93 results about "Topological map" patented technology

A method is provided for enhanced data routing in neural networks using Self-Organizing Maps (SOM) integrated with Autoencoder-GAN. The method comprises training an autoencoder to encode input data into a latent space representation; applying a Self-Organizing Map (SOM) to organize the latent space representation into a topological map; refining the latent space representation using a Generative Adversarial Network (GAN), wherein the generator generates enhanced latent space representations and the discriminator evaluates their quality; using the refined latent space representations to update the SOM topology dynamically; generating routing coefficients based on the updated SOM topology to guide data routing in a capsule network; and dynamically adjusting routing within the capsule network using the generated routing coefficients to enhance performance based on the refined latent representations.

The invention relates to the technical field of robot navigation, and discloses an automatic path-finding intelligent robot and a path-finding method thereof. According to the method, multi-dimensional spatial data including obstacle distribution, ground features and dynamic target motion information is acquired through an environment sensing device, spatial discretization processing is performed on the data, and a topological map which has a hierarchical structure and includes a node connection relation and a region passing weight is generated. Then, according to the node connection relation of the topological map, a path planning model based on manifold learning is established, and an optimal path candidate set is determined by calculating the manifold distance between adjacent nodes; then extracting a key node sequence in the candidate set, dynamically optimizing a path in combination with a region passing weight, and generating a preliminary navigation track; and finally, inputting the initial track into a motion control model, carrying out smooth processing according to kinematics constraint of the robot, and outputting a final execution path. According to the invention, the robot can efficiently find the way in a complex environment.

The invention discloses a delivery task cooperative processing method, device and equipment based on a quadruped robot and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: analyzing a delivery task through an upper computer, combining the real-time dynamic information of an office scene, and employing an improved binary particle swarm optimization algorithm to optimize the task distribution of multiple robots, and efficient collaborative distribution in an intelligent office environment is realized. The robot receives a distribution scheme sent by the upper computer, a multi-level navigation strategy is started by utilizing environmental perception data, a topological map and a D * Lite algorithm are fused to carry out path planning, and dynamic obstacle avoidance and efficient distribution are ensured. The target path planning information is monitored in real time through the upper computer, dynamic analysis is carried out through the scene perception algorithm, the scene relevance result is obtained, the collaborative distribution strategy is executed to complete the distribution task, the task response speed and the distribution efficiency are improved, interference to the office environment is reduced, and the work efficiency is improved. And automation and intelligentization of robot distribution in an intelligent office scene are realized.

The invention belongs to the technical field of artificial intelligence and robot autonomous navigation, and discloses an open vocabulary topology semantic graph construction and navigation method and system for an unknown environment. A topological map composed of nodes and edges is constructed in an online incremental mode, the nodes represent key positions in the environment, and the edges represent passable connection between the positions; for each node in the topological map, coding the corresponding visual observation image into a semantic feature vector by using a pre-trained visual language model; performing graph neural network fusion on the semantic feature vectors, executing cross-modal alignment with a natural language instruction, and generating global map representation; and based on the global map representation, generating a navigation action, and driving an intelligent agent to move towards the target. According to the method, an environment representation which deeply fuses spatial topology and semantic information is constructed, and intelligent decision making is carried out according to the environment representation.

The invention discloses a map construction and path planning method of a four-footed robot dog, and belongs to the technical field of intelligent navigation of four-footed robot dogs. The method comprises the following steps: acquiring environment original data through a preset multi-dimensional sensor, and determining a terrain structure, a terrain material, a terrain bearing capacity and a space dynamic obstacle probability of an environment according to the environment original data; constructing a multi-dimensional topological map according to the terrain structure, the terrain material, the terrain bearing capacity and the space dynamic obstacle probability; the method comprises the following steps: acquiring kinematics parameters of a four-footed robot dog, generating a motion path according to the kinematics parameters and a multi-dimensional topological map, and controlling a moving track of the four-footed robot dog according to the motion path, so that parameters such as terrain materials, terrain bearing capacity and space dynamic obstacle probability are supplemented in dimensions of a traditional grid map; the dimension information of the grid map is improved, and the accurate three-dimensional grid map is provided for the robot, so that the task execution capability of the robot in a dynamic complex environment is ensured.

