78 results about "Voronoi graph" patented technology

The invention provides an unmanned aircraft route planning method based on combination of Voronoi diagram and ant group optimizing algorithm. Firstly a model is established in accordance with properties of various threaten sources, e. g. landform, radar, missile and anticraft gun, and the unmanned aircraft route cost includes threaten costs and fuel oil costs; then initial pheromone values are given to each edge of the Voronoi diagram, enabling an ant to begin the search from the Voronoi node nearest to the start point. The marching Voronoi edge is selected based ob the status shift rule, then the search at the Voronoi node nearest to the target point is finished; And when all the ants have finished their own candidate route selection, the pheromones at each edge of the Voronoi diagram are updated in accordance with the improving and updating rules, wherein the pheromones at edges with no ant passing by are evaporated, and the process is repeated until an optimal unmanned aircraft route is found out. The method is characterized by good real-time and high-speed performance, and the found route is closer to the actual optimal unmanned aircraft route.

The invention discloses a collaborative flight path intelligent planning method for formation flying of unmanned planes under a dynamic environment. The method comprises the steps of offline intelligent planning of a formation pre-flying collaborative flight path of the unmanned planes, online replanning of the flight path for avoiding threats, collaborative rebuilding of a formation team and the like. The offline intelligent planning of the formation pre-flying collaborative flight path of the unmanned planes adopts an intelligent planning method based on a Voronoi graph and an ant colony algorithm, and an integrated optimal pre-flying flight path with collaborative time can be planned off line for the unmanned plane. The replanning of the online flight path adopts an intelligent flight path planning method based on an RRT (Rail Rapid Transit) algorithm, and quick flight path correction can be provided when the unmanned plane formation meets a sudden threat. The collaborative rebuilding of the formation team adopts a method combining unmanned plane formation member flying speed adjustment and coiling maneuvering. According to the method, pre-flying collaborative flight path offline planning and generation of online replanned flight path are provided for the unmanned plane formation, a collaborative rebuilding scheme is provided, and the online rebuilding problem of unmanned plane formation flying cooperativity is solved.

The invention provides a method for planning a path in an urban road traffic network. The method comprises the steps of dividing a region to be searched, which is determined according to a start point and a final point, into multiple sub regions according to a given road network density; then mapping the multiple sub regions into one-dimensional discrete points, and forming a Voronoi graph based on the discrete points; determining an adjacency relation between every two of all the sub regions according to the Voronoi graph, and judging the connectivity between every two adjacent sub regions; constructing a new road network according to a set of the selected adjacent sub regions which are communicated, and searching an optimal path between the start point and the final point in the new constructed road network. According to the method, the construction time of a road network topological structure is shortened; furthermore, the search range of the path is narrowed, the search time is shortened and the search efficiency is improved.

The invention belongs to the technical field of a spatial database and in particular relates to a method for querying a road network k aggregation nearest neighboring node (k-ANN) based on a Voronoi graph. The method comprises the following steps of: resolving a first nearest neighboring node (1-NN) of each query point through an R tree index; constructing a priority queue to store the 1-NN of all query points, wherein the weight is the current aggregation distance from each query point to a target node; extending a certain query point according to a certain sequence on the basis of a road network Voronoi graph, updating the aggregation distance of the next NN of the query point, inserting or updating and performing other kinds of operation on the priority queue until the target node at the head of the queue is extended by all the query points, then the target node is a first aggregation nearest neighboring node (1-ANN); and after the 1-ANN is deleted from the queue, acquiring a second aggregation nearest neighboring node (2-ANN) which accords with the conditions for the second time, and acquiring the k-ANN according to the characteristics. The method has excellent performance in the aspect of response time and page views of user query.

The invention relates to the field of wireless mobile communication, in particular to a quick automatic neighbor planning method for related networks. The method is characterized by comprising the following steps of: generating a weighted V graph according to network topology parameters by a network topology parameter acquisition system, a weighted Voronoi graph generating subsystem, a geomorphic feature processing system, a candidate neighbor generating system and a neighbor priority evaluation system; and determining polygons covered by each cell according to the generated weighted V graph, determining a first network neighbor list according to the adjacent relationship of a service sector and V graph polygons covered by other cells, generating a candidate neighbor list, and finally outputting a neighbor list according to the weight values of each neighbor. The method is suitable for systems of wideband code division multiple access (WCDMA), code division multiple access 2000 (CDMA 2000), time division-synchronization code division multiple access (TD-SCDMA) and global system for mobile communications (GSM) and 3G-to-2G labeled neighbor planning; and the weighted Voronoi graph data are adopted as a data source, and influences of geomorphic features and buildings on neighbor planning are consulted, so the method has the advantages of high running speed, high planning efficiency and precision and low cost.

