22results about How to "Realize the plan" patented technology

The invention relates to an automatic driving vehicle obstacle avoidance method and device based on TransFormer-APF-MPC and a medium, and the method comprises the following steps: obtaining pedestrian motion data and interaction scene data in real time, inputting the pedestrian motion data and the interaction scene data into an automatic driving vehicle obstacle avoidance network based on TransFormer-APF-MPC, and outputting an automatic driving vehicle obstacle avoidance scheme; the automatic driving vehicle obstacle avoidance network based on the TransFormer-APF-MPC comprises a TransFormer model and an APF-MPC obstacle avoidance model, the TransFormer model is used for predicting pedestrian trajectories according to input data, the APF-MPC obstacle avoidance model comprises a path planning layer and a trajectory tracking layer, the path planning layer is used for generating an optimal obstacle avoidance path by improving an artificial potential field method, and the trajectory tracking layer is used for tracking the optimal obstacle avoidance path. According to the improved artificial potential field method, the repulsive force between the vehicle and the obstacle and the gravitational force between the vehicle and the target point are calculated according to the improved repulsive force constant function with the adjustment factor introduced; and the trajectory tracking layer is used for calculating a vehicle control instruction through a model prediction control method, so that the vehicle runs along the optimal obstacle avoidance path. Compared with the prior art, the real-time obstacle avoidance planning and control of the vehicle can be better realized.

The invention discloses a cluster-oriented multi-agent cooperative task planning method, which comprises the steps of constructing a cruise simulation interaction scene, and determining data input to a reinforcement learning network model, the reinforcement learning network model being used for outputting a time sequence of a plurality of sub-tasks, an agent type corresponding to each sub-task and an agent number; converting output data of the reinforcement learning network model into cruise constraint conditions; and performing branch and bound search of an optimal combination scheme according to cruise constraint conditions, planning the action starting time and ending time of each agent, and completing agent sub-task planning. According to the method, a task allocation combination problem and a task execution optimization problem are decoupled, and rapid multi-agent task planning is realized. In the training stage, a task formation is generated, a task allocation decision agent is constructed, and a plan containing the type and number of agents required by each sub-task is generated through a reinforcement learning algorithm; and generating an agent task execution scheme including agent task allocation and execution time in the task.

The invention discloses an unmanned aerial vehicle flight path planning method capable of completely avoiding a no-fly zone, which belongs to the field of unmanned aerial vehicle flight path planning and comprises an application scene of the unmanned aerial vehicle flight path planning method in the no-fly zone, and the application scene of the unmanned aerial vehicle flight path planning method in the no-fly zone comprises a communication scene of an unmanned aerial vehicle and a terminal user in the no-fly zone. According to the invention, the unmanned aerial vehicle can be absolutely prevented from entering any no-fly zone in the flight process; a plurality of straight lines are adopted to approximate the actual flight path of the unmanned aerial vehicle, and the distance from the intersection point of two adjacent straight lines to the center point of the no-fly zone is calculated, so that the flight path of the unmanned aerial vehicle is strictly monitored and planned, and the accuracy of flight path planning and the flight efficiency and task execution effect of the unmanned aerial vehicle are improved; according to the method, the constraint of the adjacent time slots on the continuous trajectory is increased, and the safety and robustness of the system are further improved through approximation of multiple straight lines and accurate intersection calculation.

The embodiment of the invention is suitable for the technical field of energy storage, and provides an energy storage scheme planning method and device, computer equipment and a medium, and the method comprises the steps: determining the power utilization load power in each power utilization time period based on historical power utilization data; according to the equipment information and the power utilization load power of the energy storage equipment, a charging and discharging scheme of the energy storage equipment is determined, the charging and discharging scheme comprises the charging and discharging state and the charging and discharging amount of the energy storage equipment in each power utilization period, and the equipment information comprises the equipment power and the total electric energy capacity; based on the charging and discharging schemes of the energy storage devices, an income curve of the energy storage project is generated, and the income curve is used for representing the corresponding relation between the configuration information of each energy storage device and the income of the energy storage project; and determining target energy storage device configuration information of the energy storage project from the configuration information of the plurality of energy storage devices according to the income curve. Through the method, the energy storage equipment configuration information of the energy storage project can be automatically generated.

