Crown block scheduling method, device, equipment, medium and product

Abstract

The invention discloses a crown block scheduling method, device and equipment, a medium and a product. The method comprises the following steps: acquiring state information, motion information and to-be-processed task information corresponding to each crown block; determining a task allocation strategy according to the state information, the motion information and the to-be-processed task information corresponding to each crown block; and scheduling each crown block according to the task allocation strategy. Through the technical scheme of the invention, the traffic conflict of the crown block at the intersection of a plurality of rails can be solved, the queuing time of the crown block can be reduced, the overall traffic efficiency can be improved, and particularly, the delay caused by the bottleneck phenomenon can be avoided and the smooth production operation can be ensured in the traffic peak period in a complicated scheduling environment.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of overhead crane dispatching, and in particular to an overhead crane dispatching method, device, equipment, medium and product. Background Art

[0002] In the field of modern industry and warehousing logistics, overhead cranes are an important material handling equipment widely used in lifting, transporting and storing goods. With the expansion of production scale and the diversification of operation requirements, it is becoming more and more common for overhead cranes to operate on multiple tracks at the same time. Although this multi-track operation mode has improved production efficiency, it has also brought many new challenges. For example, when multiple overhead cranes are close to intersecting between adjacent tracks, traffic conflicts are likely to occur, resulting in interference between equipment and reduced efficiency. At the same time, traditional scheduling methods are often based on preset schedules, which are difficult to adapt to rapidly changing production needs, thus affecting the rational allocation of resources.

[0003] Most of the existing solutions for overhead crane scheduling focus on static scheduling, but lack flexibility and real-time response capabilities. During peak periods, due to the lack of effective prediction and management mechanisms, overhead cranes often queue up, which affects the production process and causes a waste of time and human resources. In addition, due to the lack of comprehensive data analysis methods, it is difficult to refine scheduling decisions, resulting in low resource utilization and reduced transportation efficiency. More importantly, the current scheduling system usually ignores the dynamic changes in the production environment, which means that when production demand is not stable, the scheduling plan often cannot be adjusted in time, so that the operating efficiency of the overhead crane cannot reach the optimal level. In addition, when multiple overhead cranes are involved in the operation at the same time, the existing technology is also insufficient in priority management, and it is impossible to reasonably balance emergency tasks and routine tasks, which in turn affects the overall production efficiency.

[0004] As the production environment changes, how to implement a quick-response scheduling plan to immediately adapt to new production requirements and operating conditions and achieve dynamic allocation and use of resources has become an urgent problem to be solved. Summary of the invention

[0005] The embodiments of the present invention provide an overhead crane scheduling method, device, equipment, medium and product to solve the traffic conflict of the overhead crane at the intersection of multiple tracks and reduce production stagnation caused by unexpected interference.

[0006] According to one aspect of the present invention, there is provided a method for scheduling an overhead travelling crane, comprising:

[0007] Obtain the status information, motion information and pending task information corresponding to each overhead crane;

[0008] Determine the task allocation strategy according to the status information, motion information and pending task information corresponding to each overhead crane;

[0009] Each overhead crane is scheduled according to the task allocation strategy.

[0010] According to another aspect of the present invention, there is provided an overhead crane dispatching device, the device comprising:

[0011] An acquisition module is used to obtain status information, motion information and pending task information corresponding to each overhead crane;

[0012] A determination module is used to determine a task allocation strategy according to the state information, motion information and pending task information corresponding to each overhead crane;

[0013] The scheduling module is used to schedule each overhead crane according to the task allocation strategy.

[0014] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the overhead crane scheduling method described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the overhead crane scheduling method described in any embodiment of the present invention when executed.

[0019] According to another aspect of the present invention, an embodiment of the present invention further provides a computer program product, the computer program product comprising a computer program, and when the computer program is executed by a processor, the overhead crane scheduling method described in any embodiment of the present invention is implemented.

