1305 results about "Path search" patented technology

The invention provides an intelligent question and answer method and system based on a knowledge graph, and relates to the technical field of knowledge graphs, the method comprises the following steps: S1, integrating multi-source heterogeneous data to construct an initial knowledge graph; s2, analyzing the questions of the user, executing single-hop query and judging whether a result meets requirements or not; if not, entering S3, performing multi-hop dynamic search based on an adaptive path extension algorithm, and generating a reasoning path and evidence; s4, calling a large language model to combine with an attention mechanism to perform semantic matching on a result or a path, and screening an optimal answer; and S5, correcting the knowledge graph and performing closed-loop feedback to the query process to realize continuous optimization. Through cooperation of the knowledge graph and the large language model and combination of dynamic path search and semantic matching, the problems that a traditional method is insufficient in knowledge coverage, low in reasoning efficiency and poor in answer interpretability are solved, the method has the advantages of being efficient, accurate and self-optimized, and the performance and user experience in a complex scene are remarkably improved.

The invention relates to a multi-objective optimization scheduling method and system for a multi-AGV flexible job shop. The method comprises the steps of collecting job shop layout data, AGV operation parameters and production task data, and constructing a scheduling system basic model; performing recurrent neural network training and physical constraint model integration to obtain a hybrid scheduling prediction model; subtask decomposition and path search processing are carried out, and a dual-objective optimization model is obtained through constraint linearization conversion; performing particle swarm optimization solution on the dual-objective optimization model, and obtaining a non-dominated solution set through two-stage iterative calculation of an adaptive weight strategy and constraint conversion; performing multi-dimensional evaluation calculation on the non-dominated solution set to obtain an optimal scheduling execution scheme; and performing model feedback updating on the hybrid scheduling prediction model to obtain a target scheduling prediction model. According to the invention, multi-target balance of task completion time and energy consumption is realized, and the real-time response capability and operation stability of the system are improved.

The invention provides an autonomous navigation path planning method, device and equipment for a humanoid robot in a complex environment. A navigation task is determined by obtaining the current position and path requirement of the robot; constructing a constraint preposition map based on body size constraint, joint motion constraint and dynamic balance constraint, and calculating a feasible motion space of the robot in advance; acquiring environment sensing data for variation trend analysis, and predicting a future movement track of the dynamic obstacle to generate a dynamic environment prediction sequence; establishing a bidirectional planning mechanism, performing forward and reverse path search at the same time, and generating a plurality of candidate path hypotheses through meeting point detection and path fusion; analyzing a human behavior pattern to identify a potential passage conflict area, establishing a social negotiation strategy, and taking an intermediate meeting point as a social key node to adaptively adjust a candidate path; the optimal safety path is determined through multi-dimensional safety evaluation of the falling risk, the collision risk and the energy consumption risk, and intelligent autonomous navigation of the humanoid robot in a complex environment is achieved.

The invention relates to the technical field of low-altitude aircraft navigation, and discloses a low-altitude aircraft track real-time planning method and system. The system comprises a flight situation awareness module, a track constraint calculation module, a real-time track planning module, a conflict prediction module and a track dynamic correction module. The flight situation sensing module generates a flight situation matrix through multi-source data fusion; a track constraint calculation module extracts static obstacle contours and dynamic obstacle tracks according to the static obstacle contours and the dynamic obstacle tracks, and generates a multi-dimensional track constraint set in combination with aircraft performance parameters; the real-time flight path planning module builds a three-dimensional flight path search domain by using an adaptive space division technology, and iteratively solves an optimal flight path sequence by using an intelligent search algorithm; the conflict prediction module combines the real-time dynamic obstacle trajectory to calculate the space-time proximity, and generates a conflict early warning map; and the track dynamic correction module re-draws an obstacle avoidance constraint area according to the map, and triggers local track correction. The system improves the comprehensiveness, real-time performance and safety of flight path planning, and guarantees the stable operation of the low-altitude aircraft.

