815 results about "Dynamic planning" patented technology

The invention relates to a mobile robot path planning method used in an intensive storage zone. The mobile robot path planning method is technically characterized by comprising the following steps: step 1, an initialized net type path diagram is set up by a scheduling layer server; step 2, a cargo storage task is divided into an empty trunk cargo searching subtask and a loading delivering subtask by the scheduling layer server; step 3, a dynamic planning path of the mobile robot is established by the scheduling layer server and a dynamic planning path of the mobile robot is sent to the mobile server; step 4: the mobile robot executes the corresponding subtask; step 5: the mobile robot sends a state report of the mobile robot to the scheduling layer server; and step 6, the scheduling layer server updates the current position, the load state, and a weight related to an original starting point and a target point of the mobile robot. By dividing every task into the empty trunk cargo searching subtask and the loading delivering subtask, according to the planning paths of different subtasks, the complexity of a safety collision prevention operation of a plurality of mobile robots is reduced, and the instantaneity and the effectiveness of the system are improved.

The invention relates to a microgrid multi-energy joint optimal scheduling method. The method includes: step 1, on the basis of force application conditions of energy supply equipment and operating states of energy storage equipment in different scenes, constructing a physical model of a multi-energy system; step 2, establishing unit mathematical models, including a wind power generator model, a photovoltaic power generation model, a micro-gas turbine model, a fuel cell model and an energy storage model, of the microgrid multi-energy system; step 3, in order to realize lowest comprehensive cost in system operation, constructing a microgrid multi-energy optimal scheduling model by taking DG operation constraints, system safety constraints and multi-energy coupling characteristics into comprehensive consideration; step 4, on the basis of reversed order dynamic planning, solving the microgrid multi-energy optimal scheduling model to obtain a microgrid multi-energy joint optimal operatingstrategy. By the microgrid multi-energy joint optimal scheduling method, operating demands in different scenes can be met, electricity-thermal coordinated optimal scheduling schemes are provided for operating of a comprehensive energy microgrid in different scenes, and high integral operating efficiency and high economic benefits are realized.

The invention discloses a method for controlling hybrid power urban buses. The method comprises the steps of off-line optimizing and on-line controlling. The idea of control strategy switching is put forward, driving reference working conditions targeting regions and more conforming to actual bus driving routes are established, off-line overall optimizing is carried out based on the working conditions, the optimum control effect can be achieved, and the problem that the dynamic planning cannot be applied to on-line and real-time control because the calculated quantity of the dynamic planning is large is solved. When the hybrid buses are driven actually, whether the similarities between the actual driving working conditions and the established driving reference working conditions and between the road prediction working conditions and the established driving reference working conditions are judged on line, if yes, real-time torque distribution is carried out on the hybrid power urban buses by calling dynamic planning optimum control parameters stored in a bus main controller, or otherwise, control strategies are switched, on-line and real-time control is carried out on the buses by adopting the fuzzy logic rule control strategy which is high in self-adaptability and realizability, and accordingly the control strategy adaptation is improved.

The invention relates to a plug-in hybrid electric vehicle energy optimization management method realizing real-time working condition adaption. The plug-in hybrid electric vehicle energy optimization management method includes the steps of (1), acquiring real-time working condition information of each section of each path; (2), setting the optimization target of minimizing accumulated equivalent fuel consumption of each section of each path, building the plug-in hybrid electric vehicle energy optimization management strategy based on the dynamic planning by taking the speed limit of each section of each path, the traffic flow velocity and the limit of power battery working current; (3), acquiring corresponding target economical speed of each section of each path and sending the same to a vehicular controller; (4), by the vehicular controller, acquiring demanded torque sequence of each moment within a predicted time scale; (5), taking the minimum accumulated equivalent fuel consumption within the predicted time scale as the target, and tracking the target economic speed in real time. Compared with the prior art, the method has the advantages of combining the global optimum and the real-time optimum of the plug-in hybrid electric vehicle energy consumption according to the real-time working condition information, and the like.