[0020] The embodiment of the present invention obtains the state information, motion information and pending task information corresponding to each overhead crane, determines the task allocation strategy according to the state information, motion information and pending task information corresponding to each overhead crane, and dispatches each overhead crane according to the task allocation strategy. The technical solution of the present invention can ensure that in a complex scheduling environment, the traffic conflict of the overhead crane at the intersection of multiple tracks is resolved, the queuing time of the overhead crane is reduced, and the overall traffic efficiency is improved, especially during peak traffic hours, to avoid delays caused by bottlenecks and ensure the smooth progress of production operations.

[0021] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 is a flow chart of an overhead crane scheduling method in an embodiment of the present invention;

[0024] Figure 2 is a structural schematic diagram of an overhead crane dispatching device in an embodiment of the present invention;

[0025] Figure 3 It is a structural schematic diagram of an electronic device for implementing the overhead crane dispatching method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0027] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and their meanings are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0029] Embodiment 1

[0030] Figure 1 is a flow chart of a method for dispatching an overhead crane in an embodiment of the present invention. This embodiment is applicable to the case of overhead crane dispatching. The method can be executed by an overhead crane dispatching device in an embodiment of the present invention. The device can be implemented in software and / or hardware, such as Figure 1 As shown, the method specifically comprises the following steps:

[0031] S101, obtaining status information, motion information and pending task information corresponding to each overhead crane.

[0032] In the industrial field, overhead crane usually refers to a kind of lifting machinery, also called traveling crane, bridge crane or crane. It is used for lifting and moving heavy objects in factories, warehouses, ports and other places. Overhead crane can move along fixed tracks and has the ability to lift vertically and move horizontally.

[0033] In this embodiment, the state information corresponding to the overhead crane may be whether the overhead crane is faulty and whether it is performing a task. Exemplarily, the state information of the overhead crane may be, for example, a working state, an idle state, or a fault state. In actual operation, the state information of the overhead crane may be detected by sensors such as cameras installed on the overhead crane and its track.

[0034] In this embodiment, the motion information corresponding to the overhead crane may be information such as the position, speed, acceleration, etc. of the overhead crane during operation. In actual operation, the motion information of the overhead crane may be detected by a speed sensor installed on the overhead crane.

[0035] In this embodiment, the pending task information corresponding to the overhead crane may be related information of the tasks to be executed by the overhead crane. Exemplarily, the pending task information corresponding to the overhead crane may be information such as the number of pending tasks and the priority of the pending tasks. In actual operation, the pending task information of the overhead crane may be directly allocated to each overhead crane by the host computer.

[0036] S102: Determine a task allocation strategy according to the state information, motion information and pending task information corresponding to each overhead crane.

[0037] It should be noted that the task allocation strategy may be a strategy of allocating the pending tasks to each overhead crane and scheduling each overhead crane to execute the pending tasks according to a certain priority order.

[0038] Specifically, a scientific and reasonable priority task allocation strategy is established based on the status information, movement information and pending task information corresponding to each overhead crane. Through the evaluation of different tasks, an efficient balance between emergency tasks and routine tasks is ensured to reduce the risk of production delays and improve overall operational efficiency.

[0039] In some embodiments, an optimization algorithm (such as a genetic algorithm or an ant colony algorithm) can be used to dynamically allocate resources to solve the problem of scheduling multiple overhead cranes at the same time. When a conflict is identified, the operation time and path of the overhead crane can be quickly adjusted to reduce waiting time and energy consumption.

[0040] S103. Dispatching each overhead crane according to the task allocation strategy.

[0041] Specifically, after determining the task allocation strategy, the new scheduling plan is converted into an execution instruction and sent to the corresponding overhead crane to realize the automatic allocation and execution of tasks. During the execution process, the equipment operation status can be monitored in real time. If a fault is found, the emergency plan is immediately initiated, such as automatic parking or rescheduling. During the implementation process, the scheduling situation, equipment status and production data can also be presented through a visual interface, which is convenient for operators to monitor and adjust, ensuring the safety of the overhead crane operation in a complex scheduling environment, avoiding accidents caused by equipment failure or human intervention, and ensuring the smooth progress of production operations.

