CN118246847A - AGV site-based custom service path planning configuration system - Google Patents
AGV site-based custom service path planning configuration system Download PDFInfo
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Abstract
The invention discloses a self-defined business path planning configuration system based on AGV sites, which relates to the technical field of AGV site path planning and comprises a starting module, a scheduling module, a path monitoring module, an abnormality alarm module and a finishing module; and a starting module: the system comprises a WMS system, a coil winder, a wireless communication system and a wireless communication system, wherein the WMS system is used for acquiring a coil winder and cargo data, and sending a cargo position data acquisition request to the WMS system according to the cargo data; and a scheduling module: the method comprises the steps of acquiring cargo position data and AGV position data, and sending a starting point task and an ending point task to the AGV; and a path monitoring module: acquiring task execution data; an abnormality alarm module: a task abnormality analysis model is built according to the input preset of task execution data, task abnormality conditions are judged, and an alarm is sent out; and (3) a finishing module: after acquiring a task completion signal of the AGV, sending a discharge completion signal to the WMS system, and occupying a cargo space; the invention designs a method for effectively butting with third-party automation equipment and timely finding task execution deviation.
Description
Technical Field
The invention relates to the technical field of AGV site path planning, in particular to a system for planning and configuring a self-defined business path based on AGV sites.
Background
An AGV is an unmanned vehicle that is guided through an automatic navigation system. AGVs are used primarily in industrial applications, such as warehouse, manufacturing, and distribution centers, to achieve automated material handling, transport, and logistics; an AGV station refers to a preset location or area where the AGV performs a particular operation during operation. These operations include loading and unloading of materials, charging, maintenance and waiting for task instructions, etc.
The communication of GV when interconnecting and communicating with the third-party automation equipment or system is divided into a TCP communication protocol based on Modbus, a TCP/IP communication protocol based on Socket communication, a Services interface communication protocol based on an upper computer system and a WebAPI communication protocol based on an upper computer; all communication protocols are based on three-party safe and effective handshake communication and disconnection reconnection technology.
For example, publication number: the invention of CN115796553B discloses an AGV task scheduling method, an AGV task scheduling device and an AGV scheduling system, wherein in the current scheduling period, the waiting time length of each AGV task to be scheduled under the condition of not completing overtime is respectively determined according to the current time, and the scheduling sequence of each AGV task to be scheduled in the current scheduling period is determined based on the waiting time length and the task priority of each AGV task to be scheduled. And if the scheduling rule is met, performing task scheduling according to the scheduling sequence of each AGV task to be scheduled in the current scheduling period. Because the scheduling order is positively correlated with the waiting time length and negatively correlated with the task priority, the shorter the waiting time length, the higher the timeout risk, the smaller the scheduling order, and the earlier the scheduling is, under the same task priority. Under the condition that the waiting time length is the same, the higher the task priority, the smaller the scheduling order, and the earlier the task is scheduled. Thus, the punctual rate of the execution of the AGV task can be improved.
For example, publication number: the invention of CN113592158B discloses a multi-AGV path planning and a combined scheduling method of AGVs and machines in a multi-AGV intelligent production line, adopts an A-type algorithm and a time window to combine, detects conflict among AGVs in advance by using the time window, avoids the conflict by adopting a mode of waiting or replacing the paths, blends the conflict into an improved A-type algorithm, and finally can plan a conflict-free path with the shortest time from a task starting point to a task ending point for the AGVs. According to the invention, an AGV and machine joint scheduling mathematical model with the minimum maximum finishing time as an optimization target in an intelligent production line is established, the constraint of AGV resources, namely the scheduling problem of the intelligent production line, is increased on the basis of a flexible workshop scheduling problem, and a hybrid genetic algorithm is provided for solving the model. The mixed genetic algorithm adopts a three-segment chromosome coding method to obtain a feasible solution of the problem, corresponding selection, crossing and mutation operations are designed, and a multi-AGV path planning algorithm is integrated into a decoding process to obtain a scheduling result of an intelligent production line.