The invention discloses a training teaching management analysis system and method based on big data, relates to the field of big data, solves the problem that the training success of a to-be-trained person cannot be effectively evaluated, and comprises a training planning module, a training plan management module, a training evaluation module, a physical fitness assessment module and a comprehensive evaluation module. The training planning module is used for planning the training plan to obtain a final training plan; the training plan management module is used for managing the training plan to obtain the daily completion condition of the training plan corresponding to the to-be-trained person; the training evaluation module is used for evaluating the training condition of the to-be-trained person to obtain a training assessment score value; the physical fitness assessment module is used for assessing the physical fitness condition of the to-be-trained person to obtain a physical fitness score value; the comprehensive evaluation module is used for comprehensively evaluating the training result of the to-be-trained person to obtain the comprehensive training grade of the to-be-trained person, and effective evaluation of the training result of the to-be-trained person is achieved.

This application relates to a preoperative planning method, storage medium, product, and surgical system. The method includes: determining the actual anatomical models of the two lower limbs based on actual image data; determining a target model based on the actual anatomical models of the two lower limbs, wherein the target model is the actual anatomical model of the relatively normal lower limb among the actual anatomical models of the two lower limbs; correcting the force line parameters of the target model to normal if they are abnormal; performing mirror symmetry processing on the target model to obtain standard anatomical models of the two lower limbs; determining the osteotomy surface of at least one lower limb based on the actual anatomical models and the standard anatomical models of the two lower limbs; and determining the prosthesis contour corresponding to at least one lower limb based on the osteotomy surface of at least one lower limb, thereby obtaining the target prosthesis. This achieves preoperative planning, facilitating improved accuracy of subsequent surgery and resulting in better surgical outcomes.

This invention relates to the interdisciplinary field of mechanical engineering and optical inspection, and discloses a method and system for quality sorting of automotive stamping parts combined with optical inspection. The method includes: synchronous imaging by a high-speed linear array camera and a structured light projector via an encoder and photoelectric triggering device; fusing 3D point clouds and 2D images, and using a deep convolutional neural network for defect identification and quality grading; calculating the six-degree-of-freedom pose of the workpiece using an iterative nearest-point algorithm and principal component analysis; calculating the spatiotemporal parameters of sorting based on a predictive instruction generation module, and issuing dynamic control commands to multi-degree-of-freedom pneumatic push rods via a hard real-time communication bus to execute sorting. The system includes a synchronous triggering unit, an imaging unit, a defect identification unit, a pose calculation unit, a predictive instruction generation module, and a dynamic sorting execution unit. This invention achieves millisecond-level accurate identification and adaptive sorting, significantly improving detection accuracy, sorting efficiency, and system robustness.

The invention discloses a method for planning a trajectory of a UAV that completely avoids a no-fly zone, belongs to the field of UAV trajectory planning, and includes application scenarios of the method for planning a trajectory of a UAV in a no-fly zone, wherein the application scenarios of the method for planning a trajectory of a UAV in a no-fly zone include communication scenarios between the UAV and a terminal user in a no-fly zone. The invention supports the UAV to absolutely avoid entering any no-fly zone during flight. Multiple straight lines are used to approximate the actual flight trajectory of the UAV, and the distance between the intersection of two adjacent straight lines and the center point of the no-fly zone is calculated to achieve strict monitoring and planning of the flight path of the UAV, thereby improving the accuracy of trajectory planning as well as the flight efficiency and task execution effect of the UAV. The invention increases the constraints on the continuous trajectory between adjacent time slots, and further improves the safety and robustness of the system through multiple straight line approximation and accurate intersection calculation.

This application discloses a machine tool structure with a combined machining head. The application includes: a first base and a second base, the first base having a working area for placing the workpiece to be processed; a column, on which a first X-axis linear module is mounted; a first group of electrical discharge machining (EDM) heads, comprising at least four heads mounted on the first base and respectively connected to the first X-axis linear module, each of the four heads having an independent Y-axis linear module and a Z-axis linear module; and a second group of EDM heads, comprising at least one head mounted on the first base, the second base having a second X-axis linear module, the at least one head connected to the second X-axis linear module, the at least one head having an independent Y-axis linear module and a Z-axis linear module, and all four heads connected to an EDM power supply.

The invention relates to the technical field of power optimization, and discloses a power distribution network planning and operation joint integrated optimization method. Comprising the steps of constructing a combined power distribution network, collecting comprehensive operation parameters, calculating an operation reliability coefficient, identifying an operation state of the combined power distribution network, comparing the comprehensive operation parameters with corresponding overrun standard values, identifying optimization parameters from the comprehensive operation parameters, and making an optimization instruction according to the optimization parameters. Compared with the prior art, the method has the advantages that the independent power distribution sub-networks can be associated together to construct the planning and operation integrated combined power distribution network, the operation reliability of the combined power distribution network can be accurately evaluated and judged, and meanwhile, corresponding optimization instructions are formulated in a targeted manner according to abnormal phenomena, so that the operation reliability of the combined power distribution network is improved. It is ensured that the running state of the combined power distribution network can be in a safe and stable state, the phenomenon of serious faults of the combined power distribution network is avoided, and then the optimization effect of power distribution network planning and running combination integration is achieved.