[0042] The embodiment of the present invention obtains the state information, motion information and pending task information corresponding to each overhead crane, determines the task allocation strategy according to the state information, motion information and pending task information corresponding to each overhead crane, and dispatches each overhead crane according to the task allocation strategy. The technical solution of the present invention can ensure that in a complex scheduling environment, the traffic conflict of the overhead crane at the intersection of multiple tracks is resolved, the queuing time of the overhead crane is reduced, and the overall traffic efficiency is improved, especially during peak traffic hours, to avoid delays caused by bottlenecks and ensure the smooth progress of production operations.

[0043] Optionally, the motion information includes: position information and speed information.

[0044] The task allocation strategy is determined based on the status information, motion information and pending task information corresponding to each overhead crane, including:

[0045] According to the position information and speed information corresponding to each overhead crane, the future operation route of each overhead crane is predicted to obtain the target motion trajectory corresponding to each overhead crane.

[0046] The target motion trajectory may be a route trajectory that the overhead crane is expected to run within a certain period of time in the future when executing the task to be processed.

[0047] In this embodiment, a path planning algorithm (such as A* or Dijkstra) may be used to calculate the optimal driving route of each overhead crane when performing the task to be processed, and obtain the target motion trajectory corresponding to each overhead crane.

[0048] The target intersection point is determined according to the target motion trajectory corresponding to each overhead crane.

[0049] It should be noted that during peak hours, there may be a situation where a traffic conflict occurs when the overhead travelling vehicle approaches to intersect adjacent tracks. The target intersection point may be a track intersection point where a traffic conflict may occur.

[0050] Specifically, machine learning models (such as regression analysis and time series prediction) can be used to predict the future operation status of the overhead travelling vehicle and the traffic volume at the intersection. Once a potential conflict is detected, an alarm can be immediately issued to provide a prompt.

[0051] The task allocation strategy corresponding to the target intersection is determined according to the status information, position information, speed information and pending task information corresponding to each overhead crane.

[0052] Specifically, based on the status information, location information, speed information and pending task information corresponding to each overhead crane, dynamic path planning is achieved, and the route is adjusted in time according to the real-time traffic status and equipment load conditions to reduce the risk of collision between overhead cranes and ensure timely response when multiple tracks intersect, thereby ensuring the safety of equipment and personnel.

[0053] Optionally, the pending task information includes: the number of pending tasks and the priority of the pending tasks.

[0054] Among them, the number of pending tasks can be the number of pending tasks assigned to each overhead crane, and the priority of the pending tasks can be the priority of each pending task. For example, they can be numbered according to level one, level two, etc. Specifically, the priority of level one tasks is greater than that of level two tasks.

[0055] The task allocation strategy corresponding to the target intersection is determined according to the status information, position information, speed information and pending task information corresponding to each overhead crane, including:

[0056] A task list is generated according to the position information, speed information, number of tasks to be processed and priority of tasks to be processed corresponding to each overhead crane.

[0057] In this embodiment, the task list may be related information of each pending task in the form of a list. For example, the rows of the task list may be arranged from high to low according to the priority of the pending tasks, and each row may include information such as the name of the pending task, the crane number corresponding to the task, the state information of the crane, and the estimated completion time of the pending task.

[0058] Specifically, a task list of each overhead crane may be generated according to the priority of each task to be processed, and then a reasonable task allocation strategy may be specified according to the task list.

[0059] The task allocation strategy corresponding to the target intersection is determined based on the task list and the status information corresponding to each overhead crane.

[0060] Specifically, according to the priority of each pending task in the task list, the operation schedule of each overhead crane is adjusted, the operation of some overhead cranes is delayed or accelerated, and the path of the overhead crane that is about to conflict is replanned to ensure that no collision occurs.

[0061] Optionally, the task list includes: the priority and estimated completion time corresponding to each pending task.