The invention provides a user position privacy protection method under the road network environment and a system thereof, and relates to mobile terminal position safety. According to method, position privacy and inquiring privacy of a mobile communication terminal are considered, road segment diversity is considered in the aspect of position privacy, and sensitive inquiring privacy is protected by setting the upper limit value of probability of sensitive inquiring. Voronoi graph partition is performed on a road network according to node dimension and the minimal road segment requirement of an anonymity set is formed. Average information entropy and probability of sensitive inquiring are calculated, and road segments are continuously added in an anonymous box if the requirement of average information entropy and probability of sensitive inquiring is not met. According to the method, two levels of security can be greatly protected for users, which is quite close to the real user privacy protection requirement. The user position privacy protection method under the road network environment and the system thereof can be applied to a mobile terminal privacy protection system under the road network environment.

The invention discloses a charging station layout programming method based on a V-graph and an HS algorithm. The method comprises the steps of firstly, estimating the range of charging stations which are constructed in a programming area through anticipation of charging queuing waiting time; secondly, comprehensively considering multiple factors such as a charging requirement and a region characteristic, establishing a charging station layout programming object according to a charging station construction/operation cost, a charging on-the-way time consumption cost and an arrival-at-station queuing waiting time cost; and finally, randomly generating station address coordinates of the charging stations in the programming area, coding the station address coordinate for obtaining one-directional vectors, defining the service range of each charging station by means of a Voronoi-graph (the V-graph in short) and generating an initial harmony vector, calculating a solution by means of a harmony search (HS) algorithm and storing the solution in a harmony memory (HM), updating the harmony memory through studying the harmony memory and tone fine turning until a number of updating times of the harmony memory is reached, finding out a charging station layout programming objective value and determining an optimal charging station layout programming solution. The charging station layout programming method has advantages of effective integration of multiple factors and high calculating speed. Furthermore the charging station layout programming method can be used for finding out an optimal value.

The invention discloses a multi-strategy route planning method of a mobile robot based on a semantic map. Techniques such as a generalized Voronoi graph (GVG), conditional random field (CRF) inference and a morphological open and close operation are integrated in the method, noise elimination and semantic entitlement and the like on a map built by a common simultaneous localization and mapping (SLAM) algorithm are achieved, finally different route planning algorithms which are suitable for corresponding area features are applied to areas with different semantic meanings in the semantic map, and mixed use of the multi-strategy route planning algorithms is achieved. Based on semantic map planning navigation, not only is the superiority of a route used by a robot improved at the algorithm level, so that the capacity of the robot for selecting a route is inclined toward human intelligence more, but the multi-strategy route planning method lays a technical foundation for a good man-machine interaction of future robots.

The invention discloses a DG-included power distribution network planning method based on a Voronoi graph. A DG-included power distribution network chance constraint planning model is built according to the power grid operation condition, wherein the model includes components such as investment and operation cost, and planning is constrained in a flexible constraint mode. For the load point distribution issue, a greedy algorithm based on the Voronoi graph is put forward and approaches the optimal value by seeking the local minimum value in every iteration. The DG-included power distribution network planning method adopts a genetic algorithm, codes the position of a transformer substation before optimization and testifies the meeting condition of chance constraint in every optimizing process.

The invention discloses a wireless sensor network positioning algorithm based on an APIT test. The coordinates of virtual anchor nodes are calculated through building a Voronoi graph; sequence ranks are built for overlapped areas; the possible unknown node existing areas are reduced; and finally determined area centroids are taken as estimated coordinates of the nodes. The specific steps comprise: building the Voronoi graph related to the anchor nodes; carrying out the approximation of the perfect PIT test; reducing generation probabilities of Out-To-In and In-To-Out; screening reasonable triangles; determining the overlapped areas through a grid scanning method; carrying out space division to the areas; building the sequence ranks; calculating the similarities of the sequence rank of each subarea and the sequence ranks of the unknown nodes; and taking the subarea centroids with the highest integrating degrees as the estimated coordinates of the unknown nodes. According to the algorithm of the invention, the relatively high positioning coverage, the relatively less positioning error and the relatively stable positioning result are obtained on the premise of increasing no hardware cost and communication cost.

