100 results about "Intelligent planning" patented technology

A distributed agent community is able to dynamically interact with alternative sofware technologies that manage distributed objects. The leveraging of capabilities of distributed object systems greatly expands the flexibility and capabilites of the distributed agent community. Through access to distributed object systems, the distributed agent community can draw on the capabilites of all the objects managed by the distributed object systems. The access to distributed systems by the distributed agent community allows for collaboration and intelligent planning that the distributed object systems do not themsleves provide.

A wireless remote telemetry system uses low-cost, low-power ad-hoc networks to provide flexible reading and control of remote devices. In an embodiment applicable to a utility service, consumption of electrical power among a population of customers is measured by a utility metering system having ad-hoc network communication capability. The remote metering unit transmits information over an ad-hoc network to one or more intermediate communication units or hops. The intermediate communication units or hops include a mobile unit, a mobile base unit, a subscriber home computer, and a home base unit. Each of these hops may co-exist in the same large-scale system. The intermediate communication units transfer the received information to a central controller through multi-hop ad-hoc networks or cellular networks, according to intelligent planning by the wireless infrastructure or the central unit.

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 relates to a planning method of a multi-system intelligent configurable wireless network. The planning method comprises the following steps of: determining systems and requirements of wireless network planning by users, and configuring network planning parameters according to the systems and requirements; respectively carrying out rough network planning and fine network planning; and finishing planning results, and providing output data and charts for planning as a total result of the current network intelligent planning for providing reality basis and reference for users. The planning method disclosed by the invention is used for carrying out rough network planning and fine network planning on a set region by combining with an actual geographic information system on the basis of current situation of coexistence of multiple networks and supports single-network and multi-network simulation. Multiplex network systems supported by the method disclosed by the invention not only comprise a 2G (2-generation) network, a 3G (3-generation) network, a 3G (HSPA (High Speed Packet Access), EV-DO (Evolution-Data Optimized)) and 4G (TD-LTE (Time Division-Long Term Evolution), FDD-LTE (Frequency Division Duplexing-Long Term Evolution)), supports planning of multiple clustering systems (TETRA (Terrestrial Trunked Radio), iDEN (Integrated Digital Enhanced Network), GoTa (Global open Trunking Architecture) and GT800) and has complete and perfect functions.

The invention provides a method and system for intelligent planning of a tour route. The method comprises the steps of obtaining online request information of a user, logging in a tourism resource platform in which tourism attraction information and related information of the user are stored; obtaining at least one tourist attraction selected by the user and a starting and ending time of a trip through the tourism resource platform; obtaining tour way information of the user; obtaining at least one tour planning route according to the tour way information of the user and by combining the at least one tourist attraction selected by the user and the starting and ending time of the trip; and selecting a tour planning route from the at least one tour planning route, generating a tour planning text, and realizing the intelligent planning of the tour route. According to the self-demand information provided by the user, including the tour way and the tourist attraction information, the method and system of the invention intelligently plan the tour route by combining specific information of each tourist attraction, the user can select a suitable tour route, and the user experience is further improved.

An intelligent control method for vertical recovery of carrier rockets based on deep reinforcement learning is disclosed. A method of autonomous intelligent control for carrier rockets is studied. Theinvention mainly studies how to realize attitude control and path planning for vertical recovery of carrier rockets by using intelligent control. For the aerospace industry, the autonomous intellectualization of spacecrafts is undoubtedly of great significance whether in the saving of labor cost or in the reduction of human errors. A carrier rocket vertical recovery simulation model is established, and a corresponding Markov decision-making process, including a state space, an action space, a state transition equation and a return function, is established. The mapping relationship between environment and agent behavior is fitted by using a neural network, and the neural network is trained so that a carrier rocket can be recovered autonomously and controllably by using the trained neural network. The project not only can provide technical support for the spacecraft orbit intelligent planning technology, but also can provide a simulation and verification platform for attack-defense confrontation between spacecrafts based on deep reinforcement learning.

The invention relates to a power distribution network intelligent planning system based on automatic optimization, and belongs to the technical field of power distribution and utilization engineering electricity network planning design. The power distribution network intelligent planning system comprises an original data collecting module, a load prediction module, a transformer substation planning module, a network frame planning module, a reactive power planning module, an alternative planning scheme module, a technical economy evaluation module and a decision making module. The input of the system is bottom layer data and planning parameters, the output of the system is the optimum planning scheme, the information input and output of each module and the combination among all modules, finally, the intelligent planning function of a power distribution network is realized, and the artificialization degree in the power distribution network planning process can be reduced to the minimum.