[0062] The estimated completion time corresponding to the pending task may be the estimated time required to complete the pending task.

[0063] The estimated completion time is determined by the position information and speed information of the overhead crane corresponding to the task to be processed.

[0064] The status information includes: working status, idle status and fault status.

[0065] It should be noted that the working state may be a state where the overhead crane has no faults and is performing a task, the idle state may be a state where the overhead crane has no faults and is not performing a task, and the fault state may be a state where the overhead crane is damaged or powered off.

[0066] The task allocation strategy corresponding to the target intersection is determined according to the task list and the status information corresponding to each target overhead travelling vehicle, including:

[0067] The dynamic scheduling algorithm is called to generate a task allocation strategy based on the priority, estimated completion time and the overhead crane in the non-fault state of each task to be processed.

[0068] Exemplary task allocation strategies may include: giving priority to tasks with a short estimated completion time to reduce total waiting time; scheduling tasks based on their priority, with high-priority tasks executed first; and adjusting queuing strategies based on real-time feedback to adapt to changing task requirements.

[0069] In this embodiment, the dynamic scheduling algorithm may be, for example, a genetic algorithm or an ant colony algorithm. In the specific implementation process, whether it is a genetic algorithm or an ant colony algorithm, the implementation ideas of the task allocation strategy are basically similar, and can be performed in the following steps:

[0070] Through sensors, the system identifies the task priority and estimated completion time in the current task list, monitors the position, speed, load, and whether the task is being executed of each overhead crane, and calls the selected algorithm (such as genetic algorithm or ant colony algorithm) according to the current task list and the status of each overhead crane to generate a new task allocation plan.

[0071] The embodiment of the present invention uses an intelligent queuing optimization algorithm to replace the traditional manual arrangement method with task scheduling in overhead crane operation. This dynamic optimization can analyze the operation status and production demand in real time, effectively shorten the standby time of the overhead crane, improve the overall production efficiency, and avoid unnecessary delays.

[0072] The embodiments of the present invention can efficiently and intelligently perform dynamic scheduling of overhead crane tasks by using genetic algorithms or ant colony algorithms. These algorithms utilize the intelligent collective behavior of nature, can effectively solve complex task allocation problems, and continuously optimize scheduling strategies through real-time data updates, thereby improving overall production efficiency and resource utilization.

[0073] Optionally, after scheduling each overhead crane according to the task allocation strategy, the following steps are also included:

[0074] Get the current scheduling data.

[0075] The current scheduling data includes at least one of: task execution time, overhead crane waiting time, task completion status, and overhead crane operation status.

[0076] Among them, the task execution time can be the actual completion time of each pending task, the overhead crane waiting time can be the waiting time of each overhead crane in the process of completing the pending task, the task completion status can be the completion status of each pending task, for example, it can be completed or not completed, and the overhead crane operation status can be the status of the overhead crane being in work, idle or faulty.

[0077] The target data set is determined based on the current scheduling data and historical scheduling data.

[0078] It should be noted that the historical dispatching data may be various dispatching data generated by each overhead crane in executing historical tasks, for example, may include at least one of historical task execution time, historical overhead crane waiting time, historical task completion status and historical overhead crane operation status.

[0079] The target data set may be a comprehensive data set formed by combining new data collected in real time with historical data.

[0080] Specifically, during the task execution process, historical scheduling data can be regularly saved, including task execution time, waiting time, task completion status, and equipment operating status, etc. The new data collected in real time can be combined with historical data to form a comprehensive data set to train and update the dynamic scheduling algorithm.

[0081] The dynamic scheduling algorithm is trained and updated based on the target dataset.

[0082] In actual operation, analyze historical scheduling data to find common patterns and trends. For example, there may be a large amount of tasks in certain periods, or equipment may often be delayed in certain situations. Analyze problems in historical scheduling, such as certain types of tasks always timeout or equipment failure, and identify factors that affect scheduling efficiency. Training models based on historical scheduling data can more accurately identify potential conflict risks. Then select the appropriate algorithm and train the decision model using historical scheduling data. For example, by analyzing this data, you can find out which tasks should be prioritized or the most efficient way to allocate resources.