In the above disclosed technical solution, at least the following technical problems exist: the AGV is an independent scheduling system, and lacks effective butt joint with the third-party automation equipment and the third-party system in the actual operation process; meanwhile, hidden danger of task execution deviation and even failure exists, and the task cannot be found timely, so that other subsequent problems are caused.
The present invention proposes a solution to the above-mentioned problems.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present invention provides a system for planning and configuring a customized service path based on an AGV site, and solves the problems set forth in the above-mentioned background art by performing path planning on the AGV site.
In order to achieve the above purpose, the present invention provides the following technical solutions:
The system is characterized by comprising a starting module, a scheduling module, a path monitoring module, an abnormality alarming module and a finishing module; and a starting module: the system comprises a WMS system, a coil winder, a wireless communication system and a wireless communication system, wherein the WMS system is used for acquiring a coil winder and cargo data, and sending a cargo position data acquisition request to the WMS system according to the cargo data; and a scheduling module: the method comprises the steps of acquiring cargo position data and AGV position data, and sending a starting point task and an ending point task to the AGV; and a path monitoring module: acquiring task execution data, wherein the task execution data comprises path data and coding data; an abnormality alarm module: a task abnormality analysis model is built according to the input preset of task execution data, task abnormality conditions are judged, and an alarm is sent out; and (3) a finishing module: after acquiring the task completion signal of the AGV, sending a discharge completion signal to the WMS system, and occupying the cargo space.
In a preferred embodiment, the path data includes pick-and-delivery anomaly coefficients and transport process interaction anomaly coefficients, and the code data includes code labeling anomaly coefficients.
In a preferred embodiment, the specific method for obtaining the abnormal coefficient of the picking and delivering goods is as follows:
Calculating a time difference value between the actual transportation time and the expected transportation time, evaluating a position deviation value of a target position in AGV loading, obtaining a vibration amplitude, and calculating and obtaining a goods taking and delivering abnormal coefficient by combining the time difference value, the position deviation value and the vibration amplitude through a geometric average method.
In a preferred embodiment, the specific method for obtaining the interactive anomaly coefficient in the conveying process is as follows: collecting interactive data of the AGV in the actual conveying process, wherein the interactive data comprise data and time of opening and closing the door and going up and down the elevator each time; preprocessing the acquired interaction data, including repeated record removal and missing value processing; extracting interactive features which can be used for analysis according to the interactive data, wherein the interactive features comprise duration time of opening and closing each time, frequency of opening and closing the door and frequency of using the elevator; carrying out event clustering on the interaction event data based on a K-means clustering algorithm; based on the time cluster identification, an abnormal cluster is obtained, and the interactive abnormal coefficient of the transportation process is obtained by calculating the proportion of abnormal events in the abnormal cluster.
In a preferred embodiment, the specific method for obtaining the coded labeling anomaly coefficient is as follows: acquiring a history of each code printing and labeling task, recording a history error rate, and calculating an average error rate and an error rate standard deviation; setting an upper control limit and a lower control limit according to the expected error rate and the error rate standard deviation; recording the number of abnormal coding events exceeding an upper control limit and a lower control limit in real time; and comparing and analyzing the abnormal coding false quantity and the total task quantity to obtain coding labeling abnormal coefficients.
In a preferred embodiment, the task abnormality determination and alarm generation specifically include: specifically, the abnormality evaluation coefficient is compared with a preset abnormality evaluation threshold, and when the abnormality evaluation coefficient is greater than the preset abnormality evaluation threshold, an alarm is sent.
