208results about How to "Improve planning efficiency" patented technology

The invention discloses an unmanned aerial vehicle route planning and dynamic management and control method for an urban low-altitude airspace, and relates to the technical field of unmanned aerial vehicle route planning and dynamic management and control, and the method comprises the steps: dividing the low-altitude airspace into a basic flight layer, a buffer anti-collision layer and an emergency guarantee layer in the vertical direction; setting different air route grades and limitation rules in different areas in the horizontal direction; generating a basic airway network skeleton and performing structure optimization; obtaining the operation state and environment updating data of the unmanned aerial vehicle; semantic annotation is carried out on each leg and node in the basic airway network skeleton, and airspace regulations, supervision rules, flight limiting areas, temporary control areas and recommended flight corridor information are embedded into a semantic layer of the airway network; and inputting the basic airway network skeleton, the semantic annotation information and the real-time monitoring data into an urban low-altitude airspace management and decision-making platform. According to the invention, cooperative scheduling and avoidance among multiple unmanned aerial vehicles are realized, and the operation efficiency of an air route network and the cooperative work capability of the unmanned aerial vehicles are improved.

The invention relates to a task planning and scheduling method which is quicker, lighter and finer in task splitting based on a large model, and aims to improve the capability of processing complex tasks by calling a tool through the large model. According to the method, on the basis of a FastAPI framework, a Text-to-SQL technology, a local knowledge base, Function Calling and other core technologies are integrated, user intention understanding is completed through a large model, dynamic calling and fusion of an API interface, the knowledge base and a database are achieved on the basis of intention understanding, and the task planning, tool calling and decision support capacity of the large model in a complex scene is remarkably enhanced. By introducing a thinking chain technology of multi-level deep task decomposition, the system can decompose a complex task into a plurality of sub-tasks, an execution path is optimized, and the accuracy and execution efficiency of a multi-step reasoning task are improved. A user query tool calling module is researched and developed, user requirements can be accurately recognized and decomposed, proper tools are automatically selected and called for task processing, and efficient solving of complex problems and optimal configuration of resources are achieved.

The invention provides a path planning method and device under multi-robot cooperative work, and relates to the technical field of path planning, and the method comprises the steps: constructing a two-dimensional layout map based on the structural layout feature information of a manufacturing workshop, and carrying out the rasterization processing through combining with the structural width of a predetermined robot, and obtaining a two-dimensional layout grid map; a task allocation evaluation mechanism is introduced to analyze the transportation task set to obtain a task list, a first task and a second task are extracted, the first task corresponds to the first robot, and the second task corresponds to the second robot; obtaining a first initial path and a second initial path; judging whether a first predetermined cooperative constraint is met or not, wherein the first predetermined cooperative constraint means that path intersection exists between the first initial path and the second initial path; and if yes, performing adjustment planning. According to the method, the technical problems of task delay and safety risk increase caused by the fact that multi-party path crossing and priority conflict cannot be processed when multi-robot cooperative work is coped with by traditional path planning are solved.

The invention discloses a multi-target path planning method based on a topological map, and relates to the technical field of path planning of automatic driving vehicles, and the method comprises the following steps: S1, constructing a topological map comprising road lengths and important nodes; s2, calculating the distance between the connected road nodes, and establishing an adjacent matrix of the road nodes; s3, selecting a starting point and a plurality of target points; s4, performing multi-target path optimization calculation through an ant colony algorithm, introducing a growth type function, performing adaptive adjustment on ant pheromone volatilization, and designing updating strategies of local pheromones and global pheromones; and S5, designing an evaluation function, and planning an optimal multi-target path by comprehensively considering the conditions of the shortest global path length and the minimum number of optimization iterations of the multi-target ant colony algorithm. By means of the mode, the optimal multi-target path can be found on the topological map through the ant colony algorithm, and the path planning efficiency is improved.

The invention provides an industrial field production decision-making system and method based on an intelligent decision-making model, and the system comprises an IBP consistency plan module which is used for supporting the generation of an integrated business plan group; a plurality of different strategy plans are set for comparison, and plan decision making is assisted; the intelligent main plan decision-making module is used for supporting constraint configuration at least including productivity and materials, generating different target-oriented main plan versions and making a decision on an optimized production plan; the intelligent production planning module is used for supporting configuration of demand plans of different levels and generating a production line scheduling plan with limited capability; the system is also used for supporting visual display of a production line scheduling plan result; and the order full life cycle management module is used for measuring and calculating an order delivery plan and generating an order delivery time report by taking the order demand as input and the capacity and the material as constraints. According to the invention, an intelligent decision technology is introduced to solve the production decision problem in the industrial field.