[0083] After that, each time new scheduling data is obtained, the new data is taken into consideration and the dynamic scheduling model is automatically optimized and updated. Using the trained model, a new scheduling plan is automatically generated to make it more in line with actual needs and resource allocation. In the new scheduling plan, the operation of tasks is continuously monitored, such as whether the tasks are completed on time and whether the waiting time is reduced. If changes are found in the operation, they can be adjusted in real time and the best decision can be made based on the current status. These execution results are analyzed and compared with previous data to judge the pros and cons of the new plan to identify which adjustments are effective and which need further improvement. Based on the lessons learned and feedback results, the decision-making model is continuously improved to make scheduling more intelligent and efficient.

[0084] In addition, feedback from operators or managers can be incorporated into the learning process to help identify problems and areas for improvement in actual operations.

[0085] Unlike previous static scheduling systems, the self-learning mechanism of this technical solution can continuously optimize the scheduling strategy based on historical data and real-time feedback. This makes the overhead crane scheduling method more adaptable in long-term operation and can gradually improve the overall efficiency of the production line. In the technical solution of the embodiment of the present invention, the self-learning function automatically optimizes the decision model by collecting and analyzing historical scheduling data, thereby improving scheduling efficiency and accuracy. This process includes data collection, analysis, model training, decision optimization, feedback learning and improvement, ensuring that the scheduling method can continue to adapt to changes and continuously improve performance.

[0086] Optionally, obtain the status information, motion information, and pending task information corresponding to each overhead crane, including:

[0087] Obtain the initial data collected by each sensor installed on each overhead crane and track.

[0088] The sensor includes at least one of an operation status sensor, a position sensor, a speed sensor, a load sensor and a task status sensor.

[0089] In this embodiment, the position sensor may be, for example, GPS and RFID (Radio Frequency Identification), which are used to obtain the position of the overhead crane in real time. The operation status sensor may be used to monitor the speed, acceleration, load and other status of the overhead crane. The task status sensor may track the progress, priority and required time of each pending task.

[0090] The initial data may be various sensor data directly collected by sensors installed on each overhead travelling vehicle and its running track. For example, the initial data may include the speed of the overhead travelling vehicle, acceleration load, and the temperature and humidity of the environment.

[0091] Specifically, sensors such as position, speed, and load are installed on the overhead crane, and sensors are reasonably arranged around the track to ensure data coverage. Each sensor is controlled to collect various data during the operation of the overhead crane in real time (the data collection frequency can be set to one second or shorter to ensure the timeliness and accuracy of the information), such as the position, speed, acceleration, relative position, and other information of the overhead crane.

[0092] The initial data is preprocessed to obtain the state information, motion information and pending task information corresponding to each overhead crane.

[0093] Specifically, the initial data collected by each sensor is cleaned to filter out abnormal or invalid data, such as extreme speed changes or abnormal load conditions, to ensure that the data is accurate and reliable, and then the information from different sensors is integrated to obtain a comprehensive crane status. For example, GPS position and speed sensor data are combined to obtain a more accurate movement status.

[0094] In actual operation, visualization tools can be used to display the status of the overhead crane and production tasks in real time, including position, speed and the number of pending tasks. The above data can be displayed through a visualization interface, and users can view the position, speed and number of pending tasks of the overhead crane in real time.

[0095] The technical solution of the embodiment of the present invention forms a complete overhead crane scheduling solution by combining advanced sensor technology, intelligent algorithms and dynamic scheduling mechanism, providing a more efficient conflict detection and resolution mechanism, and significantly reducing the risk of collision between overhead cranes and vehicles. Through highly automated scheduling and monitoring, the automation and intelligence level of overhead crane operations can be effectively improved, and the dependence on manual scheduling can be reduced, reducing labor costs and error probability. When equipment failure or abnormality is detected, emergency measures can be quickly initiated to ensure production safety. At the same time, diversified production needs are taken into account, and the scheduling strategy can be flexibly adjusted according to different scenarios. This feature enables this method to adapt to various production environments, scales and complexities, and has a wide range of application scenarios.