The invention relates to a map matching method of floating car data. An optimal matching path is guaranteed and an alternative path set of each global positioning system (GPS) point is minimized at the same time by means of multistandard dynamic planning technology, and therefore the matching efficiency is improved. In addition, aiming at the characteristics of map matching, a traditional shortest path analytical method is improved, and the matching speed is further improved by reducing a mark initialization process and a searching method from multiple points to a single point. Compared with other current methods, the map matching method of the floating car data is better in matching accuracy and matching performance, can achieve real-time map matching processing of low sample frequency floating car data in a city traffic network, and has business popularization and application prospects.

The invention discloses a method for recognizing a gesture based on an acceleration sensor. The method for recognizing the gesture based on the acceleration sensor comprises the steps that firstly, signals of the three-axis acceleration sensor is collected, a smooth denoising filter is designed and used for preprocessing the signals, and detection of the boundary of a gesture signal is automatically achieved; with the combination of a non-gesture filtering strategy, non-gesture data are filtered out before template matching; by the adoption of dynamic planning and a DTW algorithm, matching calculation is conducted on gesture data to be recognized and stored template data, and therefore a template gesture which is the most similar to the gesture to be recognized is found; through the strategies such as curve path limitation conducted by a slope, path area limitation and setting of a distorted threshold value, the template matching calculation amount is reduced, and the recognizing cost is reduced; through the template self-adaption strategy, a sample template base is updated automatically, and the gesture recognizing accuracy is improved. According to the method for recognizing the gesture based on the acceleration sensor, on the premise that energy consumption of a terminal is not obviously increased, better user experience is provided through high recognition efficiency and high recognition accuracy, and freer man-machine interaction is facilitated.

The invention belongs to the field of panoramic stitching and provides a 360-degree stitched-type panoramic camera with a wide view field in a vertical direction. The 360-degree stitched-type panoramic camera comprises a plurality of identical image sensors which are vertically arranged, wherein the models, the number and the relative positions of the sensors are determined according to the demands for the size of a view field in panoramic stitching application. The invention additionally provides a calibrating method and a stitching method based on the panoramic camera. Through calibration, images in all loops are projected on the same plane; then the stitching of panoramic images is completed by adopting a dynamic planning method and a gradient domain fusion method. Since a wider vertical view angle can be obtained under the situation of the arrangement of a single row of sensors and an image stitching algorithm is only required to be operated horizontally, the design of the stitching algorithm can be simplified and the algorithm complexity is reduced. Since the stitching operations of adjacent images in a group are mutually independent, multiple processors can be adopted for execution, the real-time stitching of loops of videos can be realized on an FPGA (Field Programmable Gate Array) and the market prospect is wide.

The invention discloses an unmanned aerial vehicle cluster cooperative reconnaissance method based on crossover and variation pigeon flock optimization, which comprises the implementation steps of: S1: initialization of a reconnaissance environment; S2: initialization of a multi-dimensional vector diagram and strategy updating; S3: method design based on crossover and variation pigeon flock optimization; S4: receding horizon control based on crossover and variation pigeon flock optimization; and S5: construction of a target function of crossover and variation pigeon flock optimization. Simulation of unmanned aerial vehicle cluster cooperative reconnaissance is carried out in a three-dimensional space. The main advantages of the method are mainly shown in two aspects that: in one aspect, the method is short in used time, can be used for dynamic planning, and compared to common methods, such as a Vorono graph, a game theory and the like, is high in convergence rate; and in the other aspect, reconnaissance efficiency is high, and in a case that a coverage region is not large, a target point can still be effectively reconnoitered.

