location change monitoring during device operation is achieved; s4, the rule simulation module completes point location read-write module calling across the devices according to the analyzed rules, and therefore linkage simulation between the devices is achieved; s5, the point location read-write module receives the calling command, scans the read point location and feeds back a scanning result to the business logic layer; and S6, the service logic layer transmits a feedback result to a simulation monitoring module for simulation effect display.

The invention provides a scenic spot navigation method, system and device based on location services and a medium, and belongs to the technical field of scenic spot navigation, the method comprises the following steps: developing a scenic spot navigation light application based on a host application, and presetting location data of each scenic spot and a dynamic distance trigger threshold configuration rule for judging the location of a user; starting a scenic spot navigation light application, and obtaining a user position and a current positioning precision parameter through a real-time position interface of a host application; executing a dynamic distance trigger threshold configuration rule, and dynamically calculating a distance trigger threshold of each scenic spot according to the scenic spot distribution density and the current positioning precision parameter; when the distance between the position of the user and a certain scenic spot is smaller than the corresponding distance triggering threshold value, staying timing is started, and corresponding voice explanation is triggered after the duration condition is met. The intelligent level and the user experience of the scenic area guide system are improved by dynamically adjusting the trigger threshold value and comprehensively considering the judgment of multi-dimensional factors such as the positioning precision, the scenic spot distribution density and the residence time.

A ship docking assistance device includes a position azimuth information acquisition unit; a LIDAR; a map generation updating unit; a high-point acquisition unit; and a position azimuth estimation unit. The LIDAR acquires point-group data three-dimensionally indicating the environment around a ship. The map generation updating unit generates a map around the ship based on the point-group data. The high-point acquisition unit acquires, from within the point-group data, a high point having a prescribed height or more. The position azimuth estimation unit estimates the position and the azimuth of the ship through matching between the position of the high point acquired by the high-point acquisition unit and the position of the high point in the map. The map generation updating unit updates the map by placing the point-group data in the map using, as references, the position and the azimuth of the ship estimated by the position azimuth estimation unit.

The invention relates to a ship route automatic recommendation and matching method and system based on big data, and the method comprises the steps: receiving a starting point position and an end point position selected by a user, and automatically matching a corresponding nearest port as an actual starting point port and an actual end point port; generating a plurality of candidate routes in combination with historical navigation data, real-time meteorological data and ship performance parameters in the route database; carrying out adaptive analysis on the candidate routes based on the ship type and the cargo capacity, and excluding candidate routes which do not conform to ship navigation conditions; performing multi-dimensional evaluation on the candidate airlines through a preset optimization algorithm, generating an airline recommendation list, and sending the airline recommendation list to a user interface; and continuously monitoring the real-time state data of the route selected by the user, and triggering an automatic re-planning process if detecting that the channel is abnormal or the weather is suddenly changed. According to the method, big data analysis, intelligent matching and dynamic optimization are integrated, and automatic, multi-dimensional and high-reliability route recommendation and collaborative management are realized.

The invention discloses a crane working path planning method and system and application thereof. The method comprises the following steps: 1) constructing a crane operation demonstration database; 2) pre-training a convolutional neural network by using a demonstration database, and extracting a mapping relation between environment features and tracks; 3) inputting the current starting point position, the target point position and the environment information obtained by the laser radar into a path generation network, and outputting an initial action sequence of the rotation degree of freedom, the dolly motion degree of freedom and the hook degree of freedom; 4) performing local re-planning on the initial action sequence by adopting a fast random tree algorithm based on physical constraint, wherein the optimization criterion is the weighted sum minimization of the path length, the load swing angle and the action sequence variation; and (5) the crane is controlled to move according to the optimized action sequence, the load swing angle is monitored in real time, and emergency braking is triggered when the swing angle exceeds a threshold value. By means of the method, efficient and safe operation of the crane in the complex environment can be achieved, and good engineering practicability and popularization value are achieved.

The invention provides an exception control method and device based on a running log, equipment and a storage medium, and the method comprises the steps: collecting and analyzing the running log, and generating multi-dimensional state mapping in a visual interface based on an analysis result; when the running log indicates that the flow node is in the abnormal state, embedding a dual-mode operation control at the position corresponding to the abnormal node of the visual interface; in response to an operation on the retry option, calling a preset processing strategy library matched with the abnormal state type, and executing a recovery operation; in response to an operation on the skipped option, releasing a key resource binding relationship occupied by the abnormal node; on the basis of the analyzed task dependency information, updating an input source dependency relationship of a subsequent node of the abnormal node; in response to successful execution of the skipping intervention, data replacement and dynamic splice operations are performed to splice the subsequent process. By adopting the technical scheme, full-process automatic closed loop of exception handling is realized, the exception response speed is improved, and the resource utilization rate is maximized.