[0096] As an exemplary description of an embodiment of the present invention, the overhead crane scheduling method is described by taking a scenario in which three overhead cranes transport goods:

[0097] Assume that in a large warehouse logistics center, three overhead cranes (A, B, C) are used to transport goods. Each overhead crane is responsible for a different area, but they may need to intersect during peak hours.

[0098] The specific implementation steps are as follows:

[0099] Position sensors, lidar, temperature and humidity sensors and cameras are installed on the overhead cranes to collect the operating status and environmental data of the three overhead cranes in real time. The collected data is processed, anomaly detection and preprocessing are performed, and algorithms are used to filter out abnormal values, such as reporting speeds or positions that exceed expectations.

[0100] Classification and regression algorithms are used to evaluate the load and operating status of each crane and predict possible failures (such as crane overload). The importance of tasks is evaluated in real time. For example, goods that need to be delivered urgently have priority over routine tasks. If crane A needs maintenance, its task will be reallocated to crane B. Genetic algorithms are used to allocate tasks, taking into account the operating status of each crane to ensure that its load is balanced. The algorithm runs and generates scheduling instructions, and the scheduling results are sent to cranes A, B, and C in real time to perform the assigned handling tasks. After issuing instructions to each crane, the execution status of each crane is monitored. If crane B stops unexpectedly, the emergency plan is immediately activated so that A and C can switch to other tasks to avoid production stagnation.

[0101] After each task is completed, the crane will provide feedback on the status, update the task completion status, and accumulate new learning data. It will record scheduling data, analyze the efficiency and errors of task completion, automatically optimize the decision-making model, and improve scheduling accuracy.

[0102] During this process, the operator monitors the crane status, task allocation and production data in real time through a visual interface. Each user needs to authenticate before accessing, and sensitive data is protected by encryption technology to prevent external attacks.

[0103] Specific scenario description: During a specific peak period, three overhead cranes handle multiple tasks at the same time. For example, A needs to move the goods to Area X, B needs to pick up the goods at the intersection, and C accepts an emergency dispatch task. The system monitors the operating status of each overhead crane in real time, evaluates the priority and urgency of the current task, and ensures the optimal work efficiency of A, B, and C. Implement an advanced queue management mechanism to ensure that high-priority tasks are processed first. For example, at the intersection, C is given priority to pass when it is an urgent task. If overhead cranes A and B may conflict at the intersection (for example, the expected time overlaps), the current operating status must be calculated in real time and an alarm must be issued in advance. Automatically adjust the path for overhead crane B, passing through different tracks or slightly delayed execution to ensure safety.

[0104] After each dispatch operation is completed, the dispatch efficiency, time and completion status will be analyzed, and the original dispatch strategy will be adjusted accordingly. For example, if the overhead crane C always has a dispatch delay in certain situations, the future dispatch time window will be automatically adjusted to prepare in advance.

[0105] The technical solution of the embodiment of the present invention integrates a dynamic scheduling algorithm and a multi-level priority decision-making mechanism to provide intelligent support for the scheduling process. Traditional scheduling often relies on manual experience, while the embodiment of the present invention uses big data and machine learning to make the decision-making process more accurate and efficient, and can quickly adapt to the ever-changing production environment. Through the above implementation plan, real-time data analysis, intelligent scheduling mechanism, conflict detection and feedback learning are combined to effectively improve the working efficiency and safety of the overhead crane, so that each overhead crane can achieve efficient operation in a complex logistics environment.

[0106] Embodiment 2

[0107] Figure 2 is a schematic diagram of the structure of an overhead crane dispatching device in an embodiment of the present invention. This embodiment is applicable to the case of overhead crane dispatching. The device can be implemented in software and / or hardware. The device can be integrated in any device that provides the function of overhead crane dispatching, such as Figure 2 As shown, the overhead crane dispatching device specifically includes: an acquisition module 201 , a determination module 202 and a dispatching module 203 .