The invention discloses an intelligent warehouse task allocation method and system for multiple types of AGVs, and particularly relates to the technical field of intelligent warehouse logistics automation, and the method comprises the steps: obtaining a to-be-allocated task through a docking warehouse management system WMS, carrying out the structural normalization processing, mapping the to-be-allocated task to a warehouse topological map, and generating a task execution element set; and meanwhile, the running state and event log records of each AGV are collected. Calling a task consumption model based on the environment feature vector to obtain a power consumption predicted value and a time consumption predicted value; constructing a health risk score based on the monitoring window and mapping the health risk score into a risk level; and generating an electric quantity safety margin by combining the residual electric quantity with the necessary return stroke or the nearby complementary energy cost, and forming a dynamic capability portrait. In the candidate set generation stage, sustainability constraint verification is carried out according to the health risk score, the risk level, the electric quantity safety margin and the maintenance window constraint, a rolling scheduling mechanism is adopted to generate a task allocation result, and a task instruction is issued to the corresponding AGV to be executed.

The invention relates to the technical field of constructional engineering quality detection, and discloses a method for testing the apparent quality of mirror-surface bare concrete. The method comprises the following steps: acquiring a multiband multispectral image of the surface of a component; through image fusion and feature decoupling, an independent specular glossiness distribution diagram, a microscopic fluctuation topological diagram and a chromaticity coordinate mapping diagram are obtained; registering and associating the three images to construct a three-dimensional total element apparent characteristic field; performing gridding scanning on the characteristic field to extract glossiness uniformity, texture roughness and chromaticity stability indexes of each grid; inputting a pre-trained apparent quality analysis network to output a local quality evaluation value and a defect type label of each grid; and integrating and generating an overall quality index and generating a repair guidance map according to the defects. According to the method, multi-dimensional, full-field and intelligent fine detection of the apparent quality is realized, the gloss, the texture and the color can be independently and quantitatively analyzed, and the defect can be accurately positioned.

The invention discloses a quadruped robot navigation method and system based on three-dimensional environment mapping and navigation, and belongs to the technical field of mobile robot navigation. The method comprises the following steps: acquiring a non-repeated scanning three-dimensional point cloud and a high-frequency pose to carry out pre-integration distortion removal; extracting features for joint optimization, and constructing a global three-dimensional point cloud topological map; stripping ground point cloud by using a double-track map mapping mechanism, and performing dimensionality reduction to generate a two-dimensional multi-dimensional cost navigation map; column cycle matching is carried out by using two-dimensional polar coordinate context features in a positioning degradation environment, and continuous poses are forcibly corrected; and forward sampling and evaluation are carried out based on the navigation map and the multi-dimensional trajectory evaluation cost function model, and closed-loop motion of the robot is controlled. According to the method, the problems of high computing power consumption of high-dimensional space calculation and easy failure of positioning in a degraded environment are effectively solved, and the safety navigation capability of the quadruped robot in a complex environment is remarkably improved.

The invention discloses a boiler fault traceability analysis system based on digital twinning, and the system comprises the following steps: constructing a boiler topological graph based on boiler physical components and a connection relation; 2, collecting boiler operation data, and correspondingly binding the boiler operation data with the map nodes; constructing structure fusion data by using the structure position relationship between the binding data and the map nodes; obtaining boiler maintenance data, executing semantic recognition processing, extracting a mapping relation between a fault field and a map node, and generating annotation data; fusing the structure fusion data with the annotation data to generate guide data; inputting the data into an improved TSFormer model, and outputting causal scoring data; and fusing the causal score data, the trend information of the operation data and the historical weight data of the map edge, executing an edge weight updating operation, and writing the edge weight updating operation into the boiler topological map. According to the invention, the diagnosis efficiency and response capability of the boiler system after abnormal operation or fault occurrence are effectively improved.

This invention relates to a path planning method for homotopy classes in planar mobile robots, based on sunlight sampling. The method includes dividing a two-dimensional planar map to be searched into a topological map composed of obstacle modules and free convex polygon modules using convex decomposition. Simultaneously, it records the relationships between convex polygon modules and their vertices, as well as the datasets of convex polygon modules and their adjacent convex polygon modules. A heuristic function is set to expand from the starting block, continuously recording the blocks traversed by the path and excluding parent and ancestor blocks to prevent path looping when advancing an adjacent block. Upon reaching the target block, the method stops and records a set of non-repeating path blocks as a path homotopy class. Sunlight sampling is performed on each path homotopy class to obtain the intra-class shortest path. This invention can quickly search for path homotopy classes in the topological map and uses the sunlight principle to search for intra-class shortest paths, achieving rapid partitioning of path homotopy classes and significantly improving the search efficiency for intra-class shortest paths.