The invention relates to a time delay optimized satellite network adaptive routing method and system, and belongs to the technical field of satellite communication. The method comprises the steps of multi-hop information age construction, multi-path routing, link state sensing, flow segmentation adaptive routing, dynamic routing decision and the like. A multi-hop information age model is adopted to consider the time-varying property of a link state, the real-time property of path information is accurately estimated, and the timeliness of data updating is ensured; a multi-path search algorithm predicts link occupation frequency according to ephemeris information to construct a plurality of disjoint transmission paths, so that the traffic congestion problem is relieved, and the link resource utilization rate is optimized; a flow segmentation adaptive routing algorithm adjusts the path flow distribution proportion, reduces the data packet loss rate and the information age, and guarantees the stability of time delay sensitive data transmission; according to the method, resource utilization is balanced in a high-dynamic satellite network, link congestion is effectively prevented, the overall transmission efficiency and reliability are improved, and a high-adaptability and efficient transmission scheme is provided for time delay sensitive services.

The invention relates to the field of airline planning, and discloses a digital twin system for low-altitude airline planning and a construction method, and the method comprises the steps: obtaining a spatial perception data set of a preset sensor in a target airspace, carrying out the fusion of the spatial perception data set, obtaining the fusion perception data, obtaining the historical flight hidden danger data of the target airspace, and obtaining the historical flight hidden danger data of the target airspace; performing multi-layer convolution on the fusion perception data by using the historical flight hidden danger data to obtain a risk analysis result, performing fuzzy fusion on preset risk factors, generating a dynamic obstacle risk field according to the risk factors after fuzzy fusion and the risk analysis result, performing flight simulation on the dynamic obstacle risk field, and obtaining a flight simulation result; and collecting flight simulation real-time data in the flight simulation process, generating an air route space cost map according to the flight simulation real-time data, and performing optimal path search on the air route space cost map to obtain a low-altitude air route scheme. In the face of airspace actual risks, the searching efficiency of the optimal path in low-altitude route planning is improved.

The invention discloses a railway station facility full life cycle information query method based on digital twinning. The method comprises the steps that a unified facility object with a unique logic identifier is generated based on multi-source heterogeneous data aggregation; constructing a facility tense version model containing time sequence nodes by using an event-driven rule; in combination with an engineering constraint knowledge base and statistical characteristics, evaluating physical feasibility and statistical association strength between events, introducing life cycle stage risk factors, and constructing a facility full life cycle causal chain model; and based on the model, responding to the explanatory query, executing a constrained path search in the facility full life cycle causal chain model, and generating a life cycle query result set containing a causal path. According to the method, the pseudo-correlation problem generated by pure data mining can be effectively solved, the cumulative influence of early-stage risks in the design and construction stage on later-stage operation is quantified, and accurate tracing and explanation of cross-stage fault causes are realized.

The invention discloses a quadruped robot obstacle avoidance control method and system based on path planning, and relates to the technical field of quadruped robot obstacle avoidance control, and the method comprises the steps: obtaining environment point cloud data, image data and quadruped robot motion speed data, and carrying out the terrain semantic segmentation and semantic pixel back projection of the image data, thereby obtaining a quadruped robot obstacle avoidance result; generating semantic point cloud data, combining the semantic point cloud data with the environment point cloud data subjected to motion compensation, and constructing a semantic annotation grid map; performing global path search on the semantic annotation grid map to generate a global smooth path; when the quadruped robot advances along the global smooth path, path nodes on the global smooth path are extracted at a fixed step pitch, the terrain category and the grid occupation state of each path node are judged according to the semantic annotation grid map, and a local reference path is generated; and executing a multi-stage obstacle avoidance strategy on the local reference path, and generating a foot end track sequence.