The invention discloses a system for planning and configuring a service path based on AGV site custom, which has the technical effects and advantages that:
1. the invention realizes unmanned operation by utilizing the automatic navigation system and is flexibly applied to material handling and logistics automation in industrial scenes. The technical means include automatic navigation technology (such as magnetic tape, laser, vision and GPS navigation), flexible path configuration, safety sensors and programmability, which enable efficient continuous operation, reduced human error and execution of tasks according to different business requirements. WMSs (warehouse management systems) provide real-time data and analysis support through functions such as inventory, order and task management to optimize warehouse operations and logistics. The AGV and the WMS are coordinated, smoothness of a logistics process is guaranteed through path planning and task distribution, meanwhile, abnormal coefficients of potential task execution deviation are analyzed, early warning is carried out in advance, measures are taken, and therefore accuracy, efficiency and safety of a logistics system are comprehensively improved.
2. According to the invention, the starting module is responsible for acquiring the offline signal and the goods data from the reel machine and sending a request to the WMS system to acquire the goods position data, so that the goods position can be accurately mastered. The dispatching module is used for acquiring the position data of cargoes and AGVs, and sending starting point tasks and ending point tasks to the AGVs according to the data so as to effectively dispatch and manage the transportation tasks. The path monitoring module is responsible for acquiring task execution data, including path data and coding data, so as to help monitor and optimize abnormal conditions in the transportation process. The abnormality alarming module establishes an abnormality analysis model according to task execution data, and gives an alarm when abnormal conditions of tasks are detected, and possible problems are timely early-warned. Finally, the finishing module sends a discharging completion signal to the WMS system after the AVG completes the task, and updates the goods space state so as to ensure the accuracy and timeliness of the logistics information. The cooperative work of the modules can improve the efficiency and reliability of logistics transportation, and simultaneously, potential problems can be timely dealt with through anomaly analysis and early warning, so that smooth execution of tasks is ensured.
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FIG. 1 is a schematic diagram of a system for planning and configuring a service path based on AGV site customization.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In embodiment 1, fig. 1 shows a system for planning and configuring a service path based on self-definition of an AGV site, which comprises a starting module, a scheduling module, a path monitoring module, an abnormality alarm module and a finishing module.
And a starting module: the system comprises a WMS system, a coil winder, a wireless communication system and a wireless communication system, wherein the WMS system is used for acquiring a coil winder and cargo data, and sending a cargo position data acquisition request to the WMS system according to the cargo data;
And a scheduling module: the method comprises the steps of acquiring cargo position data and AGV position data, and sending a starting point task and an ending point task to the AGV;
and a path monitoring module: acquiring task execution data, wherein the task execution data comprises path data and coding data;
An abnormality alarm module: a task abnormality analysis model is built according to the input preset of task execution data, task abnormality conditions are judged, and an alarm is sent out;
and (3) a finishing module: after acquiring the task completion signal of the AGV, sending a discharge completion signal to the WMS system, and occupying the cargo space.
The reel is a device similar to an elevator for initially transporting goods to a goods storage place, and when the reel is off-line, the existing goods are sent to a certain goods taking point of a warehouse by the reel.
AGV (Automated Guided Vehicle) is an unmanned vehicle that is guided for travel by an automatic navigation system. AGVs are used primarily in industrial applications, such as warehouse, manufacturing, and distribution centers, to achieve automated material handling, transport, and logistics; the following are the main features of the AGV:
Automatic navigation: the AGV can automatically run according to a preset path or through a real-time path planning system, and common navigation technologies comprise magnetic tape, laser, vision, GPS navigation and the like; flexibility: the paths and tasks can be reconfigured according to the needs, and manual intervention is not needed; safety: various sensors (such as laser radar, ultrasonic sensor, etc.) are equipped to avoid collision and ensure safety; high efficiency: the device can continuously work, improves the efficiency of transportation and material handling, and reduces human errors; programmability: programming can be performed according to different business requirements, and complex tasks and path planning can be performed.