The application relates to the technical field of robot scheduling, in particular to a mobile robot real-time scheduling method and system based on a dynamic topological map. In the system, an emergency scheduling planning scheme management module collects the transportation state information of each mobile robot in real time through a sensor, judges the current working load state of the mobile robot, combines the topological map updating result under the corresponding transportation scene at the current time and the initial material delivery target planning route of the corresponding mobile robot, generates an emergency scheduling planning scheme of the mobile robot with the abnormal working load state at the current time, and calculates the load balance comprehensive adaptive deviation value of each emergency scheduling planning scheme. The application realizes the dynamic updating of the material delivery target planning route of the mobile robot in combination with the transportation state of the mobile robot itself, introduces the concept of the load balance comprehensive adaptive deviation value, realizes the effective screening of the best emergency scheduling planning scheme of the mobile robot, and realizes the collaborative management among different mobile robots.

This invention relates to a multi-level semantic-driven visual language navigation method, belonging to the field of computer vision language navigation. The invention constructs a perception-planning-control end-to-end collaborative structure. The method involves: First, in the front-end perception stage, combining target-oriented semantic masks and spatial geometric features, a semantic enhancement potential field is constructed through morphological contour projection and a dynamic fusion mechanism to extract local candidate waypoints. Second, in the high-level planning stage, a spatiotemporal topology map is dynamically maintained, and a graph-aware cross-modal attention mechanism is used for global path planning. Finally, in the low-level action control stage, a multi-level escape mechanism is introduced, achieving proactive resolution of microscopic physical deadlocks through physical fault tolerance, semantic redirection based on near-field area ratio, and negative feedback topology pruning. This invention effectively overcomes the defects of blind exploration and significantly improves the navigation success rate and system robustness in complex continuous environments.

The application discloses a kind of open network in distributed DDC controller collaborative management method and system, belong to wireless network security technical field, including according to open network in Wi-Fi channel state information constructs the three-dimensional topological map of controller and carries out dynamic trust evaluation, lightweight communication protocol stack is built in each distributed DDC controller node, generates distributed key pool based on elliptic curve encryption algorithm and implements dynamic key distribution;Distributed DDC controller resolves input instruction and switches communication interface;Task pre-allocation is carried out, and dynamic adjustment is carried out to the execution state of continuous monitoring task, and starts arbitration mechanism to carry out dynamic adjustment.The application not only optimizes the collaborative work capacity of distributed DDC controller, but also improves the security and resource utilization efficiency of network, so that the controller can be more flexible and efficient when coping with complex network environment, to bring more reliable use experience and higher security guarantee for users.

The application provides a robot environment perception method based on multi-sensor fusion, comprising the following steps: performing space-time synchronization processing on original multi-sensor data to generate synchronized perception data; judging whether there is a semantic landmark matching the original or synchronized data in a topological map, wherein the matching condition is that the geometric primitive of the semantic landmark in the topological map and the same geometric primitive existing in the data are matched; when it is confirmed that there is a matching landmark, selecting the matching landmarks to form a set; based on the set, performing pose correction on the original multi-sensor data, fusing different pose constraints in the matching landmarks into the original data, and obtaining corrected data for robot path planning. The application can improve the consistency of multi-sensor data and the accuracy of robot environment perception, and provides reliable correction data for path planning.