[0108] The acquisition module 201 is used to acquire the state information, motion information and pending task information corresponding to each overhead crane;

[0109] A determination module 202 is used to determine a task allocation strategy according to the state information, motion information and pending task information corresponding to each overhead crane;

[0110] The scheduling module 203 is used to schedule each overhead crane according to the task allocation strategy.

[0111] Optionally, the motion information includes: position information and speed information;

[0112] The determination module 202 includes:

[0113] A prediction unit, used to predict the future running route of each overhead crane according to the position information and speed information corresponding to each overhead crane, and obtain the target motion trajectory corresponding to each overhead crane;

[0114] A first determining unit is used to determine a target intersection point according to a target motion trajectory corresponding to each overhead crane;

[0115] The second determining unit is used to determine the task allocation strategy corresponding to the target intersection according to the state information, position information, speed information and to-be-processed task information corresponding to each overhead crane.

[0116] Optionally, the pending task information includes: the number of pending tasks and the priority of the pending tasks;

[0117] The second determining unit includes:

[0118] A generating subunit, used for generating a task list according to the position information, speed information, number of tasks to be processed and priority of the tasks to be processed corresponding to each overhead crane;

[0119] The determination subunit is used to determine the task allocation strategy corresponding to the target intersection according to the task list and the status information corresponding to each overhead crane.

[0120] Optionally, the task list includes: the priority and estimated completion time corresponding to each task to be processed, and the estimated completion time is determined by the position information and speed information of the overhead crane corresponding to the task to be processed; the status information includes: working status, idle status and fault status;

[0121] The determining subunit is specifically used for:

[0122] The dynamic scheduling algorithm is called to generate a task allocation strategy based on the priority, estimated completion time and the overhead crane in the non-fault state of each task to be processed.

[0123] Optionally, the device is also used for:

[0124] Acquire current scheduling data, wherein the current scheduling data includes at least one of: task execution time, overhead crane waiting time, task completion status, and overhead crane operation status;

[0125] Determine a target data set according to the current scheduling data and the historical scheduling data;

[0126] The dynamic scheduling algorithm is trained and updated based on the target data set.

[0127] Optionally, the acquisition module 201 is specifically used for:

[0128] Acquire initial data collected by sensors installed on each overhead crane and track, wherein the sensors include: at least one of an operation status sensor, a position sensor, a speed sensor, a load sensor, and a task status sensor;

[0129] The initial data is preprocessed to obtain state information, motion information and task information to be processed corresponding to each overhead crane.

[0130] The above-mentioned product can execute the overhead crane dispatching method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0131] Embodiment 3

[0132] Figure 3 A schematic diagram of the structure of an electronic device 30 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0133] like Figure 3 As shown, the electronic device 30 includes at least one processor 31, and a memory connected to the at least one processor 31, such as a read-only memory (ROM) 32, a random access memory (RAM) 33, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 31 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 32 or the computer program loaded from the storage unit 38 to the random access memory (RAM) 33. In the RAM 33, various programs and data required for the operation of the electronic device 30 can also be stored. The processor 31, the ROM 32, and the RAM 33 are connected to each other through a bus 34. An input / output (I / O) interface 35 is also connected to the bus 34.

[0134] A number of components in the electronic device 30 are connected to the I / O interface 35, including: an input unit 36, such as a keyboard, a mouse, etc.; an output unit 37, such as various types of displays, speakers, etc.; a storage unit 38, such as a disk, an optical disk, etc.; and a communication unit 39, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 39 allows the electronic device 30 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0135] The processor 31 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 31 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 31 executes the various methods and processes described above, such as the overhead crane scheduling method:

[0136] Obtain the status information, motion information and pending task information corresponding to each overhead crane;

[0137] Determine the task allocation strategy according to the status information, motion information and pending task information corresponding to each overhead crane;

[0138] Each overhead crane is scheduled according to the task allocation strategy.