WMSs (Warehouse MANAGEMENT SYSTEM, i.e., warehouse management systems) are software systems used to optimize and manage warehouse operations. The system can track warehouse inventory, manage order fulfillment process, improve warehouse efficiency, provide real-time data and analysis support, and has the following main effects: inventory management: tracking inventory levels and locations in real time; managing warehouse entry, warehouse exit and inventory of the inventory; providing an inventory report and analyzing; order management: receiving and processing a customer order; optimizing order picking, packaging and shipping processes; tracking the status and delivery conditions of the order; and (3) task management: tasks of warehouse staff are distributed and managed; optimizing task allocation to improve efficiency; monitoring the task completion and performance; warehouse layout optimization: designing and optimizing warehouse layout to maximize space utilization; analyzing the storage locations to reduce picking time; report and analysis: providing various operation reports and KPIs (key performance indicators); analyzing warehouse operational data to support decisions; integration and automation: integrated with ERP (Enterprise resource planning) systems, MES (manufacturing execution systems), AGV systems, etc.; support the operation and management of automated equipment and robots (e.g., AGVs, AS/RSs, etc.).
The WMS of the present invention is primarily responsible for calculating and managing the storage location of goods. When the route planning management system requests the destination location, the WMS receives the request and calculates the appropriate storage location. Then, after the AGV finishes the task and discharges at the destination, the WMS system receives the discharge completion signal, updates the goods space state and ensures the accuracy and timeliness of the inventory information. Through these functions, WMSs play a key role in coordination and management throughout the logistics operation.
And a starting module: the system comprises a WMS system, a coil winder, a wireless communication system and a wireless communication system, wherein the WMS system is used for acquiring a coil winder and cargo data, and sending a cargo position data acquisition request to the WMS system according to the cargo data;
The goods data comprise the size of goods, the type of goods and the initial position of goods; the cargo position data comprises available cargo position, cargo taking position and cargo transporting route;
And a scheduling module: the method comprises the steps of acquiring cargo position data and AGV position data, and sending a starting point task and an ending point task to the AGV;
specifically, when the WMS calculates the cargo data, the cargo data is fed back to the present invention, and the cargo is fetched to the pick-up location as the start task of the AGV, and unloaded to the available cargo location as the end task.
And a path monitoring module: acquiring task execution data, wherein the task execution data comprises path data and coding data;
Specifically, the path data comprises a picking and delivering abnormal coefficient and a conveying process interaction abnormal coefficient, and the coding data comprises a coding and labeling abnormal coefficient.
In the process of picking and loading the goods, which is interacted by the AGV and the reel, the docking failure caused by inaccurate positioning, the operation interruption caused by communication faults, equipment damage or safety accidents caused by mechanical and sensor faults, task deviation caused by path planning errors, navigation problems caused by environmental factors such as barriers and uneven ground, and goods damage caused by misoperation can occur.
Analyzing the pick-up delivery data for potential hazards of deviation or failure of the analysis task has the following advantages:
The problem root occurring in the task execution process can be accurately positioned by analyzing detailed goods taking and delivering data; for example, it can be identified at which link the deviation or failure occurred, whether during the pick-up phase, during transport or during discharge;
the real-time analysis of the data can help to find abnormal conditions in time, and early warning is sent out in advance to prevent further expansion of problems; this is particularly important to avoid potential hazards that may lead to task failure;
The data analysis can help to identify and eliminate weak links in the system, improve the cooperative work reliability of the AGV and other equipment, and reduce task failure caused by equipment or system problems;
abnormal data which possibly causes potential safety hazards are identified, targeted measures can be taken to prevent accidents, and the safety of personnel and equipment is ensured;
By analyzing the historical data, the overall performance of the AGV system can be evaluated, repeated problems are identified, and improvement measures are formulated, so that the performance of the system is continuously improved;
based on analysis and decision of data, objective and accurate basis can be provided, a management layer is helped to make more scientific and effective decisions, and operation efficiency and reliability are improved;
By analyzing the trend and the mode, possible faults of the equipment can be predicted, preventive maintenance is performed in advance, and task failures caused by sudden faults are reduced.