The invention provides an automatic planning method for an imitated flight route of an unmanned aerial vehicle, and the method comprises the steps: 1, constructing a plane target track of a target flight task which comprises a starting point, an end point and n key points; 2, constructing a two-dimensional task flight profile between every two key points, and carrying out simulated path search on the two-dimensional task flight profiles to obtain a target two-dimensional track; step 3, repeating the step 2, obtaining a section of flight path between every two key points, and synthesizing each section of flight path to obtain a final unmanned aerial vehicle imitated flight path; the method comprises the following steps of: constructing a planar target track of a target flight task, constructing a two-dimensional task flight profile between every two key points, and carrying out simulated land path search on the two-dimensional task flight profiles to obtain a target two-dimensional track; and finally, the unmanned aerial vehicle imitated flight path meeting the preset flight path height adjustment constraint is obtained, the flight route is automatically planned according to the starting node and the target node, the flight path point does not need to be manually calibrated, and the flight route planning efficiency is effectively improved.

The invention relates to a robot intelligent sorting path planning method and a robot intelligent sorting path planning device for stacked parts in a charging basket, an RRT * algorithm is combined with an artificial potential field algorithm, random search of the RRT * algorithm in a barrier-free free space can be reduced by utilizing an artificial potential field, and meanwhile, in a complex barrier environment close to a part pile, the robot intelligent sorting path planning method and the robot intelligent sorting path planning device have the advantages that the random search of the RRT * algorithm in the barrier-free free space can be reduced; and an RRT * algorithm is used for accurate collision-free path planning, so that the problems of low path planning precision and local minimum of an artificial potential field algorithm are avoided. On the basis, the RRT * algorithm is improved, the problems of many redundant nodes, low planning efficiency and poor path quality existing in path planning of the RRT * algorithm are solved, meanwhile, the improved RRT * algorithm is combined with the artificial potential field algorithm, the planning scale is further reduced, and random search of the RRT * algorithm in a free space is reduced. According to the method and device provided by the invention, an efficient and accurate collision-free picking path planning scheme can be provided for industrial application of mechanical arm material frame sorting.

The invention belongs to the field of robot path planning. The invention provides an improved A * path planning method based on driver guidance and dynamic map segmentation, and aims to solve the problems that an existing path planning method is high in calculation complexity and insufficient in practicability in complex terrains and large-scale maps. A Bezier curve is adopted to fit a driver guiding path, and a dynamic map cutting method is designed based on the path, so that the calculation burden of useless areas is effectively reduced. And comprehensively considering the cost of the path length, the energy consumption and the path risk, optimizing the actual cost function and the heuristic function of the A * algorithm, and smoothing the planned path by adopting a cubic spline curve. The method can improve the efficiency and practicability of path planning.

The invention relates to a multi-ship anchoring scheduling path planning method based on an improved RRT algorithm. The method comprises the following steps: S1, constructing a multi-ship anchoring scheduling destination selection mechanism; s2, constructing a multi-ship anchoring scheduling evaluation index selection mechanism; s3, calculating ship scheduling priorities according to the multi-ship anchoring scheduling evaluation indexes; s4, constructing a multi-ship anchoring scheduling collision avoidance decision-making mechanism; and S5, calculating a multi-ship anchoring scheduling path planning result. The method can be used for coping with the situation that multiple ships need to be moored and dispatched at the same time, the berthing sequence and the sailing path of the ships are optimized, and therefore the ship anchoring dispatching waiting time is minimized, the sailing distance of all dispatched ships is reduced as much as possible, and the berth utilization rate is increased; the method is of great significance in the aspects of multi-ship scheduling in complex water areas, ship emergency evacuation, comprehensive management of water transportation hubs and the like.