The invention discloses a real-time identification method for on-line handwriting sentences. The method comprises that: an input starting module starts stroke input; a stroke acquisition module records a stroke track of a pen point moving on an input plane; a real-time identification module performs real-time identification on the stroke track after a pen is lifted; a pen lifting time judgment module calculates whether the pen lifting time is long enough; a started character string identification module calculates the fraction of each segmentation identification path in a candidate segmentation identification grid according to a path evaluation criteria, and searches the path with optimal fraction by using a dynamic planning algorithm to obtain a character string identification result; an editing modification module performs editing modification on the character string identification result, and performs editing modification on error character segmentation and character identification parts through the operation of a user; and a language association module provides subsequent characters or words for the user to select through language association according to the last character type based on the character string identification and the editing modification so as to improve the sentence input speed.

A tool for static or dynamic planning of a WDM network with dedicated protection. The WDM network is represented by a layered graph having image nodes for each node of the network and horizontal arcs for each link of the network, so as to replicate in each layer the topology of the network. A Bhandari algorithm is adapted for finding on the layered graph a working-spare pair of lightpaths for each connection request to be allocated.

The invention relates to a planning method for processing the length of a safe and shortest knife by adopting five-axle numerical control, analyzing component manufacturability and programming a smooth cutter path. Firstly, a maximum value of the cutter length is set within the range allowed in the technology; disc of the cylindrical surface for the knife rotation at the positions of knifepoint and a barrier are gridded, and through the depth testing of video card and the function of blocking and querying, the reachable information and safe shortest length of the knife in a reference direction can be obtained, and the reachable direction cone of the knife is programmed; then according to the restriction to direction continuity and processing environment, the feasible direction cone is calculated and the manufacturability is judged. If the programmed knife is manufacturable, the length of safe and shortest knife of a knifepoint sequence is programmed in the feasible direction cone in a dynamic planning method, and then a smooth knife path is programmed. The method of the invention has high efficiency, simply realized programming, can be applied to 3 plus 2 axle numerical control processing of complex components or knife choosing and path planning of five-axle linkage numerical control processing.

The invention discloses a multi-satellite cooperative observation business scheduling method and relates to satellite observation business planning and scheduling technology in a satellite operation control field. The multi-satellite cooperative observation business scheduling method is based on a satellite operation control system, builds a star land resource management model, a satellite orbit calculation model and a satellite access information calculation model, adopts a satellite observation business dynamic planning algorithm to regulate satellite observation business rapidly and dynamically, adopts an automatic processing mechanism to make a satellite load control plan and a data receiving plan immediately, adopts a satellite actual load control instruction compilation business trigger mechanism to compile satellite actual load control instructions in real time, and schedules an electronic signal detection satellite and an imaging observation satellite to complete cooperative observation business. The multi-satellite cooperative observation business scheduling method has the advantages of being rapid in response speed, accurate in calculation method, high in automation and the like and is particularly suitable for a marine moving target multi-satellite cooperative observation field.

The present invention relates to an attack and defense differential game-based network security defense decision determination method and a device. The method comprises the steps of constructing a state evolution model NIRM for network nodes according to an SIR model during the network attack and defense process; according to a network node state migration path, acquiring a node state change differential equation set based on the state evolution model NIRM; according to the node state change differential equation set, constructing an attack and defense differential game model ADDG; according to an attack and defense return strategy and a corresponding execution cost, executing a revenue function of the attack party and the defense party during the differential game process; according to the revenue function and the attack and defense differential game model ADDG, solving out a saddle point strategy for the attack party and the defense party through the dynamic planning method, determining an optimal defense strategy and outputting the optimal defense strategy. According to the technical scheme of the invention, the problem that actual requirements cannot be met through the traditional dynamic game analysis method can be solved. Compared with the existing network security defense strategy, the attack and defense process in the continuous and real-time engagement condition is analyzed. The timeliness, the pertinence and the guiding significance of network defense decision results are better.

The invention discloses a multi-unmanned aerial vehicle scheduling and task planning method for earthquake emergency response. The method includes the following three steps of: earthquake disaster area and task area determination; (2) unmanned aerial vehicle department unit ordering and unmanned aerial vehicle formation tracking; and (3) unmanned aerial vehicle formation task planning and dynamic planning. With the multi-unmanned aerial vehicle scheduling and task planning method for earthquake emergency response of the invention adopted, the efficiency of unmanned aerial vehicle scheduling and task planning can be improved, and unmanned aerial vehicle formations can be quickly scheduled to participate in disaster relief.