Therefore, through analysis of the goods taking and delivering data, the precision, efficiency and safety of the AGV system can be comprehensively improved, the flow is optimized, the reliability of the system is enhanced, and a decision basis for data support is provided. The method not only can timely find and solve the deviation and hidden danger in task execution, but also can lay a foundation for long-term system optimization and performance improvement.
The specific acquisition method of the abnormal coefficient of the goods taking and delivering is as follows:
Calculating a time difference value between the actual transportation time and the expected transportation time, evaluating a position deviation value of a target position in AGV loading, obtaining a vibration amplitude, and calculating and obtaining a goods taking and delivering abnormal coefficient by combining the time difference value, the position deviation value and the vibration amplitude through a geometric average method.
Wherein the time difference valueThe specific calculation formula of (2) is as follows:
Position deviation value The specific calculation formula of (2) is as follows:
Vibration amplitude The specific calculation formula of (2) is as follows:
Then, the specific calculation formula of the abnormal coefficient of picking and delivering goods is as follows:
In the method, in the process of the invention, For the actual transit time,/>To predict the transit time,/>For the initial position coordinates,/>For the target position coordinates, N is the length of the time series,/>For the vibration frequency at the ith time point in the time series N,/>To obtain abnormal coefficients of delivery.
According to the calculation formula of the goods taking and delivering abnormal coefficients, when the appearance value of the goods taking and delivering abnormal coefficients is larger, the potential safety hazard existing in the process of goods taking and delivering is larger; otherwise, the smaller the representation value of the goods taking and delivering abnormal coefficient is, the smaller the potential safety hazard existing in the goods taking and delivering process is.
The safety problem of the interactive link is particularly important in the AGV shipping process. The interaction links of opening the door, closing the door, getting on the elevator and the like have various potential safety hazards, such as personnel or articles possibly being hit in the door opening process, accidents possibly occurring on the elevator and the like. Therefore, it is important to effectively monitor and evaluate anomalies in these interactive processes.
Analyzing the interactive abnormal coefficient of the conveying process has the following advantages of:
identifying potential risks in advance: the interaction anomaly coefficient can timely find out anomaly conditions existing in the interaction process, including mismatching of door opening and closing times, abnormal elevator use and the like, so that potential safety risks are identified in advance;
Quantitatively evaluating security: through calculation of the interaction anomaly coefficient, the safety problem in the interaction process can be quantized into an index, so that the safety evaluation is objective and accurate;
auxiliary decision making: the interaction anomaly coefficient provides an intuitive reference for decision makers, and can help the decision makers to better understand potential safety hazards existing in the interaction process, so that more reasonable countermeasures and decision schemes are made;
The accident occurrence probability is reduced: by timely finding and processing the interaction abnormal condition, the probability of accident occurrence can be effectively reduced, and smooth execution and safe execution of the transport task are ensured;
the task execution efficiency is improved: the analysis of the interaction anomaly coefficient is helpful to find potential hidden danger of task execution deviation or failure, so that the problem is solved in time, and the task execution efficiency and quality are improved;
Therefore, the interactive abnormal coefficient in the transportation process can be analyzed to timely find possible abnormal conditions, so that corresponding measures are taken to ensure the safe and smooth operation of the transportation process.
The specific acquisition method of the interactive anomaly coefficient in the conveying process comprises the following steps:
Collecting interactive data of the AGV in the actual conveying process, wherein the interactive data comprise data and time of opening and closing the door and going up and down the elevator each time;
Preprocessing the acquired interaction data, including repeated record removal and missing value processing;
Extracting interactive features which can be used for analysis according to the interactive data, wherein the interactive features comprise duration time of opening and closing each time, frequency of opening and closing the door and frequency of using the elevator;
Carrying out event clustering on the interaction event data based on a K-means clustering algorithm;
obtaining an abnormal cluster based on time cluster identification, and obtaining interactive abnormal coefficients in the conveying process by calculating the proportion of abnormal events in the abnormal cluster;
The specific calculation formula of the interactive anomaly coefficient in the conveying process is as follows:
In the method, in the process of the invention, For the transport process to interact anomaly coefficients,/>For the number of clusters,/>Is the number of exceptional events in the j-th cluster,/>Is the total number of events in the j-th cluster.