The invention discloses a Voronoi graph and road network-based traffic cell automatic division method, which comprises the following steps of extracting all roads, and creating a geographic buffer area; deleting the repeated road nodes, and pre-creating a Voronoi graph; creating the Voronoi graph, and forming the initial traffic cells; merging the cells according to a greenbelt system; giving a minimum area threshold value, and counting the cells of which the areas are smaller than the minimum area threshold value; merging the cells with the areas smaller than the threshold value, and enablingall the cells to be larger than the area threshold value; cutting the cells by using an administrative region; S8, cutting the cells according to the buffer area, and re-counting the cells with the areas smaller than the threshold value, repeating the step S6, and continuing to merge the cells; and S10, checking the cells to ensure that all the traffic cells at least comprise one road node. According to the method, the traffic cells can be automatically divided within the limited time, so that the time and energy for manually dividing the cells by the user are saved, and meanwhile, the errorspossibly caused by the manual operation during the process are also avoided.

The invention discloses an unmanned aerial vehicle path planning method for reconstructing a Voronoi diagram in real time, belonging to the technical field of autonomous navigation of unmanned aerialvehicles. According to the method, path planning is carried out on a plane where an unmanned aerial vehicle is located in real time by taking the current spatial position of the unmanned aerial vehicle as a starting point according to the shape and size of obstacles and the real-time flight height of the unmanned aerial vehicle in a known obstacle environment. According to the method, a two-dimensional Voronoi graph segmentation method is expanded to three dimensions, and the flight path of the unmanned aerial vehicle in the three-dimensional space is planned, so the effectiveness of a plannedpath is improved.

The invention belongs to the technical field of cloud computing and information security, and discloses a safe nearest neighbor method used in cloud computing. The safe nearest neighbor method used in cloud computing includes: using a Voronoi graph to divide a 2-D space; and using two arrays to construct two kinds of safe data structures including a single-homing Bloom filter and a multi-homing bloom filter. To ensure the security of data, the 2-D safe nearest neighbor searching problem is converted into a problem of determining if a point is in a certain range or not, and then a problem of determining if two sets intersects or not is converted. The Voronoi graph based 2-D space division scheme and the two kinds of data structures including the single-homing Bloom filter and a multi-homing bloom filter can ensure performing correct nearest neighbor searching in the condition that a server does not know a data real value and a search real value, the security demand of IND-CPA can be met, and the sub-linear searching time can be reached.

The invention belongs to the field of wireless sensor network and target tracking technology application, and discloses a target tracking method and system for self-adaptive node selection based on aVino diagram, and the method comprises the steps: taking a Voronoi graph as a network model, carrying out the clustering of nodes in the network, and enabling an activated node, a dormant node, and aunique cluster head node to exist in a cluster; Partially activating the sensor nodes in the Voronoi graph area according to a proposed node selection algorithm, and performing extended Kalman filtering for target tracking. By implementing the method, the algorithm can have lower energy consumption and higher tracking precision, the energy consumption of the sensor node can be reduced, and the life cycle of the network can be prolonged; The problem of energy balance is greatly improved, and the number of activated nodes is effectively reduced through setting of a greedy algorithm and a threshold value by nodes in the cluster.

The invention provides a division method and device of user access areas based on weighting Voronoi graphs. The method comprises the steps that performance parameter indexes and load consumption indexes of all servers in all data centers are collected; according to the performance parameter indexes and the load consumption indexes, processing capacity score values of all the servers are calculated; the processing capacity score values of all the servers are converted to be in a preset numerical range, and weighting values of all the servers are obtained; according to the weighting values of all the servers, weighting values of all the data centers are calculated; the weighting values of all the data centers are used as seed points of the weighting Voronoi graphs, and the user access areascorresponding to all the data centers are divided. According to the method, the problem of imbalanced system access pressure of data centers in the related technology is solved, access division of a user can be more reasonable, the system access pressure of the data centers is balanced, resource waste is avoided, and the technical support is provided for construction of the data centers and disaster recovery systems in the big data time.

The invention provides a virtual reality roaming system and method based on improved redirection walking, and the method comprises the steps: inputting a virtual space plane graph, and employing a skeleton graph generation algorithm based on a Voronoi graph to calculate a feasible skeleton graph of a user in a virtual space in advance; according to the skeleton map in the virtual space, establishing a mapping relation between the user feasible skeleton map in the virtual space and the user feasible skeleton map in the physical space by using a static skeleton map mapping algorithm; tracking the spatial position and direction of the user in the physical space in real time through the input module; and according to the established mapping relationship between the virtual space and the physical space, calculating the corresponding spatial position and direction of the user in the virtual space in real time by using a position inverse mapping algorithm and a curvature gain redirection technology, and generating a corresponding user view image through a rendering module.