The invention discloses an unmanned aerial vehicle power transmission line patrol flight path planning method and system. The method includes the steps: acquiring image terrain data, pole and tower data and unmanned aerial vehicle and unmanned aerial vehicle carried load data of a power transmission line to be operated; making an operation plan according to the image terrain data, the pole and tower data and the unmanned aerial vehicle and unmanned aerial vehicle carried load data; making a flight path according to the operation plan; detecting the flight path to obtain detection results; editing and correcting unqualified flight path points in the detection results; simulating flight according to the edited flight path to obtain a simulated flight path; deriving the simulated flight path.Unmanned aerial vehicle line patrol task setting and flight path planning are simpler and rapider, line patrol efficiency is greatly improved, and the unmanned aerial vehicle power transmission linepatrol task and flight path intelligent planning system takes environmental factors of the power transmission line and performance requirements of an unmanned aerial vehicle and a load into full consideration, so that the planned flight path not only meets safety performance requirements, but also meets the performance requirements of the unmanned aerial vehicle and the load.

The invention provides an electronic commerce logistics system which comprises an order management module, a goods management module and a distribution management module, wherein the order management module is used for receiving client orders and determining goods content and distribution content; the goods management module generates shipping orders according to the goods content determined by the order management module, manages warehouse goods and determines stock; and the distribution management module generates shipping orders according to the distribution content determined by the order management module and delivers packed goods to consignees in specified places of receipt. According to the system, the optimization and intelligentization of management and decision are realized with intelligent planning theory and method, finite resources are reasonably utilized, the maximum benefit is achieved with lowest consumption, very good application to various aspects of vehicle stowage, transport route optimization, storage optimization and the like can be realized, and economic cost is reduced.

The invention discloses a logistics path intelligent planning method and system. The method comprises the steps of acquiring current waybill information; Determining a plurality of feasible transportation paths according to the goods taking address and the destination address; Calculating the total time consumption of each feasible transportation path, and screening out effective transportation paths of which the total time consumption is within a preset aging range; Calculating the total cost of each effective transportation path; And selecting the effective transportation path with the lowest total cost as a target transportation path. According to the method, the target path meeting the specified time efficiency is automatically planned according to the waybill information, the labor cost consumption is reduced, the transportation cost of each effective transportation path is calculated, and the effective transportation path corresponding to the lowest transportation cost is selected as the target transportation path, so that the time efficiency is ensured, and meanwhile, the transportation cost is saved.

The invention discloses an intelligent planning method for a three-dimensional global flight path of an unmanned aerial vehicle in an enemy threat uncertainty environment. The intelligent planning method comprises the steps: firstly building a three-dimensional environment model of an unmanned aerial vehicle according to a priori map; determining three objective functions for evaluating the advantages and disadvantages of the flight path, and establishing a three-objective optimization model of three-dimensional global flight path planning of the unmanned aerial vehicle in an enemy threat uncertain environment; secondly, performing particle swarm intelligent planning on the global path of the unmanned aerial vehicle by adopting an improved multi-target backbone particle swarm optimizationalgorithm; and finally, smoothing all paths in the obtained optimal path set by adopting a linear interpolation method, and displaying a plurality of solved feasible paths on a simulation map, so thata decision maker can select a final path according to actual conditions. The path selected by the intelligent planning method not only can avoid obstacles, but also can avoid threats of enemies, andthe length of the path is short, and a decision maker can select and obtain the optimal path according to actual requirements.

The invention discloses a method and a system for intelligent planning the path of a multi-working condition wall climbing robot. The optimal path of the wall climbing robot is found by an ant colonyalgorithm in an environment with known barriers. An environmental model is preprocessed, a pheromone limiting strategy, a goal orientation strategy and a reward and punishment excitation strategy areintegrated into the ant colony algorithm, and the improved algorithm has good convergence speed and optimization ability; a speed control strategy and a smallest turning frequency-based safety strategy are respectively provided according to the different working requirements of the wall climbing robot on a horizontal plane and a vertical wall, and are fused with the improved ant colony algorithm to form the method for planning the path of the wall-climbing robot under multiple working conditions; and the system for planning the path of the wall climbing robot is designed based on C++. The method and the system for planning the path realize the planning of the path of the wall climbing robot under different working conditions on the basis of the improved ant colony algorithm, and have theoretical values and practical significance.

