Task scheduling method and system for roadway stacker

Abstract

The invention relates to the technical field of tunnel stacker task scheduling, in particular to a tunnel stacker task scheduling method and system, and the method comprises the following steps: registering public resources; allocating a task for the stacker, if a task execution path needs to pass through the public resource, estimating a time period of occupying the public resource by the stacker, and applying for a time token of the public resource from the coordination module; dynamically distributing a time token, and if the stacker obtains the time token, adjusting the running speed of the stacker; judging whether the stacker cannot use the obtained time token on time or not; if it is judged that the stacker cannot use the obtained time token on time, the obtained time token of the stacker is recovered immediately; planning a detrapping path for the stacker; high-priority tasks which are not completed by the stacker are distributed to other stackers; and redistributing the released time token to other stackers which have the highest priority and can be used on time in the waiting queue. The utilization rate of public resources is optimized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of roadway stacker task scheduling, and particularly relates to a roadway stacker task scheduling method and system. BACKGROUND

[0002] In modern automated warehouses, roadway stackers are the key equipment for efficient storage and retrieval of goods. In order to cope with the growing business demand and improve operational efficiency, warehouses usually deploy multiple stackers and gradually introduce more flexible operation modes, such as allowing stackers to cross between different aisles. However, this complex operating environment also brings unprecedented scheduling challenges, especially in the face of limited public resources and unpredictable emergencies. How to ensure that stackers complete tasks efficiently and stably has become a problem to be solved. SUMMARY

[0003] The present application aims to solve the above-mentioned problems, and provides a roadway stacker task scheduling method and system.

[0004] The present application adopts the following technical solutions:

[0005] A roadway stacker task scheduling method, the method comprising the following steps:

[0006] Registering public resources and managing the state information of the public resources;

[0007] Allocating tasks to the stackers and calculating the task execution path of the stackers according to the tasks, if the task execution path needs to pass through the public resources, estimating the time period of the stackers occupying the public resources, and applying for time tokens of the public resources to the coordination module;

[0008] The coordination module dynamically allocates time tokens according to the task priority of the stackers, the availability of the public resources, the predicted arrival time of the stackers and the overall system load, if the stackers obtain the time tokens, adjusting the running speed of the stackers according to the time specified by the time tokens;

[0009] Continuously monitoring the running state of the stackers, and the environmental conditions of the main aisles and temporary work aisles of the stackers, judging whether the stackers cannot use the obtained time tokens on time according to the running state and the environmental conditions;

[0010] If it is judged that the stackers cannot use the obtained time tokens on time, immediately recycling the obtained time tokens of the stackers, and releasing the time tokens to the public resource pool;

[0011] According to the task priority of the stackers, planning an escape path for the stackers, and reapplying time tokens for the public resources required along the escape path;

[0012] offloading the unfinished high-priority task of the stacker to other stackers, and applying a time token for the offloaded task;

[0013] redistributing the released time token to other stackers in the waiting queue with the highest priority and capable of using the public resource on time.

[0014] By the technical solution, the application provides an intelligent and dynamic tunnel stacker task scheduling method, which can effectively cope with complex and variable warehouse operating environments, especially when the stacker encounters an emergency situation and cannot use the public resource on time. The method can quickly respond through a series of measures such as recycling time tokens, planning an escape path, offloading high-priority tasks, and redistributing time tokens, thereby minimizing the impact on the overall system efficiency, ensuring the timely completion of high-priority tasks, and optimizing the utilization of public resources.

[0015] Further, the steps of obtaining the availability of the public resource and the predicted arrival time of the stacker include:

[0016] Fusing data of the wheel encoder, the inertial measurement unit of the stacker, and the positioning beacon in the tunnel to obtain the position and speed of the stacker;

[0017] The stacker on-board controller sends an occupancy state query request to the public resource controller to obtain the physical occupancy state of the public resource;

[0018] The stacker on-board controller predicts the availability of the public resource by combining the physical occupancy state of the public resource, the average processing time of the public resource, and real-time monitoring of the sensor at the entrance of the public resource;

[0019] According to the position and speed of the stacker, the distance from the stacker to the entrance of the public resource is calculated to obtain the predicted arrival time of the stacker;

[0020] The stacker on-board controller and the coordination module communicate to report the predicted arrival time of the stacker and the availability of the public resource.