The invention discloses a disaster relief unmanned aerial vehicle path planning method based on an APF-IRRT fusion algorithm, and the method comprises the following steps: initializing parameters, expanding nodes, optimizing and smoothing a path, carrying out the smoothing of the path through cubic spline curve fitting or polynomial interpolation, and finally, carrying out the planning of a disaster relief unmanned aerial vehicle path. And outputting the optimized and smoothed flight path of the unmanned aerial vehicle by setting an algorithm termination condition. According to the disaster relief unmanned aerial vehicle path planning method based on the APF-IRRT fusion algorithm, the attraction force and the repulsive force are combined with adaptive step length and sampling angle optimization, the high efficiency of path planning and the obstacle avoidance safety are realized, and meanwhile, the smoothness and the performability of the path are improved through path smoothing processing; the method is suitable for efficient path planning of unmanned aerial vehicles in complex disaster relief environments.

The invention discloses an attack path planning and key node identification method based on a large language model. The method comprises the following steps: firstly, carrying out information collection on a network environment through a network security tool to obtain a network information graph; constructing an attack path planning model based on a large language model, and specifying an action output format; a few-sample learning method is adopted to guide an attack path planning model based on a large language model to learn a network information graph, and a planning result conforming to expectation is output according to an action output format; generating an attack graph according to a planning result; the nodes in the attack graph are scored through weighted calculation of node degrees and asset importance degrees, and key nodes are identified. According to the method, a large amount of text data can be automatically analyzed and processed, potential attack paths and key nodes can be identified, and the requirement of manual intervention is reduced, so that the occurrence rate of human errors is reduced, and the planning efficiency is remarkably improved.

The invention relates to the field of path planning, in particular to a path planning method and device based on an RRTstar algorithm, equipment and a storage medium. According to the method, path exploration and planning are carried out by adopting an optimized RRT tree from a starting task point and an ending task point at the same time, the path generation speed is increased by means of powerful computing resources of a computer, and the planning efficiency is improved; then the original path depth is smoothed, the problem that the depth fluctuation of a middle path point is too large can be solved, the path is smoother, and for application scenes such as an autonomous underwater robot sensitive to depth, the influence of depth change on the performance and safety of internal instruments of the autonomous underwater robot can be reduced; iteratively optimizing the smooth path to further improve the quality and adaptability of the path; and finally, the navigation state is obtained according to the iterative optimization path, and the final navigation optimization path is obtained through adjustment according to the navigation state, so that the path planning better fits the actual navigation condition, the feasibility and safety of the path are enhanced, and it is guaranteed that the path planning is better from multiple aspects as a whole.

The present invention discloses a robot path planning method based on an improved RRT algorithm. First, nodes are generated in the form of resultant vectors, which is conducive to quickly finding a path. Secondly, the use of dynamic step size allows the algorithm to avoid the problem of difficulty in finding a path in a complex obstacle environment to a certain extent, and the anti-random tree reverse growth avoids a large amount of calculation caused by too many nodes in the later stage. Further, based on the triangle pruning strategy, the path cost is effectively reduced on the basis of the initial path, and the pruned path is smoothed using a cubic B-spline curve, which reduces the jitter of the robot and reduces the wear and tear caused by the movement of the robot. By improving the RRT algorithm, the path distance is reduced and the path quality is optimized, and blind sampling is avoided while improving the planning efficiency.

The invention provides a mechanical arm path planning method and device based on an improved random tree, and the method comprises the steps: obtaining a real scene image, and constructing a three-dimensional obstacle model; performing grating processing on the three-dimensional obstacle model to generate a repulsive force field; planning a path trajectory in the three-dimensional obstacle model based on the improved random tree; and generating a joint space path point corresponding to the mechanical arm through the inverse motion so as to control the mechanical arm. According to the method, the repulsive force field of the obstacle is generated, and the randomness of the random tree is influenced by the repulsive force field, so that the obstacle can be bypassed in the random tree planning process, and the planning efficiency is improved.