The invention relates to the technical field of electronic design automation, in particular to a local layout wiring method based on sequence value correction and historical guidance search, which comprises the following steps: calling a multi-source dynamic sequence value wave diffusion path search sub-algorithm, generating initial paths for all wire nets, and initializing a historical solution set and a current solution sequence; random disturbance is carried out based on the current solution sequence, and candidate solutions are generated; judging whether the candidate solutions meet design rule constraints or not; checking whether the maximum iteration frequency is reached or no improvement frequency limit exists, if yes, entering the step of outputting the optimal solution, and otherwise, returning to the step of generating the candidate solution; selecting a wiring path which has an optimal target function value and meets all constraints from the historical solution set, and outputting a final result; according to the local layout wiring method based on sequence value correction and historical guidance search, the problems of high-density region wiring feasibility, complex design rule satisfaction, multi-objective optimization, calculation efficiency and the like can be solved.

The invention provides an electric power inspection path planning method and device and electronic equipment, and relates to the technical field of unmanned aerial vehicle electric power inspection. The method comprises the following steps: acquiring obstacle information of an electric power facility environment, wherein the obstacle information comprises the type and position of an obstacle; based on the type of the obstacle and a preset safety distance coefficient, determining a differentiated safety distance, the type of the obstacle including a power transmission line, a transformer substation, a tower and other obstacles; based on the obstacle information and the differentiated safety distance, obtaining an initial global path through a path search algorithm; based on a preset multi-objective optimization function, the initial global path is optimized, a Pareto optimal path set is generated, and the multi-objective optimization function comprises a path length objective, a safety margin objective and an electromagnetic safety objective; and determining a target global path from the Pareto optimal path set based on a preset inspection task mode. According to the invention, the inspection efficiency and adaptability can be improved while the safety is guaranteed.

The invention discloses a path planning method based on an improved Hybrid A * algorithm and a DWA algorithm. The path planning method specifically comprises the following steps: establishing a grid map for a working environment and setting task starting and ending points; improving a heuristic function in the A * algorithm; the cost function of the Hybrid A * algorithm is improved, the path cost in the improved A * algorithm is used as the complete heuristic constraint cost with obstacles, the extension distance of the Dubins curve is used as the incomplete constraint heuristic cost without obstacles, and a variable step size search strategy based on the obstacle distance is adopted; smoothing the path searched by the global path planning algorithm; extracting path key nodes; optimizing a DWA local path planning algorithm; and outputting the optimal motion path. The efficiency of path planning of the workshop inspection robot in the unstructured complex environment is effectively improved, the real-time performance and safety are enhanced, and the workshop inspection robot can dynamically avoid obstacles while finding the optimal path in the complex environment.

The invention discloses a ship path dynamic planning method based on a collision risk field, and the method comprises the following steps: carrying out the grid division of a map of a navigation water area of a ship, and obtaining a grid map of the navigation of the ship; performing path search on the grid map by adopting a path planning algorithm to obtain an initial route of the ship; establishing a collision risk field model of the target ship according to real-time navigation parameters of the target ship, and substituting the coordinates of the central point of each grid in the grid map into the collision risk field model to obtain a collision risk value of each grid in the grid map; when the ship sails to the grid with the collision risk value larger than a set threshold value, the grid which is closest to the terminal point and has the collision risk value smaller than the set threshold value serves as a local optimal point, and the ship route of the ship is updated; and repeating the steps until the ship arrives at the destination.

The invention discloses a branch topological structure automatic switching control method and system based on load balancing, and relates to the technical field of automatic switching control, and the method comprises the following steps: obtaining working condition data, and constructing a joint map; extracting a power conduction path from the trunk node to each load node based on the joint map to form a high-load segment set; aiming at the high-load transmission segment, constructing a multi-target switching feasibility set, and generating a coupling relation mapping graph; based on the coupling relation mapping map, constructing a path search model, and solving an optimal topology switching path by adopting an enhanced iterative algorithm; and generating a topology switching sequence according to the optimal topology switching path, and implementing power transfer regulation and control on a high-load transmission section. According to the method, the joint atlas is constructed, the optimal topology switching path is generated, local overload is effectively relieved, power fluctuation is weakened, and the overall load balancing level and the active regulation and control capability of the system are improved.