The invention provides a dispensing path planning recognition system based on image recognition. The dispensing path planning recognition system comprises an image acquisition module, an image processing module, a dispensing area recognition module, a pose recognition module and a path planning module, wherein a signal transmitting end of the image acquisition module is connected with a signal receiving end of the image processing module. According to the invention, the image of the LED circuit board is acquired through the image acquisition module, then the image is sent to the image processing module, the image processing module carries out denoising, contrast enhancement processing and image quality optimization on the image data of the LED circuit board, and then the features of pins and electronic components in the circuit board are extracted from the image. Compared with a traditional image processing technology, the method has the advantages that the image processing effect is improved, the image quality is optimized, fine elements or pins can be recognized, and a foundation can be laid for follow-up path planning.

The application relates to the technical field of intelligent mines, and discloses a geological guarantee intelligent planning and mining system based on deep reinforcement learning, which comprises a geological guarantee basic module, an intelligent planning engine module and a closed-loop execution system module; the geological guarantee basic module constructs a dynamic probabilistic digital twin environment through a geological uncertainty implicit neural field, and realizes real-time data fusion and update in combination with gradient flow; the intelligent planning engine module realizes long-period risk perception planning based on a geological perception Markov decision process and a causal world model; the closed-loop execution system module deploys a lightweight model through strategy distillation, establishes a twin reality bidirectional evolution closed loop, realizes adaptive cooperation of planning and execution, and solves the problems of static vulnerability of a conventional mining system, short-sighted non-strategy planning and system fragmentation and open loop, realizes dynamic cognition, far-reaching planning and closed-loop self-evolution of the whole life cycle of a mine, and significantly improves mining efficiency and safety.

The utility model relates to the technical field of paperboard processing, and provides a paperboard gluing machine. The gluing machine comprises a gluing assembly and a first fixing rod, the gluing assembly comprises a glue spray head and a gluing head, the glue spray head and the gluing head are integrally formed, the gluing head is composed of a horizontal plate and an inclined plate, the width of the gluing head is equal to that of the glue spray head, the horizontal plate is connected with a main body of the glue spray head, and the inclined plate is connected with the main body of the glue spray head. The inclined plate is located below a glue outlet of the glue nozzle, and anti-overflow protrusions are arranged on the two side edges of the inclined plate. The gluing assemblies are evenly fixed to the first fixing rod, and the gluing assemblies are attached to one another. Each gluing assembly independently works, the gluing machine can only conduct gluing on a planned gluing area through the multiple independent gluing assemblies carried by the gluing machine, and fine gluing tasks such as intermittent gluing are achieved.

The invention relates to a workpiece nesting method and device, machining equipment and a readable storage medium. The method comprises the steps that contour machining features, a machining length constraint value and a size parameter model of a workpiece are obtained; according to the contour machining characteristics and the machining length constraint value, a machining control instruction of the workpiece is determined; and according to the machining control instruction and the size parameter model, a visual contour machining path of the workpiece is determined. According to the method, nesting of workpieces of different sizes and specifications and planning and visual display of the machining process are achieved, and compared with a traditional nesting technology, the problem that the nesting and machining requirements of laser machined parts of different sizes and specifications are difficult to meet due to the fact that the laser machined parts suitable for a machining template are relatively fixed is effectively solved; the material utilization rate can be increased, meanwhile, the workpiece nesting efficiency is improved, and the higher requirement of the laser machining process is met.

The invention provides a blade attitude detection and route correction method in fan unmanned aerial vehicle inspection, and relates to the technical field of unmanned aerial vehicle application. The method comprises the following steps: configuring an unmanned aerial vehicle, carrying a distance measuring sensor and a YOLO identification module, and obtaining the length of a fan blade; the unmanned aerial vehicle is controlled to fly to the front of a fan hub and vertically rise to the blade midpoint and the blade tip position, and related data are recorded; calculating an attitude angle of the blade according to the measured deviation angle and the actual shape of the blade, and correcting an ideal route of the unmanned aerial vehicle; and generating an inspection route adaptive to the actual position of the blade. The method can improve the inspection precision and safety, is suitable for the complex shape and position deviation of the fan blade, and improves the detection efficiency.