The invention discloses a multi-objective optimization-based unmanned vehicle motion planning method. A vehicle and an environment are mapped from a Cartesian coordinate system to a Frenet coordinatesystem. A mathematical model for an unmanned vehicle multi-objective path planning problem is established. Path planning is performed by using a linear dynamic planning method. A track is described byusing a piecewise quintic polynomial, and a mathematical model for an unmanned vehicle multi-objective track generation problem is established by using a minimum track slope, minimum curvature, comfortable riding experience, and a closest distance to a path obtained from linear dynamic planning respectively as optimization objectives, using a location of a piecewise quintic polynomial connectionpoint, a first order derivative, a second order derivative, and a third order derivative as equality constraints, and using a road natural boundary constraint and an obstacle boundary constraint as inequality constraints. An optimal solution of the unmanned vehicle multi-objective track generation problem is obtained. The invention solves a problem that a path obtained by using a random point scatter-based path planning method is difficult to meet a vehicle kinematics constraint.

The invention relates to an automobile energy-saving path and economic speed dynamic planning method based on V2I. The automobile energy-saving path and economic speed dynamic planning method comprises the following steps that (1) a starting point and an ending point of a route are arranged, each path is sectioned, and real-time working condition information of sections of each path is obtained; (2) a plug-in hybrid electric vehicle energy consumption optimizing strategy based on dynamic planning is built with the minimum accumulative equivalent oil consumption of the sections of each path as an optimizing target, and with the speed limit and the traffic flow speed of the sections of each path, and the limit value of the working electricity quantity of a power battery as constraint conditions; and (3) the minimum accumulative equivalent oil consumption, the economic speed and the travelling time which correspond to each path are obtained. Compared with the prior art, the automobile energy-saving path and economic speed dynamic planning method has the advantages that according to real-time road network information and the real-time working condition information, and by combining the energy consumption characteristic of a plug-in hybrid electric vehicle, the energy-saving paths and the economic speed are optimally decided; the navigation function is enriched; the configuration advantage of the plug-in hybrid electric vehicle is given to play; and energy consumption is optimal.

The invention belongs to the field of control technologies, and provides an energy control method and device for a hybrid electric vehicle. The method includes the steps that required power Preq(k+j) of a driver in the [k, k+p] time period is predicted, j equals 0, 1, ..., p, and k represents the current sampling time; required torque Treq(k+j) and the vehicle speed v(k+j) of the hybrid electric vehicle in the [k, k+p] time period are obtained; through nerve cell dynamic planning, the optimal control vector [u(k), ..., (k+p-1)] is calculated; and a control variable sequence u(k) of the current sampling time is output. According to the method and device, energy management control of the hybrid electric vehicle is achieved on the basis of random model prediction control and a nerve cell dynamic planning algorithm, and on the premise of guaranteeing the vehicle dynamic quality, the fuel economy of the vehicle can be improved; the calculated quantity is small, the real-time performance is good, and the fuel economy of the hybrid electric vehicle can be further improved.

The invention discloses an unmanned aerial vehicle route dynamic planning method based on A* search, which is used for solving the technical problem that the existing method has poor adaptability for the situation that long-strip shaped polygonal threatening regions or no-fly zones exist in the complex environment. The unmanned aerial vehicle route dynamic planning method comprises the steps of: constructing circumscribed circles of polygonal threatening regions or no-fly zones at first, and judging whether a line segment formed by a starting point and a target point intersects with each polygonal circumscribed circle; further judging whether the line segment and the polygonal threatening regions or no-fly zones have an intersection point or not if the line segment intersects with the polygonal circumscribed circles; and if so, planning and generating a route directly avoiding the polygonal threatening regions or no-fly zones based on an A* search algorithm, wherein a dead zone escaping and two-step optimizing strategies is adopted during the route planning process for planning and generating route points in sequence. The unmanned aerial vehicle route dynamic planning method can adapt to the situation that the long-strip shaped polygonal threatening regions or no-fly zones exist in the complex environment, and can adapt to the situation that the circular or polygonal threatening regions or no-fly zones are overlapped with one another.