[0021] Further, the step of calculating the predicted arrival time of the stacker includes:

[0022] The coordination module receives real-time position and real-time speed data provided by the stacker on-board positioning system;

[0023] The coordination module performs real-time filtering processing on the real-time position and real-time speed data to obtain the position and speed of the stacker;

[0024] According to the position of the stacker, the pre-stored warehouse map, and the tunnel topology information, the distance from the stacker to the entrance of the public resource is obtained;

[0025] The coordination module calculates the estimated arrival time of the stacker according to the position and speed of the stacker, in combination with the distance from the stacker to the common resource entrance, using a path tracking algorithm and a kinematics model.

[0026] Further, the step of filtering the real-time position and real-time speed data in real time to obtain the position and speed of the stacker comprises:

[0027] The coordination module selects a filtering algorithm to filter the real-time position and real-time speed data to obtain filtered position and speed estimates.

[0028] The filtered position and speed estimates are the position and speed of the stacker.

[0029] Further, the step of obtaining the distance from the stacker to the common resource entrance according to the position of the stacker, the pre-stored warehouse map and the lane topology information comprises:

[0030] According to the position of the stacker, the pre-stored warehouse map and the lane topology information, the stacker calculates the optimal path from the stacker to the common resource entrance using a path planning algorithm.

[0031] The distance from the stacker to the common resource entrance is obtained according to the optimal path from the stacker to the common resource entrance.

[0032] Further, the step of distributing the uncompleted high-priority task of the stacker to other stackers comprises:

[0033] The available state of the stacker is continuously monitored, including battery power, device health state and environmental conditions of the lane where the stacker is located.

[0034] According to the task priority and task type of the stacker, a plurality of stackers that can replace tasks are preliminarily screened out.

[0035] For each preliminarily screened stacker, based on its latest available state, its current available capacity and task load are evaluated, and potential risks that may occur during execution of a new task are predicted.

[0036] According to the predicted potential risks, the candidate priority of the stacker is adjusted or the stacker is removed.

[0037] Before the replacement stacker starts executing the task, an available state query request is sent again, and the environmental conditions of the lane where the replacement stacker is located are monitored again.

[0038] If the replacement stacker's available state is found to have changed again, the task allocation is cancelled and the task distribution process is restarted.

[0039] Further, the step of determining whether the stacker cannot use the obtained time token on time comprises:

[0040] collecting operation data of the stacker and environment data of a tunnel where the stacker is located;

[0041] analyzing performance trend of the stacker according to the operation data of the stacker;

[0042] analyzing change trend of the tunnel environment according to the environment data of the tunnel where the stacker is located;

[0043] matching the performance trend of the stacker, the change trend of the tunnel environment and information of the time token obtained by the stacker, to determine whether the stacker cannot use the obtained time token on time;

[0044] if it is determined that the stacker cannot use the obtained time token on time, triggering a warning;

[0045] starting an intervention process, the intervention process including sending an instruction to the stacker, or sending a time token adjustment request to a coordination module;

[0046] if the stacker still cannot use the obtained time token on time after the intervention, immediately recycling the obtained time token of the stacker, and releasing the time token to a public resource pool.