The invention relates to the technical field of parameterization modeling, in particular to a construction drawing intelligent design optimization method and system based on parameterization, and the method comprises the following steps: extracting boundary and annotation information, judging the orientation and affiliation relation of components, analyzing the coordinates of end points, adjusting the order of side lines, calculating the occupation offset, comparing the positions of intersection points, recognizing preorder nodes, and sorting. Extracting junction point distribution to judge a contact range and a connection relation, and determining a drawing page number by combining a component starting point and a path direction. According to the method, the spatial affiliation relation of the components is established through geometric boundaries and labeling information, the trend is adjusted according to the included angle difference value of side lines, the connection strength is recognized by combining the joint angle and the contact range, the drawing sequence is deduced according to the serial number sequence and the intersection point sequence, and the component combinations are continuously divided through attachment sections. The drawing page distribution is positioned based on the starting point of the component and the path direction, dynamic cooperation of component arrangement, sequence organization and drawing splicing is achieved, and the accuracy of component structure expression and the integrity of construction drawing generation are improved.

A system (100) for the secure MCP-mediated use of tools by AI agents and generative AI / LLM services in cloud-native distributed applications, wherein the system (100) comprises: a KL agent interface (1) configured to receive natural language commands and application events from a variety of client applications and to generate appropriate tool call commands for one or more generative KL or Large Language Model (LLM) services; an MCP mediator service (2) that is configured to: (a) to convert the tool request requests into messages compatible with a model context protocol (MCP); and (b) to maintain the conversation context, including at least one of the following: user identity, tenant identity and application identity; a tool register (3) that stores a plurality of tool descriptions, each tool description defining at least a tool identifier, an input and output scheme, an endpoint location and allowed functions, wherein the tool register (3) is accessible to the MCP mediator service (2); a policy and security manager (4) configured to evaluate each MCP tool call against one or more security and access policies based on the conversation context and the corresponding tool description, and to issue a decision to allow, modify or block the tool call; a tool connector layer (5) comprising a plurality of tool adapters, each tool adapter being configured to communicate securely with a corresponding external tool, service or data source using credentials and permissions restricted according to the decision of the policy and security manager (4); an observation and audit manager (6) configured to record, for each tool call, at least a timestamp, the calling KL agent, the tool identifier, the policy decision, and a summary of the tool response, and to provide audit logs and metrics for monitoring and compliance purposes; and a cloud-native deployment controller (7) configured to provide the MCP mediator service (2), policy and security manager (4), tool connector layer (5) and observation and audit manager (6) as distributed microservices with network isolation between tenants in a cloud-native environment.

The invention discloses a campus spontaneous activity layout optimization method coupling spatial features and behavior probabilities, and relates to the technical field of campus space planning, and the method comprises the following steps: dividing space units in an outdoor space, generating candidate points, superposing a clear pass width, fire evacuation, barrier-free and illumination constraints to form a constructable candidate point set, and carrying out the construction of the candidate points; gathering wireless network, access control, reservation and calendar data according to a space unit-time window; identifying a staying event based on the aggregated data, establishing a planned activity library, and deducting plan contribution according to space-time attenuation to obtain spontaneous activity observed quantity; constructing statability and risk features, and establishing a probability and intensity model to output a probability field, an intensity field and uncertainty; and under budget and constraint, combining with facility gain and influence attenuation to solve a facility combination packet point location, an output point location, a bill of materials and a check record, thereby reducing short-term peak misjudgment and improving layout implementability and safety compliance.

The invention discloses a virtual reality level simulation method based on a material point method and gridding surface reconstruction, and belongs to the crossing field of computer graphics, physical simulation and virtual reality technologies. The method comprises the following steps: S1, classifying and storing position coordinates of material points according to material numbers of the material points, and traversing the coordinates to obtain a boundary of a bounding box of the material points; s2, selecting a grid size and a boundary extension distance for reconstructing the surface in a self-defined manner, and generating a grid; s3, selecting a Gaussian function to calculate the contribution of each substance point to the overall substance point density field, and obtaining parameters; s4, calculating the contribution of each substance point to the overall substance point density field, and performing accumulation to obtain the overall substance point density field; and S5, obtaining a contour surface of the overall material point density field, and exporting the contour surface as a rendering engine general three-dimensional model to obtain a simulation visual effect. According to the method, the problems that in the prior art, tens of millions of substance points cannot be processed, reconstruction parameters are difficult to select, and connection with a high-end rendering engine is not smooth can be solved, and the virtual reality level simulation visual effect is achieved.