The invention belongs to the field of intelligent transport study and relates to an adaptive intersection signal control method considering supply side constraint. The problem that consideration on intersection exit ramp transportation supplies is absent in the existing signal control system and study is solved. The method comprises the following steps: 1, detecting and processing intersection traffic information, and acquiring traffic demands of an intersection entrance ramp and traffic supplies of the exit ramp; 2, establishing a time-varying relationship of intersection traffic supplies, and constructing an intersection supply-demand matrix; 3, establishing an intersection signal timing dial optimization model for quintuple descriptions on problem description, initial state, target state, action set and knowledge rule based on intelligent planning; and 4, searching the target state by adopting a decision-making tree method, and generating a corresponding timing plan. Compared with the prior art, the method disclosed by the invention has the advantages that active control of intersections is realized, the intersection downstream exit ramp queue overflow can be avoided, and intersection 'deadlock' is avoided.

The present invention discloses a method for path intelligent planning of a robot cleaner. The method mainly comprises automatic positioning, path planning and road finding when encountering obstructions. The robot cleaner performs positioning through the triangle and centroid algorithm, performs bow-shaped cleaning along the longest edge of a room, performs automatic road finding along the edges when obstructions are encountered and performs traversal cleaning. The method for path intelligent planning of the robot cleaner plans the cleaning path of the robot cleaner as much as possible so as to improve the work efficiency and allow the home cleaning to become simpler and more efficient.

The invention discloses an industrial robot control system. The industrial robot control system comprises a robot and a controller, wherein the robot and the controller are separated from each other; the robot comprises a main control module, a communication module and an execution module; the controller comprises an input unit, a transmission unit, a fault detection unit, a display unit, a storage unit, a main control unit and an intelligent planning unit. According to the industrial robot control system provided by the invention, a control mode is flexible, and the intelligent degree is high; an input mode comprises a key-press input mode, a handwriting input mode and a voice input mode; the fault detection unit can be used for detecting the performance and the state of the robot online, and the operation accuracy and the operation safety of the robot are ensured; the intelligent planning unit is used for applying an artificial intelligence technology to track planning of the robot, the working mode of a traditional industrial robot that the working is inflexible, the operation just can be carried out according to an established procedure, and a response to the change of an environment cannot be carried out can be changed, an optimal track can be autonomously planned, and the service life of the robot can be prolonged.

The invention discloses a device and method for sorting building waste. The outline, position, height and other information of materials are obtained through a laser sensor on the basis of a six-freedom-degree mechanical arm, and then, in the process that the six-freedom-degree mechanical arm is guided to grab materials, a tension sensor on the six-freedom-degree mechanical arm is used for obtaining the grabbed material weight information. Finally, the material density can be roughly estimated by utilizing material weight information and space volume information, and accordingly the material type is judged. A density recognition method is adopted for accurately sorting the building waste, and the sorting error rate is greatly reduced; through intelligent planning of the motion path of thesix-freedom-degree mechanical arm, the coordinates of the materials can be rapidly positioned, the material sorting efficiency is guaranteed as well, accurate material sorting is achieved, the work efficiency is greatly improved, and the human resource is saved.

The invention discloses an electric vehicle charging route planning method, and belongs to the technical field of electric vehicles. A vehicle owner cannot query whether sufficient charging stations suitable for an own vehicle exist between a starting place and a destination in advance before a long-distance journey in the prior art, so that a lot of vehicle owners give up the idea of driving theelectric vehicle across the city and take other types of vehicles, and thus the practicability of the electric vehicle is greatly reduced. The method comprises the following steps of firstly, acquiring basic data; secondly, segmenting the route; thirdly, computing the optimal charging station of the road section; and fourthly, generating a charging route. According to the charging route planning method, a problem that the charging facility information is not symmetric is solved, the real-time condition of the vehicle is combined, and the optimal route after intelligent planning is dynamicallygenerated, so that when the vehicle owner drives the electric vehicle for a long distance, the available charging station can be found before the electric quantity is exhausted at each time until thevehicle owner arrives at the destination successfully.