[0047] Further, the step of reassigning the released time token to other stackers with the highest priority and capable of using on time in the waiting queue includes:

[0048] selecting stackers with the highest priority and capable of reaching within the available time window of the released time token from the waiting queue as preliminary candidate stackers;

[0049] sending a pre-assignment token notification to the preliminary candidate stackers, the pre-assignment token notification containing a public resource ID, an available time window and a confirmation response deadline of the released time token;

[0050] after the preliminary candidate stacker on-board controller receives the pre-assignment token notification, performing self-state self-checking, including checking battery power, drive system health status and the latest accuracy report of the vehicle positioning system;

[0051] based on the results of the self-state self-checking, the preliminary candidate stacker on-board controller pre-rehearses the path from the current location to the public resource and continues to perform subsequent tasks;

[0052] during the path pre-rehearsal process, the preliminary candidate stacker on-board controller sends a query request to the path-required resources on the path of the subsequent tasks of the preliminary candidate stacker, to obtain the real-time availability of the path-required resources;

[0053] The preliminary candidate stacker on-board controller calculates the preliminary candidate stacker's estimated arrival time at the pre-allocated common resource according to the path rehearsal result, and evaluates whether the preliminary candidate stacker can arrive within the available time window of the released time token;

[0054] The preliminary candidate stacker on-board controller evaluates the time token application success rate on the path of the preliminary candidate stacker's subsequent task in combination with the real-time availability of the path-required resources;

[0055] The preliminary candidate stacker on-board controller generates a response according to the evaluation result, and the response includes a time token acceptance response or a time token rejection response;

[0056] The coordination module receives the responses of the preliminary candidate stackers;

[0057] The coordination module waits for the responses of all the preliminary candidate stackers before the response deadline;

[0058] If the coordination module receives a time token acceptance response and does not receive any other conflicting time token acceptance response before the response deadline, the time token is finally allocated to the preliminary candidate stacker;

[0059] If all the preliminary candidate stackers reject the time token response, or no time token acceptance response is received before the deadline, the time token is released back to the common resource pool, and the next stacker with the highest priority is selected from the waiting queue to repeat the pre-allocation and response process.

[0060] Further, the dynamic allocation of the time token further includes the following steps:

[0061] The coordination module sends an instruction to the stacker that obtains the time token, and the instruction includes the time specified by the time token;

[0062] The stacker adjusts the running speed of the stacker according to the time specified by the time token.

[0063] Through the technical solution, the application can directly send an instruction to the stacker through the coordination module, so that the running speed is adjusted according to the time specified by the time token, thereby realizing fine control of the stacker running, ensuring that the stacker can accurately use the common resource on time, and further improving the scheduling efficiency and system collaboration.

[0064] The application also discloses a roadway stacker task scheduling system applied to the roadway stacker task scheduling method, and the system comprises:

[0065] A management module is configured to register a common resource and manage state information of the common resource;

[0066] The planning module allocates tasks to the stacker, calculates a task execution path of the stacker according to the tasks, estimates a time period of occupation of the common resource by the stacker if the task execution path needs to pass through the common resource, and applies for a time token of the common resource to the coordination module;

[0067] The coordination module dynamically allocates the time token according to the task priority of the stacker, the availability of the common resource, the predicted arrival time of the stacker and the overall system load, and adjusts the running speed of the stacker according to the time specified by the time token if the stacker obtains the time token;

[0068] The monitoring module continuously monitors the running state of the stacker and the environmental conditions of the main roadway and the temporary work roadway of the stacker, and judges whether the stacker cannot use the obtained time token on time according to the running state and the environmental conditions;

[0069] The release module recovers the time token obtained by the stacker and releases the time token to the common resource pool if it is judged that the stacker cannot use the obtained time token on time;

[0070] The escape module plans an escape path for the stacker according to the task priority of the stacker, and re-applies for a time token for the common resource required along the escape path;

[0071] The shunting module shunts the high-priority task not completed by the stacker to other stackers, and applies for a time token for the shunted task;

[0072] The allocation module re-allocates the released time token to other stackers in the waiting queue with the highest priority and capable of using on time.

[0073] Through the technical scheme, the application provides a functionally complete roadway stacker task scheduling system, which realizes intelligent management of the whole process of common resource, task planning, time token coordination, stacker state monitoring, exception handling, escape, task shunting and resource re-allocation through modular design, and can effectively support the implementation of the above scheduling method.