According to the calculation formula of the interactive abnormal coefficient in the transportation process, when the expression value of the interactive abnormal coefficient in the transportation process is larger, the potential safety hazard existing in the interactive link in the transportation process is larger; otherwise, when the expression value of the interactive abnormal coefficient in the transportation process is smaller, the potential safety hazard existing in the interactive link in the transportation process is indicated to be smaller.
During the shipment, the AGV (automatic guided vehicle) must interact seamlessly with the coding machine to ensure that the goods can be coded and labeled accurately. However, such interaction processes may face a variety of potential task failure risks and safety hazards. For example, communication interruptions between the AGV and the encoder may cause the labels to print incorrectly or fail entirely, thereby affecting the tracking of the goods and logistics. In addition, if the AGV fails or malfunctions during interaction with the coding machine, it may cause cargo retention or mishandling and may even pose a threat to the safety of the personnel. Therefore, ensuring stable, efficient interaction between the AGV and the code printer is critical, and proper techniques and safety measures need to be taken to minimize the risk of task failure and potential safety hazards.
The hidden danger of analyzing the execution deviation or failure of the code printing and labeling abnormal coefficient has the following advantages:
Identifying problems in advance: by monitoring the abnormal coefficient of the code printing and labeling, the deviation or failure in task execution can be found early; an increase in anomaly coefficients may indicate problems in certain links, such as failure of the AGV to interact with the printer or degradation of label print quality.
Quantitatively evaluating risk: the abnormal coefficient can be used as a quantization index to help evaluate the risk degree of task execution; with the increase of the abnormal coefficient, the risk may gradually rise, and measures need to be taken in time to prevent task failure;
Optimizing and deciding: by analyzing the abnormal coefficients, the problems in the task execution process can be further understood, so that the decision is optimized and the logistics flow is timely adjusted; for example, the interaction mode of the AGV and the coding machine can be adjusted according to the change of the abnormal coefficient or the maintenance level of equipment can be improved, so that the possibility of task failure is reduced;
Continuous improvement: monitoring and analysis of anomaly coefficients helps to establish a mechanism for continued improvement; by continuously tracking the change of the abnormal coefficient, potential problem points can be identified and targeted improvement measures can be taken, so that the stability and efficiency of task execution are improved.
Therefore, analyzing the abnormal coefficient of code printing and labeling can effectively help identify hidden trouble of task execution deviation or failure, and provides important reference for management and optimization of the logistics transportation process.
The specific acquisition method of the code printing and labeling abnormal coefficient comprises the following steps:
Acquiring a history of each code printing and labeling task, recording a history error rate, and calculating an average error rate and an error rate standard deviation;
setting an upper control limit and a lower control limit according to the expected error rate and the error rate standard deviation;
recording the number of abnormal coding cases exceeding the upper control limit and the lower control limit in real time; and comparing and analyzing the abnormal coding false quantity and the total task quantity to obtain coding labeling abnormal coefficients.
Wherein, the calculation formula of the average error rate is as follows:
the specific calculation formula of the error rate standard deviation is as follows:
the specific calculation formula of the coding labeling abnormal coefficient is as follows:
In the method, in the process of the invention, Labeling abnormal coefficients for coding,/>Index for historic error rate,/>For average error rate,/>Is error rate standard deviation,/>Is the total number of historical error rates,/>Is the historical error rate.
According to the calculation formula of the code marking and labeling abnormal coefficients, the greater the expression value of the code marking and labeling abnormal coefficients is, the greater the potential safety hazard exists in the code marking and labeling process is; otherwise, the smaller the expression value of the code-printing labeling abnormal coefficient is, the smaller the potential safety hazard existing in the code-printing labeling process is.