The invention discloses a dynamic strategy-driven intelligent network resource planning and configuration method, which comprises (1) a strategy management module, (2) a network planning module, (3) asimulation evaluation module, (4) a reconfiguration management module and (5) cognitive computing based autonomous management module, wherein the reconfiguration management module is used for completing automatic configuration of network elements based on a planning scheme and network operation situation information. The invention provides an implementation method of network resource planning andconfiguration based on cognitive computing and dynamic strategy generation, and the planning fulfillment success rate and the automatic configuration level are improved. The method proposes to perform automatic and intelligent planning process management and control on the whole life cycle including demand reception and decomposition, automatic planning and simulation evaluation, dynamic servicedeployment, dynamic bottom resource planning and scheduling and dynamic optimization of the operation process, feeds back the actual operation condition to the planning module, carries out expansion and optimization compared with the traditional network resource planning and configuration, and effectively gives consideration to local adjustment and overall optimization.

The invention relates to a method and a device for distributing surveying and mapping tasks of multiple unmanned aerial vehicles. The method comprises the steps of obtaining the attribute informationof a multi-UAV surveying and mapping system; according to the acquired attribute information of multi-UAV surveying and mapping system, determining the cooperative surveying and mapping task model ofmulti-UAV; establishing a heterogeneous division of labor population corresponding to the set of unmanned aerial vehicles; solving the heterogeneous ant colony system to obtain the optimal path of theheterogeneous ant colony under the current number of iterations; updating the pheromone of heuristic heterogeneous ant colony algorithm and obtaining the task assignment scheme by iterative solution.The invention adopts an intelligent planning method to solve the problem of constructing the surveying and mapping task plan of multiple unmanned aerial vehicles (UAVs), so as to improve the directionality of the searching process. Heterogeneous ant colony technology is used to decompose the solution task into several platforms, and distributed solution is realized by information exchange mechanism, which improves the efficiency of solution. The probability of infeasible solution is reduced; on the basis of the current optimal solution, the local search is carried out in a certain search range to avoid falling into the local optimal solution.

The invention discloses a self-service query statistics analysis method based on natural language processing. The method comprises the steps that a power communication data query statistics analysis rule base, a knowledge base and a corpus are constructed; a multi-dimensional data query statistic analysis model for power communication standardization and programming is established; a query statistics analysis statement or a paragraph is input, a query statistics analysis natural language processing task is formed, and a semantic dependency tree is generated; each element in the semantic dependency tree corresponds to a query statistic analysis model, a structured query statement is generated through matching of the rule base and the knowledge base, and finally a query statistics analysis result set is generated. According to the method, self-defined, fast and flexible data configuration, processing, analysis and management can be supported, automatic and intelligent planning and designof a communication network can be achieved, and the operation and maintenance level is improved.

An intelligent generation method and system of planning scheme based on machine learning are disclosed. A generation model shown in the description is obtained by machine learning training the parameters of the model through the marked planning design scheme. Then, the data z' of the area to be planned is inputted into the generation model shown in the description, and the planning scheme of the area to be planned is obtained by operation. The planning scheme of the area to be planned comprises a design element M of the area and attribute information corresponding to the design element M, which can be rendered and edited by a graphics processing software. The invention can further realize intelligent planning and design on the basis of existing CAD graphics processing software through machine learning. Moreover, combined with the comprehensive evaluation of the planning and design scheme, the invention can further optimize the model obtained by training in the use process, and furtherimprove the quality of the 'batch' fully automatic planning and design scheme. The invention retains a data interface for a designer to operate, and the designer can directly modify the planning and design scheme through the interface, so that the efficiency is higher.

The invention discloses a method and an apparatus for route planning. The method includes the steps of: acquiring a pixel coordinate set corresponding to a user-provided route trace in a terminal screen coordinate system; according to the pixel coordinate set and a mapping relationship between the pixel coordinate and longitude and latitude coordinates, determining a longitude and latitude coordinate set that is corresponding to the route trace in a geographic coordinate system; according to the longitude and latitude coordinate set, determining a target planning route that is corresponding to the route trace. The method can achieve intelligent planning of a travel route on the basis of the user-provided route trace and solve a problem of inconsistence between route planning and a user expect route. Compared with a route planning method in the prior art, the method improves accuracy of route planning and improves the interaction manner between the user and an electronic navigation map. The method and the apparatus are easier to achieve interaction of custom information between the user and the electronic navigation map application.