[0074] The application significantly improves the overall operation efficiency, system stability and decision-making ability in response to emergencies.

[0075] In order to further understand the features and technical contents of the application, please refer to the following detailed description and drawings of the application. However, the provided drawings are only used for reference and illustration, and are not used to limit the application. BRIEF DESCRIPTION OF DRAWINGS

[0076] Figure 1 The method flowchart of the roadway stacker task scheduling method of the application. DETAILED DESCRIPTION

[0077] The advantages and effects of the present application can be understood by those skilled in the art from the disclosure of the specification. The present application can be implemented or applied by other different embodiments, and various modifications and changes can be made to the details in the specification based on different views and applications without departing from the spirit of the present application. In addition, the drawings of the present application are only simple schematic illustrations and are not drawn according to the actual size, and it is declared in advance. The following embodiments will further illustrate the related technical content of the present application, but the disclosed content is not used to limit the protection scope of the present application.

[0078] The present embodiment provides a kind of roadway stacker task scheduling method and system, combined with Figure 1 As shown in the figure.

[0079] Reference Figure 1 A kind of roadway stacker task scheduling method, the method comprises the following steps:

[0080] Register public resources, and manage the state information of public resources;

[0081] Assign tasks for stacker, and calculate the task execution path of stacker according to task, if task execution path needs to pass through public resources, then estimate the time period of stacker occupying public resources, and apply for the time token of public resources to coordination module;

[0082] Coordination module dynamically allocates time token according to the task priority of stacker, the availability of public resources, the predicted arrival time of stacker and overall system load, if stacker obtains time token, then adjust the running speed of stacker according to the time specified by time token;

[0083] Continuously monitor the running state of stacker, and the environmental condition of main roadway and temporary work roadway of stacker, according to running state and environmental condition, judge whether stacker can use the time token obtained in time;

[0084] If it is judged that stacker can not use the time token obtained in time, then immediately recycle the time token obtained by stacker, and release time token to public resource pool;

[0085] According to the task priority of stacker, plan escape path for stacker, and reapply time token for the public resources required along the escape path;

[0086] Divert the high-priority task not completed by stacker to other stacker, and apply time token for diverted task;

[0087] Reallocate the released time token to other stacker in waiting queue with the highest priority and can use in time.

[0088] Where "public resources" refer to infrastructure or areas in the automated warehouse that multiple stackers may share, such as transfer lanes, intersections, charging stations, maintenance areas, etc. These resources can only be occupied by one or a limited number of stackers at a certain time, so coordination management is needed to avoid conflicts and improve utilization.

[0089] A "time token" is a virtual permission certificate that represents a stacker's right to occupy a certain public resource within a specific time period. When a stacker needs to pass through or use a public resource, it must apply for and obtain the corresponding time token from the coordination module. The time token usually contains information such as the ID of the public resource, the allowed time window (start time and end time), etc.

[0090] The "coordination module" is the core component of the entire scheduling system, responsible for receiving stacker applications for public resource time tokens, and dynamically allocating or recycling time tokens based on pre-set scheduling strategies, real-time system status, and stacker priority.

[0091] "Stacker task priority" is used to distinguish the importance and urgency of different tasks. High-priority tasks usually need to be executed first and have higher weights in resource allocation.

[0092] "Availability of public resources" refers to whether a public resource will be in an idle state within a certain time period in the future and can be occupied by a stacker.

[0093] "Stacker's estimated arrival time" refers to the estimated time for a stacker to arrive at the entrance of a certain public resource from the current location according to the planned path.

[0094] "Overall system load" reflects the task volume, resource occupation, and potential congestion risk of all stackers in the current warehouse, which is an important reference for the coordination module to make decisions.

[0095] This method is usually deployed in the central scheduling system or distributed control system of an automated warehouse, and through communication with the stacker on-board controller, public resource controller, and various sensors, it realizes real-time monitoring and scheduling of stackers and public resources.