The application relates to the technical field of electric power inspection, and discloses a cluster type unmanned aerial vehicle inspection method based on a power transmission line and related equipment. The method comprises the following steps: obtaining a three-dimensional laser point cloud model of a target power transmission line and sensing parameters of each unmanned aerial vehicle, extracting each inspection space information and a plurality of inspection points in the three-dimensional laser point cloud model, and generating an inspection tower directory tree; performing geographic coordinate conversion on each inspection point in the inspection tower directory tree to obtain a plurality of inspection point coordinates, and calculating sensing values of each unmanned aerial vehicle based on the sensing parameters of each unmanned aerial vehicle; matching corresponding inspection point coordinates based on the sensing values, and generating corresponding route inspection lines of each unmanned aerial vehicle according to the matching results; and controlling each unmanned aerial vehicle to form an unmanned aerial vehicle cluster to inspect each inspection point according to the route inspection lines, so that inspection data is obtained. The application realizes efficient cluster type unmanned aerial vehicle inspection of a power transmission line.

The invention provides a multi-legged robot leg position planning method, device and equipment and a storage medium, and the method comprises the steps that a gait sequence of a target leg of a multi-legged robot and a current pose of the multi-legged robot are acquired, and the target leg is any leg of the multi-legged robot; according to the gait sequence, determining the phase of the target leg in each time slice corresponding to the gait sequence; and according to the current pose and the phase, planning a leg lifting point position and a foot falling point position of the target leg in each time slice. According to the technical scheme, the positions of the leg lifting point and the landing point of the legs of the multi-legged robot within a period of time can be planned.

The invention discloses a machine tool structure with a combined machine head. The device comprises a first base and a second base, and the first base is provided with a working area used for containing a to-be-machined workpiece; a first X-axis linear module is arranged on the stand column; the first group of electric discharge machining machine heads comprises at least four machine heads, the four machine heads are installed on the first base and connected to the first X-axis linear module, and any one of the four machine heads is provided with an independent Y-axis linear module and an independent Z-axis linear module; the second group of electric discharge machining machine heads comprises at least one machine head, the at least one machine head is installed on the first base, a second X-axis linear module is arranged on the second base, the at least one machine head is connected to the second X-axis linear module, and the at least one machine head is provided with an independent Y-axis linear module and an independent Z-axis linear module; and the four machine heads are connected with an electric discharge machining power supply.

This application discloses a resource allocation method, system, and storage medium. The resource allocation method includes: a target identification step, which responds to externally input demand information and matches available targets; a target filtering step, which responds to available target data, issues demand instructions to all targets in the available target data, receives at least the first feedback, and generates feedback data; a path planning step, which responds to the feedback data, calls the location of the target that issued the feedback and the location in the demand information, plans the shortest path, and generates path data; and a trajectory tracking step, which responds to the targets corresponding to the path data and feedback data, tracks the target positions, generates real-time location data, and provides real-time location feedback. The technical solution of this application can effectively improve the resource utilization and allocation efficiency in the medical industry.

The embodiment of the invention discloses an inventory method and device, communication equipment and a storage medium. The method comprises the following steps: a base station generates inventory information according to at least one of inventory service demand information, environment information, the position of the base station, the transmitting power of the base station, the position of a relay node, the transmitting power of a read-write module of the relay node and label sensitivity; the inventory information comprises a plurality of positions to which the relay node is to be moved and information representing whether label inventory operation is executed at each position; sending an instruction to the relay node based on the inventory information, wherein the instruction is used for indicating the moving position of the relay node and whether the label inventory operation is executed at the position; and receiving the inventory label information sent by the relay node.

Embodiments of the present application provide a network parameter planning method and device, the method comprises: determining the coordinate sequence of the coverage area block of the cell of the 5G base station according to the spatial topology distribution of the 5G base station in the network, determining the adjacent area block sequence of the coverage area block of the cell of the current 5G base station according to the coordinate sequence, determining the 5G base station adjacent cell sequence according to the adjacent area block sequence, and processing the PCI sequence configured for the 5G base station adjacent cell sequence to determine the target processing result from the processing result sequence, determining the target cell sequence from the 5G base station adjacent cell sequence according to the target processing result, and determining the shortest path sequence between the cell of the current 5G base station and the target cell sequence, determining the shortest distance sequence according to the shortest path sequence, determining the target shortest distance from the shortest distance sequence, and planning the PCI of the current 5G base station, which realizes the planning of the PCI parameter in the 5G base station.

The invention discloses a measuring and mapping system based on a mobile base station, and the system comprises the mobile base station which is used for providing a stable communication network; the intelligent measuring equipment is used for collecting geographic information data; the data processing module is used for processing the received geographic information data and generating a surveying and mapping result; and the output device is used for receiving, storing and displaying the surveying and mapping result. According to the measurement surveying and mapping system based on the mobile base station, through the mobile base station and the intelligent measurement equipment which are flexibly deployed, the accuracy and the integrity of surveying and mapping results are improved, and the flexibility and the high efficiency of surveying and mapping work are achieved.