The invention relates to the technical field of UV printing, and discloses an intelligent scheduling method and system for UV printing nozzles based on multi-objective optimization, and the method comprises the steps: collecting the real-time state data of a physical UV printing system, and forming a state data set; establishing a digital twinborn model at the edge computing node; scheduling simulation is carried out by adopting an improved ant colony algorithm, and a scheduling scheme is generated through path search of virtual ants; the scheduling scheme is applied to a physical system, feedback data are collected, a physical mathematical bidirectional feedback system is constructed, and hierarchical pheromones of edge nodes and a cloud end are cooperatively updated; each UV printing nozzle autonomously calculates a multi-objective optimization function value, and an optimal working strategy is selected; according to the method, a completely distributed self-organizing scheduling architecture is adopted, so that the single-point fault problem and the expansibility limitation of traditional centralized scheduling are effectively solved.

The invention discloses a cable trench inspection robot path planning method and device and a medium, a cable trench three-dimensional semantic map is constructed through multi-sensor fusion, and a laser radar and a depth camera are combined to accurately identify the spatial distribution of a cable support, a suspension cable and an obstacle. An improved directional path search algorithm is adopted, firewall passing sequential logic and lifting platform kinematics constraints are integrated, and a multi-mode inspection path is generated. The environment change is sensed in real time in the inspection process, the path is adjusted online through a dynamic path optimization engine, a planning strategy is iteratively optimized based on historical data, a digital twin system is introduced to realize path pre-verification, and the firewall interaction efficiency and the exception handling capacity are optimized by adopting reinforcement learning. According to the invention, the technical problems of poor real-time performance of path planning and low reliability of facility interaction in a complex cable trench environment are solved, and the inspection efficiency and safety are significantly improved.

The invention is suitable for the technical field of robots, and provides a path planning method and a robot, and the method comprises the steps: obtaining the environment information of a target area, building a grid map according to the environment information, and enabling the grid map to comprise a starting point area, an end point area and an obstacle area; determining a global path through a path search algorithm according to the grid map; in the process of controlling the robot to move along the global path, performing local path optimization through a dynamic window algorithm; wherein the dynamic window algorithm calculates the score of each candidate local path through a trajectory cost function and determines the optimal local path, and a strategy network output score obtained by predicting the candidate paths through a pre-trained deep learning strategy model is introduced into the trajectory cost function. The adaptive capacity of the robot in a dynamic environment can be improved.

The invention discloses a case evidence logic deduction method based on a graph neural network. The method comprises the following steps: S1, forming a standardized case evidence data set; S2, forming a multi-level case evidence graph; s3, performing vectorization representation on case evidence data nodes and edges of the multi-level case evidence graph, and calculating weights of the case evidence data nodes; s4, inputting the multi-level case evidence graph into a graph neural network, and calculating a logic relation weight between case evidence data nodes; s5, identifying case evidence data nodes with low credibility; and S6, based on the logical relationship weight of the case evidence data nodes and a causal reasoning result, calculating an optimal case evidence deduction path by adopting a path search algorithm, identifying a case core fact chain, and generating a case deduction conclusion. According to the invention, different types of case evidence data can be reasoned in respective hierarchies, information mixing is effectively avoided, and the accuracy and interpretability of case fact deduction are improved.

The invention discloses a three-dimensional path planning method for a low-altitude unmanned aerial vehicle, which belongs to the technical field of unmanned aerial vehicle path planning and comprises the following steps: constructing a three-dimensional flight environment model; according to a particle swarm optimization method, performing global path search and path cost optimization on the three-dimensional flight environment model to obtain optimized path cost and position corresponding to each particle in a particle swarm; according to the path cost and the position of each particle in the particle swarm, performing repeated iteration of selection, crossover and mutation operation on the particles through a genetic algorithm, and obtaining a global optimal path solution based on the optimal path cost of each iteration; and according to the globally optimal path solution, performing conversion to obtain an optimal path under the target coordinate system, and performing drawing through a drawing function to obtain an optimal path in the three-dimensional flight environment model. The problems of low efficiency and insufficient reliability in unmanned aerial vehicle path planning are solved.