The present application relates to the technical field of data processing, and more particularly to an intelligent scheduling method and system for an unmanned single-track hoist in a mine. The method comprises the following steps: scanning the whole mine roadway by a patrol vehicle to construct a three-dimensional topological map; when the vehicle enters a blind area, a ground scheduling server generates a shadow vehicle according to the running state data of the vehicle, and generates an offline strategy package in combination with the historical running data of the vehicle under standard working conditions and the map attributes of the blind area section; the vehicle obtains a real trajectory after resuming communication when it drives out of the blind area; a vehicle aging factor and a corresponding position slope angle of the shadow vehicle are introduced to calculate a net acceleration to iteratively deduce the position of the shadow vehicle, and the total length of the safety envelope is synchronously calculated; the aging factor is corrected based on the residual error between the real trajectory and the deduced position, which is used to iteratively optimize the deduction of the shadow vehicle and safety warning when the vehicle enters the blind area next time. The present method can easily grasp the dynamic position of the vehicle during network interruption by constructing a shadow vehicle, and greatly improves the safety under complex terrain.

The invention provides an unmanned aerial vehicle multi-mode topological map navigation method based on language guidance. The unmanned aerial vehicle multi-mode topological map navigation method comprises the steps that a multi-frame image sequence and a natural language task instruction in the flight process of an unmanned aerial vehicle are obtained; based on the natural language task instruction, extracting a semantic key frame from the multi-frame image sequence; based on the semantic key frame, constructing a topological node representing image, language and spatial information; based on the topological node, determining a topological edge of semantic space joint constraint; and on a semantic space topological graph, the optimal path of the unmanned aerial vehicle is determined by adopting a search algorithm, and the semantic space topological graph is constructed by topological nodes and topological edges. According to the invention, the unmanned aerial vehicle can autonomously construct the semantic map in an unknown environment and complete effective navigation according to the language instruction.

The application relates to the technical field of robots, in particular to a lightweight topological map construction method for scene recognition, which comprises the following steps: collecting data and processing the data to obtain accumulated point cloud; extracting scene descriptors; calculating the similarity between the descriptors to generate topological nodes; and calculating an optimal topological map. The application describes a scene according to multi-frame point cloud data accumulated according to a robot running track, extracts a descriptor of the point cloud, and judges whether to generate a topological node according to the similarity of the descriptor; the application can guarantee effective construction of a lightweight topological map, is particularly suitable for the demand of large-range scene topological map construction, and compared with an appearance-based topological map construction method, the number of topological map nodes constructed by the application is greatly reduced, but the reliable scene recognition performance can still be guaranteed.

The invention discloses a topological map generation method, device and equipment, and belongs to the technical field of intelligent driving, and the topological map generation method comprises the steps: determining a corresponding vehicle pose of a vehicle in a parking process and first sensing data for a stand column; based on the first sensing data and the vehicle pose, determining the column position of the column; based on the driving track of the vehicle in the parking process, determining an intersection position through which the vehicle passes in the parking process; based on the stand column position and the intersection position, the intersection shape of an intersection through which the vehicle passes in the parking process is determined; determining a connection relationship between the road and the intersection based on the intersection shape and the driving track; and generating a topological map corresponding to the parking process based on the intersection position, the intersection shape and the connection relationship between the road and the intersection. According to the scheme, the topological map which accurately and simply expresses the intersection shape and the connection relation between the road and the intersection can be constructed, the marking dependence is overcome, and the topological expression of the complex intersection is effectively simplified.

The invention discloses a large-scale scene positioning method and system based on a double-layer scene semantic topological graph, and relates to the technical field of unmanned system visual environment perception. The method comprises the following steps: constructing a hierarchical semantic topological map which at least comprises an image layer and an object layer, and establishing a hierarchical association relationship between the two layers through a topological edge; generating image layer nodes and object layer nodes containing object instance semantics and appearance features based on the scene image data; establishing a hierarchical association relationship to enable the image layer node to serve as an index of the object layer node; and receiving a query image and carrying out progressive matching, firstly screening out candidate image nodes in the image layer, and then carrying out matching in the object layer nodes associated with the candidate image nodes according to the hierarchical association relationship to determine a positioning result. According to the method, through layered map organization and a coarse-to-fine matching strategy, the problems of high positioning calculation complexity and similar environment ambiguity in a large-scale scene are solved, and the efficiency and stability of robot object-level positioning are remarkably improved.

