18results about How to "Reduce search time" patented technology

The invention provides an unmanned aerial vehicle routing inspection method and system based on semantic guidance and an asset value cost graph, and the method comprises the steps: reasoning a possible distribution region of a target when the target is not directly observed through analyzing the structure law of semantic information, such as an equipment number, a function partition identifier and the like, in a transformer substation; generating a confidence map to guide the unmanned aerial vehicle to efficiently inspect; constructing a semantic cost graph fusing the static asset value and the dynamic operation risk, and quantifying potential loss of different regions when collision or falling occurs; according to the real-time health state of the unmanned aerial vehicle, semantic guidance is emphasized during normal inspection through a dual-guidance function fusion and switching mechanism, and the unmanned aerial vehicle is automatically switched to asset value cost minimization guidance in an abnormal or emergency state to realize safe disposal; the system adopts a framework of semantic reasoning, cost evaluation and flight control module decoupling, and guidance intelligence and control reliability are ensured. According to the invention, the inspection blindness of the unmanned aerial vehicle is obviously reduced, and the abnormality handling risk is reduced.

The application discloses a long-range ground laser point cloud plane segmentation method, and specifically comprises the following steps: T1, determining the best neighborhood based on a dynamic search range, T2, designing a region growing algorithm based on dimensional features and the best neighborhood, and relates to the technical field of laser point cloud data processing application. The long-range ground laser point cloud plane segmentation method has density adaptability, the neighborhood search range is automatically generated based on a theoretical point spacing, and the needs of point cloud neighborhood searching at different scanning distances can be met; the construction of the best neighborhood guarantees that the calculation of point cloud local features is not affected by density changes; the estimation of the sampling interval conforms to the ground laser scanner acquisition principle, and the rationality of the theoretical point spacing is enhanced; the best neighborhood is added to the region growing, the plane segmentation algorithm is adapted to high-density change point clouds, has wide applicability of the dynamic search range, and the determination of the neighborhood search range starts from a single point, and the overall density change of the point cloud does not need to be analyzed.

The invention discloses a cooperative control method for a floating type photovoltaic-hybrid energy storage system, and the method employs a flexible connection and semi-tensioning mooring design, and is suitable for a 0-degree head wave long-period working condition. Improving maximum power tracking control, and inhibiting power point oscillation based on a partition variable step size and a prediction power algorithm; hybrid energy storage power is distributed through a low-pass filter, a storage battery and a super capacitor cooperatively process high / low frequency fluctuation, and the service life is prolonged by combining charge partition management; a virtual synchronous generator VSG adaptive control strategy is provided, an improved particle swarm optimization algorithm is adopted to optimize a J / D initial value, and frequency fluctuation is dynamically suppressed; an optical storage grid-connected system is established for verification, and the VSG technology enables the power frequency fluctuation to be quickly stabilized, thereby guaranteeing the stable operation of the system.

The invention provides an intelligent seamless switching system, method and equipment for network signals, relates to the technical field of networks, and aims to realize real-time change and high-speed seamless switching of routes. The system is characterized in that each signal forwarding node receives a signal from one source node in N source nodes at a moment and forwards the signal to other signal forwarding nodes or a destination node; the signal source synchronous calibration module is used for carrying out nth signal source synchronous calibration on the first node and the second node if the signal source identifiers of the signals received by the first node and the second node are the nth signal source identifiers aiming at the nth signal source identifier generated by the nth source node; the routing module is used for synchronously calibrating the nth signal source and determining a first path and a preselected path; and the switching module is used for switching the transmission path of the signal identified by the nth signal source from the first path to the preselected path in the process of transmitting the nth signal from the nth source node to the destination node based on the first path.

This invention relates to a method, device, and medium for multi-agent coverage search and task allocation path optimization. The specific method includes: scenario construction and problem description, which describes the characteristics of the task area, the attributes of agents and targets, and clarifies the area coverage search problem and the target task allocation problem; area coverage model design, which establishes a minimum task time model objective function and constraints, and then solves the area coverage model; and task allocation strategy and path planning algorithm, which, considering agent speed and target attributes, combines a greedy strategy and a genetic algorithm to allocate target exploration tasks to agents, optimize target exploration paths, and reduce total task time. Compared with existing technologies, this invention improves the efficiency of marine area search and target exploration through multi-agent cooperation, achieving full area coverage search and accurate target exploration.

The application discloses a kind of low-carbon scheduling method, system, equipment and medium of power system, belong to power grid low-carbon scheduling technical field, method includes initialization parameter and constructs collaborative space;By particle swarm module optimization reinforcement learning hyperparameter;Reinforcement learning module interactive experience data generation;Extract priority sample and elite particle realize two-way experience sharing;Converge after output scheduling strategy.System includes initialization module, collaborative space construction module, hyperparameter optimization module, interactive storage module, two-way experience sharing module and strategy output module.The application is coupled by constructing dynamic collaborative optimization space and two-way experience sharing mechanism, particle swarm and deep reinforcement learning.Feedback guides particle swarm to realize adaptive disturbance, avoid local optimum trap.At the same time, spontaneous optimization network parameter, significantly enhance the adaptability and generalization ability of algorithm.The scheme breaks through single algorithm decision bottleneck, improves low-carbon scheduling efficiency and power system reliability.