The invention provides a data quality detection and improvement system for a large language model, and relates to the technical field of code quality management. The data analysis and characteristic extraction module is used for extracting structured and semantic characteristics of codes and constructing a code distribution diagram; the multi-dimensional quality detection module comprehensively evaluates the data set quality from three aspects of semantic diversity, structural consistency and error mode; the code optimization and verification module generates an optimization suggestion based on a detection result, and verifies the effectiveness of an optimization scheme through dynamic evaluation and unit testing; the feedback and self-adaptive optimization module is combined with developer feedback and runtime performance test to dynamically adjust a repair strategy, and the complex code repair efficiency is improved through quantum computing auxiliary path search; according to the method, full-process automation from quality detection to optimization verification is achieved, the method is suitable for multi-dependency and multi-module complex code repair tasks, and the quality and efficiency of the code life cycle are improved.

The invention relates to the technical field of semiconductor manufacturing, in particular to an automatic loading and unloading control system for semiconductor material plates. A clamping force dynamic control module; the path planning and obstacle avoidance module is used for dividing safety levels of loading and unloading areas on the basis of material plate stacking parameters, and generating an obstacle avoidance track by adopting an improved path search algorithm; optimizing an acceleration curve of the path according to the joint load data of the mechanical arm; the closed-loop verification module is used for carrying out deviation comparison on the actual pose of the tail end of the mechanical arm and the target coordinates, and if the deviation exceeds the limit, the visual positioning and morphology detection module is triggered to cooperatively reset to the path planning and obstacle avoidance module; the visual positioning and morphology detection module and the closed loop verification module are executed in sequence, and output parameters of the previous module serve as input parameters of the next module. Through close cooperation of the modules, efficient and accurate automatic loading and unloading control is achieved, the automation level is improved, and operation safety and accuracy are guaranteed.

The invention discloses a dynamic path optimization method based on response time domain attenuation, and relates to the technical field of artificial intelligence and intelligent path planning, and the method comprises the steps: generating a node network composed of navigation points, terrain units or interaction regions, and forming a node network topology structure; generating a dynamic state feature set used for describing game scene changes, and forming input data used for follow-up node priority dynamic adjustment; converting the dynamic state feature set into node-level standardized event data, and distributing the node-level standardized event data to a node state management module through an event bus; setting a current node priority for each node in a node state management module based on the node-level standardized event data; forming a time domain attenuation model of the node priority; the priority recovery coefficient is improved; in the path planning stage, executing a dynamic path search algorithm to generate a passing path with the minimum total cost and the optimal path smoothness; when it is detected that player operation or scene change causes node response mutation, a local re-planning mechanism is triggered, smooth path transition is achieved, and overall jumping is avoided. According to the method, the problems of path congestion, frequent switching and unsmoothness caused by lack of dynamic node state and event response calculation in the prior art are solved. Through node priority time domain attenuation and dynamic path optimization, the technical effects of smooth path, efficient passing and node load balancing are achieved.

The invention discloses a mechanical arm obstacle avoidance path planning method based on an improved RRT-Connect algorithm, a smearing mechanical arm and a masonry robot. The mechanical arm obstacle avoidance path planning method comprises the steps that firstly, a fixed sampling function is adopted in a three-dimensional space formed by a starting point Xinit and a target point Xgoal of a path to generate a fixed point; and respectively and simultaneously constructing four random trees between the starting point and the fixed point and between the fixed point and the target point to carry out path search, and generating a path from the starting point to the target point. A target guiding sampling method based on a heuristic function can be introduced into the algorithm of the four-random-tree collaborative path searching mechanism, and the sampling probability is adjusted; and a better path planning effect is achieved by setting a self-adaptive step length strategy, a greedy strategy and other technical means. According to the method, the path planning of the mechanical arm is realized by setting the fixed sampling points to perform the four-way RRT-Connect algorithm, so that the rapid planning is ensured, the path time consumption is reduced, the collision with an obstacle is avoided, and the robustness of the path is enhanced.