The invention provides a configuration method of an area feature annotation based on a double visual center and a device thereof, belonging to the digital mapping technical field. The configuration method comprises the following steps: carrying out grid treatment on planar features by a predetermined grid spacing to obtain a set of points in the area feature; calculating a polygon area value S corresponding to the area feature; optionally selecting two points from the set of the points in the area feature, and respectively calculating an area value of a Voronoi graph corresponding to the two selected points; and calculating the sum of a geometric information entropy of a first point and a geometric information entropy of a second point in the selected two points, and setting coordinates ofthe two selected points corresponding to the sum of the maximum geometric information entropies obtained by calculation into a coordinate of the area feature annotation configured based on the doublevisual center. The method can help realize automatically complete configuration of the area feature annotation without manual intervention.

The invention discloses a rapid base station irradiation range calculation and updating method. The method comprises the following steps of: (1) calculating and updating a Delaunay triangulation network by taking an initial triangle as basis; (2) calculating and updating a grid index and a topological relationship of a Delaunay triangle; (3) calculating and updating a Voronoi graph on the basis ofthe Delaunay triangulation network and the Voronoi graph; (4) calculating and updating a theoretical irradiation range of a base station by combining the Voronoi graph and an irradiation direction ofthe base station; and (5) clipping the theoretical irradiation range of the base station according to a minimum external rectangle which comprises the base station. The method has the beneficial effects that through an algorithm of constructing the grid index and the topological relationship and improving the Voronoi graph, the Voronoi graph calculation and updating efficiency is enhanced, so that the rapid calculation and updating of the theoretical irradiation range of the base station is realized, the way of positioning login users on the base station via the theoretical irradiation rangeof the base station is beneficially supported, and assistance is brought to position the login users on the base station more correctly.

The invention discloses a terminal section partition method based on a graph theory and a genetic algorithm. The method is achieved through a computer system in an auxiliary mode. The system comprises a section design and evaluation subsystem which is used as an achieving platform of the terminal section partition method. According to the method, statistics of control work load values of all key points in a terminal area are acquired, a section partition module with balance control work loads as the target is built, initial section partition is finished through a voronoi graph and the genetic algorithm, secondary section partition is finished through a maklink graph and a dijkstra algorithm; sawtooth-shaped parts of borders of sections are eliminated through a piecewise linear fitting method, and the final section partition is finished. According to the method, working states of control personnel can be directly reflected through the control work loads; because the balance of loads of all sections is achieved through a three-stage partition method, minimum flying time, minimum distance and convex section constrains are satisfied, the commanding difficulty of the control personnel is reduced and the safety of airspace operation is guaranteed.

The invention relates to a modeling method of a full-graded concrete three-dimensional mesoscopic model containing random defects. The modeling method mainly solves the important problems in the current concrete mesoscopic modeling process that (1) complex aggregate convexity judgment and aggregate intersection and overlapping judgment are difficult to avoid by most modeling methods; (2) a modeling method based on a traditional Voronoi technology is difficult to meet the requirement of aggregate grading; (3) random defects are difficult to introduce into the mesoscopic model; and (4) the modeling efficiency needs to be further improved. The method comprises the following steps: performing a random shrinkage process meeting aggregate grading requirements on each convex polyhedron cell element in a three-dimensional Voronoi graph by taking a corresponding nucleation point as a center, and generating a random aggregate model with four-grade distribution; and the random spherical pore defect with the required volume content is rapidly introduced outside the aggregate distribution area, and finally the full-graded concrete mesoscopic model containing the random defect is established. According to the modeling method, random defects are introduced. Meanwhile, the aggregate grading requirement can be accurately met, and the modeling method has the very obvious efficiency advantage.

The invention discloses a barrier construction method for a dynamic underwater environment. The method comprises the following steps: 1, an aggregation node control center is established according toan underwater sensor node deploying and controlling water area; 2, the sink node control center calculates the sink depth of each underwater sensor node according to the two-dimensional coordinates ofthe underwater sensor nodes; 3, the sink node control center executes the sinking depth of the underwater sensor nodes and performs information interaction with the underwater sensor nodes in the adjacent water area to establish a neighbor node list of each underwater sensor in the deploy and control water area; 4, whether the underwater sensor node with the maximum weight in the neighbor node list of the underwater sensor is a redundant node or not is judged by using the voronoi graph, and if the condition is met, deleting the node from the neighbor node list of the underwater sensor; according to the method, the coverage rate of the underwater wireless sensor network in the dynamic water area is improved, and energy consumption in the anchor node deployment process is reduced and balanced.