The invention discloses a shaft straightening method based on empirical value learning, which adopts a computer machine learning algorithm to optimize a straightening strategy, full-automatic straightening equipment comprises a casting horizontal measuring table and a gantry pressing device, one end of the equipment is provided with a pinch roller rotating mechanism, and the other end of the equipment is provided with a driven pinch roller. Firstly, a to-be-straightened shaft is placed on a V-shaped lifting sliding table of a casting platform, a single-side pressing wheel mechanism drives a rotating shaft to operate in a servo mode, meanwhile, the radial run-out value of the shaft at each distance is measured, the shaft bending degree is determined, the shaft adjusting sequence is generally from the middle of the shaft, the shaft is adjusted rightwards firstly and then adjusted leftwards from the middle, and after the requirement is basically met, the two ends of the shaft are adjusted; rough adjustment and straightening are conducted firstly, fine adjustment and straightening are conducted finally, and adjustment is conducted from one end of the shaft to the other end of the shaft. Through machine learning, the planning efficiency of the straightening sequence can be improved, and the overall performance of the straightening process can be improved. Through continuous learning and adaptation, the machine learning model can bring significant improvement and optimization to the straightening strategy planning stage.

The invention relates to the technical field of gold bonding wires, in particular to a gold bonding wire welding method and system based on artificial intelligence optimization. S2, constructing a grid map, and generating an initial optimal path by using an RRT algorithm; optimizing the initial optimal path by using a DWA algorithm and a bidirectional Theta * algorithm to obtain an optimal welding path; s3, a prediction model is constructed based on a machine learning algorithm, a prediction result is output, and then the optimal welding path is adjusted; s4, the workpiece is welded according to the optimal path; and S5, acquiring a workpiece image of the gold bonding wire finished product to judge whether the appearance of the gold bonding wire finished product meets a preset standard or not. According to the method, the initial optimal path generated by the RRT algorithm is optimized by combining the DWA algorithm with the bidirectional Theta * algorithm, so that the welding path planning efficiency is improved, the gold bonding wire welding safety is ensured, and the welding production efficiency and the production quality are remarkably improved.

The invention discloses a mobile terminal path planning method and system based on a distance field, and the method comprises the steps: firstly building an ESDF map, and calculating a gradient value of each grid point in the ESDF map; establishing a state vector and a discretization state transition equation of the mobile terminal based on the vehicle model; and finally, calculating the next state of the mobile terminal moving from the current node by using an improved # imgabs0 # algorithm until an optimal path from the starting node to the terminal node is formed. Wherein the ESDF cost is calculated by using the ESDF value and the gradient value of the node, and the cost function of the improved # imgabs1 # algorithm is the sum of the actual cost, the heuristic estimation cost and the ESDF cost. According to the distance field and gradient information of the ESDF map, collision detection and expansion cost calculation in the # imgabs2 algorithm are combined, and the path planning efficiency is improved while the path safety is guaranteed.

The invention relates to the technical field of testing, in particular to a path planning method and device, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining test demand information; according to the test demand information and pre-generated test case information, determining a road section or an interest point matched with the test scene; and acquiring a test path passing through the road section or the interest point. According to the scheme, on the premise of not depending on testers, the test path covering the required test scene can be automatically planned, so that the efficiency of planning the test path is improved, and the cost is reduced.

The invention provides a visualization method and system based on digital twinning, and the method comprises the steps: responding to an automatic modeling request of each planning end for planning a park, obtaining video data shot by a recording device for an entity model based on a collection visual angle, and enabling the entity model to comprise a dynamic planning area and a fixed planning area; according to the video data, determining customization elements configured for the dynamic planning area by each planning end, performing customization updating on an initial twin space corresponding to the entity model based on the customization elements, and determining the dynamic planning area which does not meet a cost planning condition as a to-be-scheduled area, calling a planning adjustment strategy to adjust and update a virtual planning area corresponding to the to-be-adjusted area in the initial twin space to obtain customized display spaces corresponding to the planning ends, and obtaining selection coefficients corresponding to the customized display spaces, and determining that the customized display space with the maximum selection coefficient is a planned selected space corresponding to the planned park.

The invention relates to the field of power distribution network optimization, in particular to a novel power system power distribution network planning method and system, and the method comprises the following steps: step 1, data collection, step 2, mathematical modeling, step 3, simulation analysis, step 4, optimization design, step 5, feasibility evaluation, step 6, scheme making, and step 7, scheme implementation. The method comprises the following steps: firstly, collecting and arranging related data through a data management module; then visual display and spatial analysis are carried out by utilizing a geographic information system module; performing multi-aspect planning analysis through a planning analysis module; an optimal planning scheme is found by using an optimization planning module; finally, a detailed planning report is generated through a report generation module, automation and intelligentization of power distribution network planning are achieved through modular design, meanwhile, all the modules cooperate with one another, a complete planning system is formed, and the planning efficiency and accuracy are improved.