The invention discloses a transformer substation positioning and navigation method and system integrating positioning and visual auxiliary positioning. The method comprises the following steps: establishing a background electromagnetic field distribution baseline graph associated with a three-dimensional reference map; electromagnetic field data of the transformer substation in an emergency response mode is collected through the unmanned aerial vehicle, and the abnormal field intensity of a space electromagnetic field and a fault source pointing vector pointing to a fault source are calculated; constructing a risk adaptive elliptical forbidden zone; calculating a passage cost index Cto of the unmanned aerial vehicle passing through each three-dimensional grid in the three-dimensional reference map by using the fault source pointing vector and the risk adaptive elliptical forbidden zone; and searching a path which is from the current position of the unmanned aerial vehicle to a preset target point, bypasses the risk adaptive elliptical forbidden zone, faces the fault source and has the lowest total passing cost index Cto by adopting a preset path search algorithm. According to the method, the risk self-adaptive elliptical forbidden zone is constructed and is used as the three-dimensional grid forbidden assignment processing, so that the dynamic global path avoidance of the sudden dangerous zone is realized.

The invention discloses a personalized self-driving travel route planning method and system, and relates to the technical field of intelligent travel, and the method comprises the steps: obtaining the historical travel track data of a user, and collecting the real-time road condition data and weather information around a destination; extracting a user preference feature matrix from the historical travel trajectory data of the user by using clustering analysis, constructing a geographic position-point-of-interest association network, and dividing the geographic position-point-of-interest association network by using a community discovery algorithm to obtain destination groups conforming to user preferences; constructing a road network cost matrix, performing path search by using an improved ant colony algorithm, and generating candidate routes in combination with real-time road conditions; and mapping the candidate route to a rasterized map, carrying out comprehensive evaluation on the candidate route, and selecting a Pareto optimal solution as a recommended route. Practicality and reliability of route planning can be improved, a reliable travel scheme is provided for a user, and travel experience and satisfaction of the user are improved.

The invention relates to the technical field of new energy, and particularly discloses a new energy heavy truck energy-saving path planning method and electronic device.The new energy heavy truck energy-saving path planning method comprises the steps that a layered road network based on an energy consumption model is constructed, and the layered road network divides a road into multiple levels through a comprehensive weight formula, wherein the high-level road network comprises low-energy-consumption main roads, and the low-level road network comprises all road types; and on the basis of vehicle real-time state parameters and destination information, a two-way A algorithm is adopted to carry out path search in the layered road network, the two-way A algorithm is synchronously expanded from a starting point and an ending point, and the search direction is optimized on the basis of a dynamic heuristic function. According to the new energy heavy truck energy-saving path planning method provided by the embodiment of the invention, three major pain points of high energy consumption, difficult energy complementation and poor real-time performance in new energy heavy truck path planning are optimized and solved through modules of layered road network construction, dynamic weight adjustment, bidirectional A * algorithm optimization and the like, and the energy complementation bottleneck problem of the new energy heavy truck is solved.

The invention discloses a path planning and trajectory optimization method for a mobile robot in a non-flat terrain, and the method comprises the following steps: S1, the mobile robot employs a laser radar to detect the surrounding environment, and an SLAM module constructs a three-dimensional map according to point cloud data and odometer data collected by the laser radar in real time; and S2, a trafficability analysis module performs terrain trafficability evaluation based on the generated three-dimensional map, and generates a trafficability layer accordingly. And S3, the global planning module performs path search in the trafficability layer to obtain an initial path of the mobile robot from the starting point to the target point. And S4, a trajectory optimization module optimizes the initial path to ensure that the obtained trajectory meets the kinematics constraint of the mobile robot. And S5, vertically mapping the optimized trajectory to the non-flat terrain surface to obtain a final path for direct tracking of the mobile robot. According to the method, it can be ensured that the mobile robot generates a feasible track conforming to kinematics constraints in the non-flat terrain.