[0139] In some embodiments, the overhead crane dispatching method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 38. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 30 via the ROM 32 and / or the communication unit 39. When the computer program is loaded into the RAM 33 and executed by the processor 31, one or more steps of the overhead crane dispatching method described above may be performed. Alternatively, in other embodiments, the processor 31 may be configured to execute the overhead crane dispatching method in any other appropriate manner (e.g., by means of firmware).

[0140] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0141] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0142] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0143] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0144] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0145] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0146] In one embodiment, the embodiment of the present invention further includes a computer program product, the computer program product includes a computer program, and when the computer program is executed by a processor, the overhead crane scheduling method of any embodiment of the present invention is implemented.

[0147] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0148] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0149] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for dispatching an overhead crane, characterized in that: include: Obtain the status information, motion information and pending task information corresponding to each overhead crane; Determine the task allocation strategy according to the status information, motion information and pending task information corresponding to each overhead crane; Each overhead crane is scheduled according to the task allocation strategy.

2. The method according to claim 1, characterized in that The motion information includes: position information and speed information; The task allocation strategy is determined based on the status information, motion information and pending task information corresponding to each overhead crane, including: According to the position information and speed information corresponding to each overhead crane, the future running route of each overhead crane is predicted to obtain the target motion trajectory corresponding to each overhead crane; Determine the target intersection point according to the target motion trajectory corresponding to each overhead crane; The task allocation strategy corresponding to the target intersection is determined according to the state information, position information, speed information and pending task information corresponding to each overhead crane.

3. The method according to claim 2, characterized in that The pending task information includes: the number of pending tasks and the priority of the pending tasks; Determine the task allocation strategy corresponding to the target intersection point according to the state information, position information, speed information and pending task information corresponding to each overhead crane, including: Generate a task list according to the position information, speed information, number of tasks to be processed and priority of tasks to be processed corresponding to each overhead crane; The task allocation strategy corresponding to the target intersection is determined according to the task list and the status information corresponding to each overhead crane.

4. The method according to claim 3, characterized in that The task list includes: the priority and estimated completion time corresponding to each pending task, wherein the estimated completion time is determined by the position information and speed information of the overhead crane corresponding to the pending task; the status information includes: working status, idle status and fault status; Determining a task allocation strategy corresponding to the target intersection point according to the task list and the status information corresponding to each target overhead travelling vehicle includes: The dynamic scheduling algorithm is called to generate a task allocation strategy based on the priority, estimated completion time and the overhead crane in the non-fault state of each task to be processed.

5. The method according to claim 1, characterized in that After scheduling each overhead travelling crane according to the task allocation strategy, the method further includes: Acquire current scheduling data, wherein the current scheduling data includes at least one of: task execution time, overhead crane waiting time, task completion status, and overhead crane operation status; Determine a target data set according to the current scheduling data and the historical scheduling data; The dynamic scheduling algorithm is trained and updated based on the target data set.

6. The method according to claim 1, characterized in that Obtain the status information, motion information, and pending task information corresponding to each overhead crane, including: Acquire initial data collected by sensors installed on each overhead crane and track, wherein the sensors include: at least one of an operation status sensor, a position sensor, a speed sensor, a load sensor, and a task status sensor; The initial data is preprocessed to obtain state information, motion information and task information to be processed corresponding to each overhead crane.

7. A crane dispatching device, characterized in that: include: An acquisition module is used to obtain status information, motion information and pending task information corresponding to each overhead crane; A determination module is used to determine a task allocation strategy according to the state information, motion information and pending task information corresponding to each overhead crane; The scheduling module is used to schedule each overhead crane according to the task allocation strategy.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the overhead crane dispatching method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the overhead crane scheduling method according to any one of claims 1 to 6 when executed.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the overhead travelling vehicle dispatching method according to any one of claims 1 to 6 is implemented.

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