The invention relates to the field of flow field measuring point position selection, in particular to a time history deep learning method for flow field measuring point position selection, which comprises the following steps of: arranging flow field monitoring points according to original data of an experimental object; numerical simulation of the flow field is carried out, and flow field time history data at the measuring points are obtained; constructing an FTH-AE deep learning network model, and training the deep learning network model by using the original data; clustering the feature codes to obtain a measuring point set with similar time-varying features; and visualizing the measuring point samples in each region, analyzing sample characteristics in each region, and determining an optimal measuring point arrangement scheme. According to the method, the limitation of traditional experience dependence is broken through, an area with remarkable flow characteristics is accurately positioned, and scientific arrangement of measuring points is realized.

The invention particularly relates to a GIS map mass point location loading optimization method. According to the GIS map mass point location loading optimization method, an appropriate level range for using point location aggregation is preset according to the characteristics of client data access; sVG is selected as a map marking format, and point location data is rendered based on the boundary of a map viewport; and when the map zooming level is lower than the user-defined threshold value and the data volume exceeds the user-defined threshold value, reducing the number of the independent marks on the screen by using a Marker Cluster strategy so as to improve the loading speed of the map and the user experience. According to the GIS map mass point location loading optimization method, the mass point location loading speed and rendering efficiency are remarkably improved, repeated calculation and DOM operation are reduced, system resource occupation is reduced, map interaction smoothness is enhanced, and therefore user experience and the stability and practicability of a GIS system are effectively improved.

The invention provides a multi-modal view linkage method, relates to the technical field of image processing, and is used for realizing real-time linkage of a 2D plane view, a 3D model view and a panoramic view. The method comprises the following steps: establishing a global coordinate system; mapping the two-dimensional plane coordinate system, the three-dimensional model coordinate system and the panoramic coordinate system to the global coordinate system through coordinate transformation; based on the global coordinate system, preset point position coordinates in the panoramic coordinate system are mapped to a two-dimensional plane coordinate system and a three-dimensional model coordinate system, and corresponding plane point position coordinates and model point position coordinates are obtained respectively; establishing an association relationship among the preset point location coordinates, the plane point location coordinates and the model point location coordinates; when it is detected that the observation point positions and / or the observation view angles of the panoramic view are / is changed, the corresponding observation point positions and / or the observation view angles in the two-dimensional plane view and the three-dimensional plane view are / is synchronously adjusted based on the incidence relation.

The invention relates to the field of numerical control post-processing, and particularly discloses a five-axis series-parallel processing machine tool tool path post-processing method, which comprises the following steps: establishing a target test piece CAD model, importing a CAM software planning path, and generating an original tool location file containing a tool nose position and a tool axis direction vector; c4 continuous pH splines are inserted between corners and adjacent small line segments for fairing, and control polygon side length constraints are set; local synchronization is firstly carried out, and then a seven-time B spline is used for replacing a straight line segment to carry out global synchronization; key point speed limiting is conducted, feeding speed constraint is obtained in combination with multiple constraints, and the speed is planned through a mixed S-shaped curve; and S6, judging the position of an interpolation point, and selecting a corresponding mode for calculation. According to the technical scheme, the problems that fairing is sensitive, errors are difficult to control, pH splines are only C3 continuous, and parameters are not synchronous are solved, track continuity is improved, vibration and tracking errors are reduced, and machining precision and efficiency are improved.

The invention relates to a false detection meridian recovery method, device and equipment based on spatial topology and position reasoning, and the method comprises the steps: generating a false detection recovery acupoint coordinate through a known meridian acupoint and a symmetrical meridian acupoint according to a symmetry constraint relation of human meridian acupoints, and generating a false detection recovery acupoint coordinate based on a logic topology constraint relation of the human meridian acupoints. The method comprises the following steps: correcting X-axis coordinates of falsely detected and repaired acupuncture points through inherent trend and naming sequence of human meridians and collaterals, correcting Y-axis coordinates of the falsely detected and repaired acupuncture points according to a spatial topology constraint relation of the human meridians and collaterals and acupuncture points by determining an up-down position relation of the meridians and collaterals under a human body posture and through a relative position relation under a specific scene, and correcting the false detected and repaired acupuncture points according to the spatial topology constraint relation. The positions of the acupuncture points are estimated through the movement distance of the bed body, and the false detection of the acupuncture points is discriminated and recovered. According to the method, the repairing coordinates are generated through the features of the acupuncture points and the symmetric points, cooperative correction of the axis coordinates is achieved through the logical topology and the spatial topology of the meridians and collaterals, and discrimination and recovery of long-section false detection are achieved through the position of the target point.