The embodiment realizes unmanned operation by utilizing the automatic navigation system and is flexibly applied to material handling and logistics automation in industrial scenes. The technical means include automatic navigation technology (such as magnetic tape, laser, vision and GPS navigation), flexible path configuration, safety sensors and programmability, which enable efficient continuous operation, reduced human error and execution of tasks according to different business requirements. WMSs (warehouse management systems) provide real-time data and analysis support through functions such as inventory, order and task management to optimize warehouse operations and logistics. The AGV and the WMS are coordinated, smoothness of a logistics process is guaranteed through path planning and task distribution, meanwhile, abnormal coefficients of potential task execution deviation are analyzed, early warning is carried out in advance, measures are taken, and therefore accuracy, efficiency and safety of a logistics system are comprehensively improved.
Embodiment 2, abnormality alert module: and inputting preset task execution data to establish a task abnormality analysis model, judging task abnormality conditions and giving an alarm.
Specifically, the specific formula of the task anomaly analysis model is as follows:
In the method, in the process of the invention, For the anomaly evaluation coefficient,/>For the preset proportion coefficient of the abnormal coefficient of picking and delivering goods,/>For the preset proportionality coefficient of the interactive abnormal coefficient in the conveying process,/>Preset proportional coefficient of abnormal coefficient is marked for coding,/>For taking and delivering abnormal coefficient,/>For the preset proportionality coefficient of the interactive abnormal coefficient in the conveying process,/>Preset proportional coefficient for marking abnormal coefficient by code printing and/>、/>、/>Are all greater than 0.
Specifically, the abnormality evaluation coefficient is compared with a preset abnormality evaluation threshold, and when the abnormality evaluation coefficient is greater than the preset abnormality evaluation threshold, an alarm is sent.
And (3) a finishing module: after the task completion signal of the AVG is obtained, a discharging completion signal is sent to the WMS system, and the cargo space is occupied.
According to the embodiment, the starting module is responsible for acquiring the offline signal and the goods data from the reel machine and sending a request to the WMS system to acquire the goods position data, so that the goods position can be accurately mastered. The dispatching module is used for acquiring the position data of cargoes and AGVs, and sending starting point tasks and ending point tasks to the AGVs according to the data so as to effectively dispatch and manage the transportation tasks. The path monitoring module is responsible for acquiring task execution data, including path data and coding data, so as to help monitor and optimize abnormal conditions in the transportation process. The abnormality alarming module establishes an abnormality analysis model according to task execution data, and gives an alarm when abnormal conditions of tasks are detected, and possible problems are timely early-warned. Finally, the finishing module sends a discharging completion signal to the WMS system after the AVG completes the task, and updates the goods space state so as to ensure the accuracy and timeliness of the logistics information. The cooperative work of the modules can improve the efficiency and reliability of logistics transportation, and simultaneously, potential problems can be timely dealt with through anomaly analysis and early warning, so that smooth execution of tasks is ensured.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product.
Those of ordinary skill in the art will appreciate that the various illustrative modules and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The system is characterized by comprising a starting module, a scheduling module, a path monitoring module, an abnormality alarming module and a finishing module;
And a starting module: the system comprises a WMS system, a coil winder, a wireless communication system and a wireless communication system, wherein the WMS system is used for acquiring a coil winder and cargo data, and sending a cargo position data acquisition request to the WMS system according to the cargo data;
And a scheduling module: the method comprises the steps of acquiring cargo position data and AGV position data, and sending a starting point task and an ending point task to the AGV;
and a path monitoring module: acquiring task execution data, wherein the task execution data comprises path data and coding data;
An abnormality alarm module: a task abnormality analysis model is built according to the input preset of task execution data, task abnormality conditions are judged, and an alarm is sent out;
and (3) a finishing module: after acquiring the task completion signal of the AGV, sending a discharge completion signal to the WMS system, and occupying the cargo space.
2. The AGV site-based custom business path planning configuration system of claim 1, wherein the path data comprises pick-and-delivery anomaly coefficients and transport process interaction anomaly coefficients, and the code data comprises code labeling anomaly coefficients.