The invention discloses an intelligent control and operation system for a tower crane. The intelligent control and operation system for the tower crane comprises an intelligent planning subsystem anda real-time running parameter measuring subsystem, a handheld positioning and controlling terminal, a field operation managing subsystem and a movement control subsystem which are in communication connection with the intelligent planning subsystem. The intelligent control and operation system for the tower crane has the beneficial effects that the running mode of the tower crane is changed to computer process control from manual control, an operator only needs to input an operating instruction through the handheld positioning and controlling terminal, and the background intelligent planning subsystem automatically calculates and plans the safe running sequence and routes of all movement parts of the tower crane according to collected construction site information and tower crane information and the operating instruction of the operator. Compared with a traditional manual operation and remote controller control mode, the intelligent control and operation system for the tower crane has the advantages that a tower crane driver is liberated from a dangerous working environment, the operation process is simple and efficient, and the safety and production efficiency of tower crane operation are greatly improved.

The invention relates to a warehouse goods and material storage path intelligent planning method, a storage medium and electronic equipment. The method comprises the steps that historical disaster data, historical material delivery information and existing material information are acquired; the storage order of existing materials is set according to the historical disaster data, the historical material delivery information and the existing material information; a warehouse is divided into N storage areas according to preset units; a delivery position serves as a center, and the distance between each storage area and the delivery position is obtained; and according to the storage order of the existing materials and the distance between each storage area and the delivery position, a storagearea of each existing material is set. Through the warehouse goods and material storage path intelligent planning method, the storage medium and the electronic equipment, automatic planning of storagepositions of the materials is realized, a large amount of manpower is saved, and meanwhile planning efficiency is improved; and meanwhile setting of an optimal delivery position for the materials inthe warehouse is realized.

The invention discloses an interactive travel itinerary planning method based on artificial intelligence, and the method comprises the steps: firstly, receiving basic itinerary information input by auser, and enabling the basic itinerary information to comprise but not limited to a departure place, a destination list, departure time, planning days, budget, and personnel composition information; Identifying a travel destination mode according to the travel basic information, wherein the travel destination mode comprises a default local mode, a single destination mode or a multi-destination mode; Making a travel itinerary scheme by combining the itinerary basic information and the user knowledge information; And providing the formulated travel itinerary scheme for a user in a real-time combination interaction or result selection interaction manner. According to the method, the accurate personalized travel route customization service can be provided, and the problem of intelligent planning of the travel route of the free tourist is solved, so that the user is helped to formulate an appropriate travel plan quickly and accurately.

The present invention discloses a flexible cable path intelligent planning method considering gravity constraint rules. The method comprises the following steps: carrying out modeling on the three-dimensional environment of the wiring space, and using the partitioned space division method to carry out partition division on the overall space of the product so as to obtain a to-be-wired space area that needs to be wired and a non-wiring space area; carrying out grid processing on the divided to-be-wired space area, establishing an obstacle bounding box model, and establishing a wiring space grid model and an abstract model of the wiring path point; and finally, carrying out intelligent search and optimization on the flexible cable path by using the ant colony optimization algorithm and by considering the gravity constraint rules. According to the method disclosed by the present invention, automatic obstacle avoidance can be realized, the wiring route satisfying certain engineering rules is generated, and the wiring efficiency of the flexible cable and the final overall performance and reliability of the product are improved.

The invention provides an intelligent planning method for an electric automobile charging station, and the method employs an artificial bee colony algorithm for solving a multi-target model, and effectively irons out the defects that a multi-target model is poor in solving and calculation precision, is complex in operation, is large in number of control parameters, and is poor in robustness. The solving method has no requirements for a target function and constraints, hardly employs external information in a search process, just takes a fitness function as an evolving basis, and forms the artificial intelligent technology which takes generation + verification as the features. A solving result is a comprehensive optimal charging strategy, and provides a charging guide with the good experience and high participation degree for a power grid company and an electric automobile charging user.

The invention relates to an ODN network intelligent planning method, device and system. The method comprises steps that an OBD layout impact factor set of the to-be-planned area is acquired; the OBD layout impact factor set comprises a historical OBD layout sample data set and a business sample data set; the historical OBD layout sample data set is processed through a neural network model to acquire present OBD layout training parameters and present OBD layout classification result data corresponding to the present OBD layout training parameters; the business sample data set is processed through similarity clustering to acquire OBD layout clustering result data; the OBD layout clustering result data is processed through nearest neighbor classification to acquire OBD layout classification result data after optimization; the present OBD layout classification result data is compared with the OBD layout classification result data after optimization, and present OBD layout optimization datais generated according to the comparison result. The method is advantaged in that OBD layout of the ODN network in the to-be-planned area can be optimized, and OBD layout accuracy and efficiency areimproved.