The embodiment of the invention provides a multi-AGV path planning method and a related device. The method comprises the steps that in the single AGV path searching stage, a dynamic weight coefficient, a steering punishment mechanism and a Bezier curve smoothing strategy are introduced on the basis of a traditional A * algorithm, the operation efficiency of the algorithm can be improved, the unnecessary turning frequency in a path can be reduced, and the smoothness of the path can be improved. In a multi-AGV path conflict coordination stage, most traditional avoidance strategies use a fixed priority strategy, and the relative importance of tasks among the AGVs is not considered, however, according to the method, the avoidance among the AGVs can be implemented according to the relative importance of the tasks by setting a dynamic priority strategy. In the multi-AGV online navigation stage, a traditional DWA algorithm is prone to falling into local optimum, and the situation can be avoided by adopting the improved DWA algorithm, so that local obstacle avoidance can be achieved, and falling into local optimum can also be avoided.

The invention relates to the technical field of cable layout design, in particular to a branch cable automatic layout method of a given topological structure based on a dynamic programming algorithm. Comprising the following steps: determining an optimization target of automatic cable layout design according to engineering requirements of wiring, giving a three-dimensional model and a wiring harness electrical definition of a product to be wired, constructing a path search map on sampling points on the surface of the model, and executing an automatic cable layout algorithm based on dynamic planning in the path search map, solving a cable path and the position of a branch point which meet the constraint condition and enable the wiring objective function to be optimal, and finally obtaining a geometric model of the cable through curve fitting and profile endowing. The method has the advantages of being simple in algorithm and high in solving efficiency, the accuracy of wiring and optimal path selection can be improved, complex connection requirements can be met, the automatic layout efficiency and quality of branch cables can be effectively improved, and the method has high practical application potential in cable layout design of complex mechanical and electrical products.

The invention relates to the technical field of nuclear power equipment quality management and control, in particular to a nuclear power unit quality defect source analysis and total value chain tracing method, which comprises the following steps: S01, collecting total value chain multi-modal data including structured data, logs, texts and sensor time sequence data, and carrying out BIO labeling, BERT coding, BiGRU-Attention feature extraction and CRF sequence labeling; constructing a mixed storage data resource pool; s02, mining association rules by adopting a dynamic pruning improved Apriori algorithm, processing sample imbalance in combination with chi-square test and an NSGAII algorithm, and analyzing defect causes; s03, a dynamic knowledge graph containing multiple types of nodes, relations and threshold attributes is constructed, and rapid defect tracing is achieved through entity linking and probability path searching; the objective of the invention is to solve the problems of difficulty in defect source calibration, low tracing efficiency and the like in nuclear power equipment quality control.

The invention provides a path planning method and system based on four-AGV cooperative carrying, and relates to the technical field of automatic logistics transportation. The method comprises the steps that a high-precision grid map is constructed, a global path is generated in combination with a simulation improved A * algorithm, dynamic weight factors are adaptively adjusted according to the obstacle density, and the path search efficiency is optimized; a time window constraint method is adopted to divide path segments and dynamically allocate time windows; real-time sensing of dynamic obstacles is fused, and a local path is adjusted based on Kalman filtering and a dynamic priority scheduling algorithm; a one-master and three-slave cooperative control architecture is adopted, a master AGV tracks a simulation path, and slave AGVs dynamically adjust control parameters through a fuzzy adaptive PID algorithm; the synchronous jacking operation of the four AGVs feeds back the state to the central server in real time through the Ethernet, so that the synchronism and safety of collaborative carrying are ensured. According to the invention, the technical problems of high path conflict rate, low trajectory tracking precision and slow obstacle avoidance response of a multi-AGV system in a complex environment are solved.