3. The AGV site-based custom traffic path planning configuration system according to claim 2, wherein the specific formula of the task anomaly analysis model is as follows:
In the above, the ratio of/> For the anomaly evaluation coefficient,/>For the preset proportion coefficient of the abnormal coefficient of picking and delivering goods,/>For the preset proportionality coefficient of the interactive abnormal coefficient in the conveying process,/>Preset proportional coefficient of abnormal coefficient is marked for coding,/>For taking and delivering abnormal coefficient,/>For the preset proportionality coefficient of the interactive abnormal coefficient in the conveying process,/>Preset proportional coefficient for marking abnormal coefficient by code printing and/>、/>、/>Are all greater than 0.
4. The system for planning and configuring a customized service path based on an AGV site according to claim 3, wherein the specific method for obtaining the abnormal coefficient of picking and delivering goods is as follows:
Calculating a time difference value between the actual transportation time and the expected transportation time, evaluating a position deviation value of a target position in AGV loading, obtaining a vibration amplitude, and calculating and obtaining a goods taking and delivering abnormal coefficient by combining the time difference value, the position deviation value and the vibration amplitude through a geometric average method.
5. The system for planning and configuring a customized service path based on an AGV site according to claim 3, wherein the specific method for obtaining the interactive anomaly coefficient of the transport process is as follows:
Collecting interactive data of the AGV in the actual conveying process, wherein the interactive data comprise data and time of opening and closing the door and going up and down the elevator each time;
Preprocessing the acquired interaction data, including repeated record removal and missing value processing;
Extracting interactive features which can be used for analysis according to the interactive data, wherein the interactive features comprise duration time of opening and closing each time, frequency of opening and closing the door and frequency of using the elevator;
Carrying out event clustering on the interaction event data based on a K-means clustering algorithm;
Based on the time cluster identification, an abnormal cluster is obtained, and the interactive abnormal coefficient of the transportation process is obtained by calculating the proportion of abnormal events in the abnormal cluster.
6. The system for planning and configuring a customized service path based on an AGV site according to claim 3, wherein the specific method for obtaining the anomaly coefficient of the code marking and labeling is as follows:
Acquiring a history of each code printing and labeling task, recording a history error rate, and calculating an average error rate and an error rate standard deviation;
setting an upper control limit and a lower control limit according to the expected error rate and the error rate standard deviation;
recording the number of abnormal coding cases exceeding the upper control limit and the lower control limit in real time; and comparing and analyzing the abnormal coding false quantity and the total task quantity to obtain coding labeling abnormal coefficients.
7. The system for planning and configuring a customized service path based on an AGV site according to claim 6, wherein the task abnormality determination and the alarm generation specifically include:
Specifically, the abnormality evaluation coefficient is compared with a preset abnormality evaluation threshold, and when the abnormality evaluation coefficient is greater than the preset abnormality evaluation threshold, an alarm is sent.
8. The AGV site-based custom traffic path planning configuration system of claim 7, wherein the cargo data comprises cargo size, cargo type, and cargo initial position; the cargo position data includes available cargo position, pick-up position, and delivery route.
9. The system for planning and configuring a customized service path based on an AGV site according to claim 8, wherein the specific calculation formula of the coded labeling anomaly coefficient is as follows:
In the above, the ratio of/> Labeling abnormal coefficients for coding,/>Index for historic error rate,/>For average error rate,/>Is error rate standard deviation,/>Is the total number of historical error rates,/>Is the historical error rate.
10. The AGV site-based custom traffic path planning configuration system according to claim 9, wherein the specific calculation formula of the pick delivery anomaly coefficient is as follows:
In the above, the ratio of/> For the actual transit time,/>To predict the transit time,/>For the initial position coordinates,/>For the target position coordinates, N is the length of the time series,/>For the vibration frequency at the ith time point in the time series N,/>To obtain abnormal coefficients of delivery.
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