The invention discloses a scene text identification method based on a Bayesian probability frame, and relates to vision and mode identification of a computer. The scene text identification method based on the Bayesian probability frame comprises the steps that S1, scene image text is input; S2, character detection and recognition are carried out; S3, a detection-identification candidate grid is built, particularly, a candidate character area, a corresponding character class and a corresponding identification score are stored in the detection-identification candidate grid, each detection-identification route in the detection-identification candidate grid corresponds one text detection and identification result, and a route evaluation function is designed to evaluate each detection-identification route in the candidate grid; S4, the best detection-identification route is searched for from the candidate grid through a dynamic planning algorithm, that is to say, the identification result is obtained; S5, the text identification result is output. The scene text identification method based on the Bayesian probability frame achieves probability modeling and parameter learning of scene text identification integrating detection and identification.

The invention discloses a distributed optimal cooperative fault-tolerant control method based on self-adaptive dynamic planning. The distributed optimal cooperative fault-tolerant control method comprises the steps of: firstly, constructing a communication topology of a multi-agent system by means of communication links among agents, and representing the communication topology by a directed graphG=(V, E, A); secondly, establishing a local domain consistency error equation, and defining a failure-free cooperative control input quantity of the agent vi as ui based on an optimal control theory and a minimum value principle, so as to obtain a distributed optimal cooperative control law; thirdly, executing the distributed optimal cooperative control law; and finally, designing a distributed optimal cooperative fault-tolerant control law of the agents. The distributed optimal cooperative fault-tolerant control method can overcome the shortcomings of the existing nonlinear multi-agent systemfault-tolerant control method, and has a good application prospect in the fault-tolerant control of UAV formation.

The invention discloses an energy control method of a hybrid power vehicle. The method comprises the following steps: (1) observing current system states comprising a vehicle driving speed, driver pedal information, an SOC (State of Charge) of a battery, a rotary speed and a rotary torque and the like of an engine; (2) judging a current EVT (Electronically Controlled Continuously Variable Transmission) mode state according to the vehicle driving speed and the driver pedal information and updating a current system model and system constraint; assuming that the EVT mode state in a predicated time domain keeps unchanged; (3) predicating a future vehicle speed in the predicated time domain to obtain a system observation input amount in the predicated time domain; (4) constructing a predicationcontrol optimization problem in the predicated time domain and carrying out numerical solution online through a dynamic planning algorithm; (5) calculating to obtain an optimal control sequence in the predicated time domain; (6) only adopting a first group of optimal control quantity and acting to the system at a sampling moment; removing the residual control quantity; (7) repeating the process at the next moment until driving is finished.

The invention discloses a BIM-based building scheme project management system. The system comprises a scheme formulation module and a dynamic planning module; an optimal processing module is connectedbetween the ports of the scheme formulation module and the dynamic planning module; the scheme formulation module comprises a BIM project unit and a WBS task node allocation unit; the output of the WBS task node allocation unit is connected with a dynamic project quantity management unit; the dynamic planning module comprises a resource management database; the data read-write end of the resourcemanagement database is connected with a cost implementation tracking unit; the input end of the cost implementation tracking unit is connected with a scheme implementation unit; the optimal processing module includes a risk assessment unit and a stage statistics unit; and the data output end of the stage statistics unit is connected with a project optimization unit. With the BIM-based building scheme project management system of the invention adopted, the full digital processing of large building projects is realized; task scheduling and project cost statistics can be carried out conveniently; and dynamic optimization processing can be carried out according to an implementation condition, so that project optimization can be realized.