This invention relates to the field of image processing and discloses a method for tracking multiple moving targets with resistance to occlusion interference. The method includes: identifying target pixel clusters in a video frame sequence and determining their occlusion state; extracting residual visible pixel clusters for target pixel clusters in the occluded state, and constructing a local topological map using the geometric relationships between feature pixels to generate a topological feature vector; extracting optical flow vectors from the occlusion edges and converting them into size adjustment parameters for the spatiotemporal trajectory constraint envelope to determine the search area for subsequent video frames; calculating the cosine distance between candidate pixel clusters and the topological feature vector within the search area to complete trajectory association. This invention utilizes local topological invariants to maintain target identity, eliminating the system's dependence on global feature smoothness; and sensing blind zone movement trends through edge optical flow to narrow the search range, suppress identity switching, and ensure continuous and stable trajectory under complex conditions.

The application discloses a large model driven path growth type semantic topology self-optimization navigation decision closed loop method in an unknown environment, takes the traveled path of a robot as the only topology skeleton, incrementally constructs a path growth type semantic topology map, only includes the path nodes of the traveled area, the surrounding task related semantic nodes and the front exploration nodes, does not store irrelevant environment information, and completely eliminates redundancy from the source; in combination with large model driven multi-dimensional self-optimization operation, the topology structure is further simplified, the map compactness is maintained, the topology map storage and the calculation resource occupation are reduced by more than 50%, the nodes and edges are subjected to differential multi-dimensional feature coding, the node coding space, semantic, task and state information are coded, sufficient feature information is ensured, excessive redundancy is avoided, sufficient and accurate judgment bases are provided for topology self-optimization and navigation decision, in combination with navigation decision, only the optimized effective feature information is called, the decision calculation amount is greatly reduced, and the planning efficiency is improved by more than 20%.

The application discloses a photoresist stripping liquid stripping detection method and system, which comprises optical confocal collection and flat field preprocessing, photoresist residual area adaptive segmentation, three-dimensional height mapping and residual glue area quantification, edge shadow extraction and lateral erosion angle derivation and comprehensive topological map output. The application constructs a comprehensive evaluation method considering residual glue area and lateral erosion, effectively overcomes subjective deviation and false error judgment of traditional optical equipment, and provides a high-precision and automatic quantitative measurement tool for optimization of semiconductor wet stripping process and stripping liquid formula.

A method for path planning of a driving robot by using a feature map, includes: a feature map generation step of generating a feature map including multiple nodes and multiple blocks on the basis of a topological map for a random space; a primary block search step of acquiring a departure node and an arrival node from among the multiple nodes, and designating a departure block and an arrival block on the basis of the departure node and the arrival node; a secondary block search step for determining the drivability of each of multiple subsequent blocks placed after the departure block, and performing path designation; and a termination step of terminating path planning if a random subsequent block is the arrival block.

The application provides a dynamic repair welding method and system based on welding quality evaluation, and relates to the technical field of data processing.The method comprises the following steps: obtaining three-dimensional point cloud data and image data of a welded area; determining the welding quality of the welded area by a welding quality evaluation model based on deep learning according to the three-dimensional point cloud data and the image data; judging whether the welding quality is qualified; if yes, repair welding is not needed; otherwise, the next step is entered; updating a three-dimensional topological map; performing global repair welding path planning in the three-dimensional topological map by an RRT* algorithm; performing local optimization on the global repair welding path by a gradient ascent algorithm to generate a final repair welding path; performing repair welding according to the final repair welding path, and returning to continue monitoring.The application can adaptively generate a repair welding path according to the change of welding quality in a real-time welding process, dynamically repair welding defects, and effectively improve the degree of welding automation.

A lightweight semantic map construction method for lawnmower robots includes: designing a lightweight semantic SLAM method, using an RGB camera to identify targets and a depth camera to measure depth information, thereby performing semantic extraction and 3D position estimation of the targets; establishing a semantic map and a topological map, fusing the information extracted from both, with the fused map providing target location information for target search, and continuously updating the map using information collected by the camera; fusing location information provided by GPS and pose data acquired by IMU based on Kalman filtering to accurately determine the lawnmower robot's own position; exploring the lawnmower robot's working area using a random exploration tree; dividing the lawnmower robot's working area into multiple sub-regions using an unsupervised region partitioning method; delineating the environment and assigning targets to a specific sub-region based on their distance from the center of the target region, thereby improving the performance of the target search task.