The invention provides a rear wheel steering vehicle track planning method and system in a road scene based on iterative optimization, and the method comprises the steps: S1, building an optimization problem, and deducing a kinematics formula of a rear wheel steering vehicle, an obstacle avoidance constraint formula, and a calculation formula of the distance and angle error between a rear axle center point and a road center line; s2, on the basis of a road scene structure, constructing a collision-free track which fits a road center line as much as possible to serve as an initial guess in an optimization problem; s3, solving an approximate feasible track, softening the kinematics constraint into a penalty function, constructing a space-time corridor constraint, and constructing and solving an optimization problem to obtain the approximate kinematics feasible track; and S4, solving an optimal track, and gradually increasing sampling points in the optimization problem until the number of the sampling points reaches a threshold value. The method is combined with a vehicle positioning algorithm, track planning of the rear wheel steering vehicle in a road scene can be realized, scene robustness is realized, and the quality of the planned track is high.

The present invention relates to a multi-ship anchoring scheduling path planning method based on an improved RRT algorithm, comprising the following steps: S1, constructing a multi-ship anchoring scheduling destination selection mechanism; S2, constructing a multi-ship anchoring scheduling evaluation index selection mechanism; S3, calculating the ship scheduling priority according to the multi-ship anchoring scheduling evaluation index; S4, constructing a multi-ship anchoring scheduling collision avoidance decision-making mechanism; S5, calculating the multi-ship anchoring scheduling path planning result. The present invention can be used to deal with the situation where multiple ships need anchoring scheduling at the same time, optimize their berthing sequence and navigation path, thereby minimizing the ship anchoring scheduling waiting time, reducing the navigation distance of all scheduled ships as much as possible, and improving the berth utilization rate; it has important significance in multi-ship scheduling in complex waters, emergency evacuation of ships, and comprehensive management of water transportation hubs.

The invention discloses a space-time joint trajectory planning method for an unmanned vehicle in a non-structural environment, which belongs to the technical field of robot systems and comprises a mixed A * sampling step, a cost function design step, a constraint condition design step and a quadratic planning step. In the mixed A * sampling step, an initial planning track of the unmanned vehicle is obtained through a mixed A * algorithm, and sampling is carried out at equal time intervals, so that an initial solution of space-time joint planning of the unmanned vehicle in the unstructured environment is generated; the space-time joint trajectory planning step is used for constructing a space-time joint trajectory planning proposition of the unmanned vehicle in a non-structural environment, and the quadratic programming step is used for performing space-time joint optimization on the trajectory obtained in the mixed A * sampling step by using a quadratic programming solver so as to form a safe, executable and higher-quality unmanned vehicle trajectory.

The invention provides a unified context and multi-level memory cooperation system and method for an LLM agent, and belongs to the field of artificial intelligence. The system comprises a unified context module which is used for aggregating and structuring all input information required for organizing agent operation, and providing an integrated context view for an LLM agent core; the LLM agent core is used for executing task planning, tool calling, result evaluation and response generation based on the context provided by the unified context module; and the multi-level memory system is connected with the unified context module and the LLM agent core and is used for hierarchically storing, managing and feeding back experience and knowledge of the agents. According to the method, the problems that an existing LLM intelligent agent is limited in context, low in memory efficiency and lack of self-correction capacity are solved, and the intelligent level and reliability of complex task processing are remarkably improved.

The invention provides an HMI-based stack type planning method, device and equipment and a storage medium, and the method comprises the steps: displaying a stack type planning interface in an HMI, and enabling the stack type planning interface to comprise a stack type list; the new stack type interface comprises a stack type layer number, stacking type and bar code orientation setting area and a manual stack type planning area, inputting material parameter information and tray parameter information in the new stack type interface, and setting the stack type layer number, the stacking type and the bar code orientation to generate at least one reference stack type; the generated reference stack type is displayed in the manual stack type planning area; and determining a reference stack type as a target stack type according to selection indication information of the user or a preset priority. Therefore, stack type planning of various different materials and different trays can be carried out through the HMI, the stack type planning capability is greatly improved by combining a stack type planning algorithm and an artificial auxiliary planning mode, the planning efficiency is high, and the method is suitable for scenes with a large number of materials and various materials and high in reliability.