The utility model relates to disinfection device technical field, and disclose a blood glucose detection wound disinfection device, including the high block, the bottom of high block is provided with the spray disinfection mechanism, the bottom of spray disinfection mechanism is provided with the cotton ball storage mechanism. This blood glucose detection wound disinfection device, through setting cotton ball storage mechanism, in the use, utilize the storage cylinder of setting, can store medical cotton ball, and can replenish cotton ball to detach the storage cylinder, press the baffle to rotate to press the column, can take out the cotton ball inside the storage cylinder, simultaneously utilize the transparent storage bottle and the storage cylinder to the centralized storage mode of alcohol and cotton ball, can reduce the time of looking for, and the combination formula's big body, the centralized storage mode of both, can be convenient for long -term multiple use, and can be convenient to find before detection, realize the portable function of disinfection device, improve the convenience of use.

The invention provides a path planning method and system for personnel evacuation and obstacle avoidance, and belongs to the technical field of personnel evacuation dynamic obstacle avoidance path planning. The invention provides a Bi-RRT *-based personnel evacuation path planning algorithm with self-adaptive bias and a new improved self-adaptive extended step length. On the basis of the standard Bi-RRT * algorithm, an adaptive bias strategy which is jointly influenced by search experience and obstacles is added, so that the convergence speed of the algorithm is effectively improved, the path search efficiency is improved, and the ability of passing through narrow terrains is improved; based on a self-adaptive step length search strategy combining the repulsion size and the direction included angle, the obstacle avoidance capability is improved; in combination with improved adaptive bias, adaptive step length and bidirectional search capability, the adaptive capability to a complex evacuation space search path and the search efficiency of a multi-obstacle region algorithm are effectively improved. The method has remarkable advantages in the aspects of path planning efficiency, path quality, convergence speed, complex environment adaptability and the like.

The utility model discloses a pathological section file cabinet unit and its intensive cabinet belongs to hospital file management technical field, including unit cabinet body and the multiple drawer of movable installation in unit cabinet body, the drawer inside is divided into a plurality of along the width direction setting storage area by partition, including slide box and baffle piece, the slide box is multiple, along the length direction and side by side setting in each storage area, and the same number of carding position of patient pathological section is provided in each slide box, the number of baffle piece is same with the number of storage area and movable installation in each storage area, baffle piece and the inner wall of drawer together hold a plurality of slide boxes in the corresponding storage area, the utility model discloses be convenient for to the pathological section of patient to carry out quick and take, and avoid missing simultaneously, and the section in each slide box is mutually separated, and there is no extrusion pollution phenomenon.

The invention discloses a geometric guidance and task self-adaption multi-thread sphere decoding method and a related device, and belongs to the technical field of wireless communication, and the method comprises the steps: obtaining a channel matrix of a system model, and carrying out the QR decomposition of the channel matrix of the system model, and obtaining a QR decomposition result; constructing a search tree based on a result of the QR decomposition; dynamically updating the search radius and the optimal solution of the search tree, and determining a geometric threshold value; according to the search radius and the optimal solution of the updated search tree and the determined geometric threshold value, searching the search tree through multiple threads according to an SE sequence to obtain a symbol vector of a transmitting antenna in a system model, and completing multi-thread sphere decoding of geometric guidance and task self-adaption. Meanwhile, the search time is shortened, and the search task scheduling and synchronization cost is reduced.

The invention relates to an unmanned high-speed service area robot global path planning method and device and a robot. The method comprises the steps that 1, a path grid map is constructed; step 2, improving the Runyanlong optimization algorithm, including: generating an initial population; random key coding; judging the priority; introducing an affinity function; embedding a concentration adjusting mechanism; carrying out a double-variation strategy; step 3, bidirectional beetle antennae parallel search: taking a starting point and a target point corresponding to the initial path sequence generated after optimization in the step 2 as double search initial points, and synchronously executing the improved Rhouyanlong optimization algorithm; if the two-way search meets at the middle path points, directly butting to form an optimal path sequence; if not, selecting an optimal path sequence through a distance strategy and a time strategy; the distance strategy is to select a sequence with shorter path length, the time strategy is to select a sequence with shorter walking time consumption, and random selection is carried out when the length or time consumption is equal. The problem that the convergence speed is not high enough is solved.