The present application relates to the technical field of measurement, in particular to a kind of full parameter measurement method of arc end tooth under error driving, to solve the problem that traditional projection method cannot obtain correct addendum position, three-coordinate scanning needs to rely on standard division circle parameter, it is difficult to accurately measure when there is no original processing parameter, the present application is directly measured and the key parameters are preliminarily calibrated by optical projection method, the number of gear teeth is determined by three-coordinate scanning, and the preliminary value of full parameter is calculated, the theoretical tooth profile model is constructed by inputting preliminary parameter into gear measuring center, the actual topological map is obtained by scanning actual tooth surface, and the key parameters such as pitch diameter are adjusted iteratively according to error mode after comparison, until the error is up to standard, three-dimensional model is constructed based on correction parameter and compared with workpiece to verify.The method does not need original processing parameter, and the accuracy and applicability of arc end tooth parameter measurement are improved.

The invention discloses an urban low-altitude meteorological monitoring method and system based on multiple unmanned aerial vehicles, relates to the technical field of urban meteorological monitoring, and discloses the urban low-altitude meteorological monitoring method and system based on the multiple unmanned aerial vehicles. According to the method, the layout of a monitoring grid is dynamically adjusted in combination with a computational fluid mechanics model, meteorological data are calibrated by using an ultra-wideband positioning system, and finally a high-precision urban low-altitude meteorological distribution model is generated, so that the problems of insufficient space coverage, dynamic response lag and poor data space relevance of a traditional monitoring method are solved; the monitoring precision can be improved, the resource allocation can be optimized, and the relevance between the meteorological data and the urban three-dimensional structure can be enhanced.

The invention provides a dry-mixed mortar strength evolution modeling method and system. The method comprises the following steps: acquiring synergistic excitation effect data (including an activity index and a hydration heat release curve) of the dry-mixed mortar waste residues, and analyzing reaction kinetics to generate a waste residue-cement interaction characteristic matrix; a temperature field and an acoustic emission signal in the hydration process are monitored in real time through a thermoacoustic synchronous sensing array integrating a thermocouple and piezoelectric ceramics, and a thermoacoustic coupling space-time distribution diagram is output based on space-time relevance; fusing the interaction characteristic matrix and the thermoacoustic distribution diagram by using a graph neural network, and constructing a waste residue / cement / water molecule multi-topology interaction diagram; and simulating a collaborative excitation path in the graph, dynamically mapping the topological graph into intensity evolution curves of different ages by adopting an intensity trajectory prediction algorithm, and quantifying the contribution degree of the waste residue. Accurate prediction of the waste residue resource utilization efficiency is achieved, the waste residue mixing amount is optimized, and the prediction precision is improved.

The invention relates to a low-voltage distribution area user-transformer relation checking method based on multi-source data fusion. The method comprises the following steps: collecting multi-source information and a topological connection relation of a user side and a distribution transformer side; preprocessing the data by adopting a meta-learning enhanced FCM-physical rule hybrid cleaning mechanism; constructing a differentiable topology perception fusion tensor, and converting the time series data into a multi-scale two-dimensional space image through an improved Grubrum angle field; respectively inputting the time sequence data, the two-dimensional space image and the topological graph into a neural network three-path model for feature extraction; and aligning heterogeneous feature representation through cross-modal contrast learning, outputting the three paths through a triple dynamic fusion mechanism to perform feature fusion, and outputting a user change relation checking result. According to the method, the electrical coupling relation is dynamically captured through differential topology modeling, the feature expression capability is improved in combination with cross-modal contrast learning, the adaptability problem under dynamic change of the power distribution network structure is solved, and the user change relation identification precision and robustness are remarkably improved.

The application is suitable for the technical field of inspection, and provides an inspection method, device, terminal equipment and storage medium, comprising: determining a target inspection position according to an inspection task, determining a first route according to a topological map and the target inspection position for each target inspection position, the first route being an optimal route between a first position and the target inspection position, determining a second route according to each first route, the second route being an optimal route for an inspection equipment to execute the inspection task, navigating the inspection equipment according to the second position and the second route, and collecting an environmental image of the target inspection position by the inspection equipment when the inspection equipment reaches each target inspection position, detecting whether the environmental image exists a target equipment in the inspection task, determining position information of the target equipment when the environmental image exists the target equipment, and inspecting the target equipment according to the position information of the target equipment. The application can realize automatic inspection and improve the automatic inspection efficiency of the inspection equipment.