The invention provides an inverter type selection method of a photovoltaic power generation system and a related product. The inverter type selection method of the photovoltaic power generation system comprises the following steps: acquiring a photovoltaic design scheme of the photovoltaic power generation system; determining electrical parameters of three groups of different types of inverters according to the electrical parameters, wherein the three groups of different types of inverters comprise a string type inverter, a centralized inverter and a micro inverter; determining the mechanical performance requirements of the three groups of different types of inverters according to the installation mode; selecting matched alternative equipment models of three different types of inverters from an inverter model selection library according to the electrical parameters and the mechanical performance requirements; generating three groups of alternative inverter type selection schemes according to the selected alternative equipment types of the three different types of inverters; and selecting a target inverter from the three groups of alternative inverter type selection schemes. The scheme provided by the invention is wide in application scene, and suitable inverter schemes can be provided for various photovoltaic design schemes.

The present invention provides a method and system for optimizing the configuration of distribution network resources based on artificial intelligence. It relates to data processing technology, and the method includes: establishing a virtual network corresponding to the distribution network based on digital twin technology, obtaining the power planning starting point and the power planning ending point selected by the resource configuration end; determining the initial planning route composed of the power planning starting point and the ending point, and performing corridor interception on the virtual corridor based on the relative position relationship between the initial planning route and the virtual corridor to obtain the corridor planning section; segmenting the corridor planning section, and updating the route of the initial planning route based on each divided sub-segment of the corresponding idle attribute to obtain the current planning route; configuring route temperature control, and sending circuit resource optimization data to the resource configuration end; in response to receiving the configuration completion signal sent by the resource configuration end, obtaining temperature monitoring data, and updating the operation status of the current planning route in the virtual network. The present invention at least improves the planning efficiency.

The invention discloses a multi-station welding robot coordinated motion planning method and an off-line programming system, and the method specifically comprises the steps of welding pose optimization, welding taboo table generation, welding spot redistribution, same-direction welding sequence optimization, single robot path planning, track scanning body generation of all robots, track scanning body interference inspection and the like. And coordinated optimization of paths of multiple robots is realized. According to the method, multiple optimization strategies and planning methods are provided, coordinated motion planning and track generation of multi-station multi-robot welding paths are achieved, an automatic offline programming system of multiple welding robots is developed, and the motion planning efficiency of the multi-robot welding process is remarkably improved.

The invention discloses a method and system for routing inspection of a cable channel by an unmanned aerial vehicle, and the method comprises the steps: carrying out the routing inspection of the cable channel in construction through the unmanned aerial vehicle at a channel construction stage, and carrying out the geographic position calculation and modeling of the cable channel based on a language prompt word coding module and closed operation; planning a cable channel inspection route based on the established cable channel model; in the inspection stage, the unmanned aerial vehicle autonomously flies according to a planned route and shoots real-time images, and hidden danger target recognition and effective alarm analysis of the position and the moving direction are carried out on each frame of image. The route planning efficiency is high, and the polling effect and timeliness are improved.

The invention provides a design method of a cable connection mode in a photovoltaic power generation project and a related product. The design method of the cable connection mode in the photovoltaic power generation project comprises the steps of obtaining a photovoltaic panel design scheme of the photovoltaic power generation project; reading the specification, number, arrangement mode and accessed inverter parameters of photovoltaic units in a photovoltaic array in the photovoltaic panel design scheme; determining the number of the photovoltaic units connected in series in each photovoltaic string according to the specifications and the number of the photovoltaic units and the parameters of the inverter; generating a to-be-selected wiring scheme according to the arrangement mode and the number of the photovoltaic units connected in series in each photovoltaic string; and simulating the to-be-selected wiring scheme, selecting the to-be-selected wiring scheme with the optimal simulation result, and combining the to-be-selected wiring scheme with the photovoltaic panel design scheme to form an overall scheme of a photovoltaic power generation project. According to the scheme, automatic design of the cable connection mode in a photovoltaic power generation project is achieved, the design efficiency is improved, the power generation efficiency of photovoltaic power generation can be improved, and the requirements of construction owners are met.