The utility model discloses a kind of snack packaging boxes of multilayer composite structure belong to food packaging technical field, including packaging box body, the surface of packaging box body is fixedly connected with portable rope, the inside of packaging box body is equipped with packaging cavity, the top of packaging box body is inserted and is connected with sealing box cover, the top of sealing box cover is fixedly connected with open-close handle, the bottom of packaging box body is equipped with operating slot;The utility model, by setting operating slot, operating handle, the cooperation structure of outer thread rod and inner thread cylinder, can drive three snack storage frame synchronous rotation lifting, realize the convenient access of different layer snack, solve the inconvenient problem of bottom snack taking, improve taking efficiency, and in the process of lifting taking, the specific position of snack needing to be accessed can be quickly positioned by rotating snack storage frame, it is convenient for user to find target snack accurately, reduce searching time, further enhance the convenience of taking.

The application discloses a complex background infrared image background motion compensation method based on image registration, which comprises the following steps: using a FAST feature point detection algorithm to detect feature points of two adjacent infrared images, and removing redundant feature points by using a quadtree algorithm; generating position descriptors and gray level descriptors, and combining the two with BEBLID descriptors to generate LGB descriptors for feature description of all preprocessed feature points in the two images; dividing each image into four quadrant regions, and calculating hash key values of each feature point; matching feature points in the two images according to the hash key values to obtain matched feature point pairs in the two images; screening the matched feature point pairs by using a random sample consensus algorithm, calculating final background motion parameters, and performing affine transformation on a previous image in the two images according to the final background motion parameters to realize background motion compensation. The application improves the effect of background motion compensation and provides better conditions for subsequent infrared dim and small target detection.

This invention provides a method for processing database query statements and related products, relating to the field of database optimization. The method includes: obtaining the query statement to be processed; searching for the execution state corresponding to the query statement from a pre-established execution state cache record; if found, the database executor directly loads the execution state to process the query statement; if not found, obtaining the execution plan of the query statement, executing the execution plan by the executor, and saving the execution state of the executor to the execution state cache record. The solution of this invention allows the database executor to directly load the execution state to process the query statement, directly reusing the already initialized execution state, avoiding the time-consuming process of repeated initialization by the executor; it shortens the overall processing flow of the query statement, and is particularly suitable for scenarios where the same query is executed repeatedly.

The application discloses a boundary scan test matrix generation method based on heuristic search, which comprises the following steps: firstly, counting the number of networks in the measured circuit board and calculating the normalized distance between any two networks; then, calculating the short-circuit probability between the networks through the normalized distance between any two networks, so as to construct a short-circuit probability matrix between the networks; then, setting a test matrix and generating a plurality of row test matrices according to the test matrix; finally, searching for the test matrix with the minimum cost through the establishment of a search tree based on the test cost and the heuristic function value.

The application relates to a path planning method based on improved bidirectional A* algorithm through opposite node query, which improves the traditional A* algorithm through the mode of bidirectional search and opposite node query, takes the starting point and the ending point as the algorithm origin in the global map, simultaneously carries out bidirectional path search, calculates a global evaluation function to determine the best path. Although the mode of bidirectional search improves the search efficiency, in the search process, the two paths are misaligned and do not intersect in the middle. In view of the situation, when the global evaluation function is the same, the opposite node is taken as the query information to further determine the search node, and a cost function of the current node and the latest node of the opposite search is constructed to ensure that the paths intersect in the middle point. Compared with the traditional A* algorithm, the method provided by the application reduces the number of search nodes and improves the search efficiency.

The application provides a three-dimensional flight path planning method for fire-fighting aircraft based on improved A* algorithm, which firstly carries out initial flight path planning through an improved A* algorithm search strategy, solves the problems of slow search of nodes, more search of useless nodes and frequent turning of the original A* algorithm in a three-dimensional map, then processes redundant points in the initial flight path, carries out further flight path optimization and reduces the flight path length. The application comprehensively considers the terrain factors and the specific conditions of forest fire sites, combines with the performance constraints of the aircraft itself, can provide a safer flight route for the aircraft, greatly reduces the search time through the way of reducing the search points, simultaneously solves the frequent turning defect of the path planned by the original A* algorithm, and effectively shortens the flight path distance. The three-dimensional flight path planning method for fire-fighting aircraft based on improved A* algorithm provides a set of usable solution for the flight path planning problem in the forest fire-fighting task.

This invention discloses a robot relocalization method, apparatus, and robot. In the method, laser point cloud data and image data acquired by the robot at its current position are received; keyframe information corresponding to the image data is determined according to a visual dictionary; physical location information corresponding to the keyframe information is obtained from a visual map; feature point information of the image data is matched with feature point information corresponding to the keyframe information; and calculation is performed by combining the physical location information of the feature points in the visual map and the pixel location information of the feature points in the image data. After obtaining the robot's first pose data, a predetermined area is set based on the first pose data, and iterative matching calculations are performed within the predetermined area using the laser map and laser point cloud data to obtain the robot's second pose data. By using the above scheme, the iteration range of laser matching can be reduced by utilizing the initial pose data, thus accelerating the matching speed and quickly achieving robot relocalization.