[0096] First, during the system initialization phase, public resources need to be registered and their state information managed. Public resources can be any shared area or device in the warehouse, such as transfer lanes, intersections, charging stations, etc. Managing the state information of public resources can include their current occupancy status, estimated idle time, maintenance schedule, etc. For example, sensors can be deployed at the entrance and exit of public resources to monitor their occupancy in real time, and this information can be aggregated into a central database for management. In addition, static attributes of public resources (such as capacity, type) can also be entered into the system through manual input or preset configuration.

[0097] Secondly, tasks are assigned to the stacker, and the task execution path of the stacker is calculated according to the task. If the task execution path needs to pass through a public resource, the time period of the stacker occupying the public resource is estimated, and a time token of the public resource is applied to the coordination module. Task assignment can be based on various strategies, such as shortest path, minimum energy consumption or highest priority. Once the task is assigned to the stacker, its on-board controller or central dispatching system will calculate an optimal task execution path based on the warehouse map and lane topology information. If this path contains a public resource, the system will estimate the time period of the stacker occupying the public resource based on factors such as the speed of the stacker, the length of the public resource, etc. Then, the stacker will send a time token application to the coordination module, which contains information such as public resource ID, estimated occupation time period, and task priority of the stacker.

[0098] Thirdly, the coordination module dynamically allocates time tokens based on the task priority of the stacker, the availability of the public resource, the estimated arrival time of the stacker, and the overall system load. If the stacker obtains a time token, it adjusts its running speed according to the time specified in the time token. After receiving the time token application, the coordination module will make decisions by considering multiple factors. For example, if a high-priority task needs to pass through a public resource that has been occupied by a low-priority task within the estimated time period, the coordination module may choose to reclaim the time token of the low-priority task and allocate it to the high-priority task. The coordination module can also adjust the estimated arrival time of the stacker based on the availability of the public resource to avoid conflicts. Once the stacker obtains a time token, the coordination module will send instructions to the stacker to inform it of the time window allocated to it. The on-board controller of the stacker will adjust its running speed according to this time window.

[0099] Further, the operating status of the stacker and the environmental conditions of the main lane and the temporary work lane of the stacker are continuously monitored, and according to the operating status and the environmental conditions, it is determined whether the stacker cannot use the time token obtained on time. The monitoring can be achieved in various ways, for example, the stacker on-board sensor can report its position, speed, battery power, equipment health status and other operating data in real time. At the same time, the environmental sensors deployed in the lane can monitor the temperature, humidity, obstacles and other environmental conditions. The coordination module will continuously collect these data and match them with the time token information obtained by the stacker. For example, if the speed of the stacker abnormally decreases due to equipment failure, or its main lane is blocked, the coordination module will determine that the stacker may not be able to use the time token obtained on time.

[0100] If it is determined that the stacker cannot use the time token obtained on time, the time token obtained by the stacker is immediately recovered, and the time token is released to the public resource pool. When the coordination module determines that the stacker cannot use the time token obtained on time, it will take immediate action. For example, the coordination module will send an instruction to the stacker to cancel its occupation of the public resource, and mark the time token as available and put it back into the public resource pool.

[0101] According to the task priority of the stacker, a escape path is planned for the stacker, and time tokens are re-applied for the public resources required along the escape path. Once the stacker is determined to be unable to use the time token on time, it usually means that it has encountered some obstacles or failures. At this time, the coordination module will plan an escape path for the stacker according to its task priority and current position. For example, if the stacker is trapped in a temporary work lane, the coordination module may plan a path to return to its main lane or go to a repair area. When planning the escape path, the coordination module will consider the public resources required along the way and re-apply time tokens for these resources to ensure that the stacker can successfully escape.

[0102] Divert the high-priority tasks of the stacker to other stackers and apply time tokens for the diverted tasks. In order to minimize the impact of the emergency on the overall system efficiency, the coordination module will identify the high-priority tasks that are not completed on the trapped stacker. Then, according to the available state, task load and position of other stackers, the coordination module will select suitable stackers to take over these tasks. Once the tasks are diverted, the coordination module will apply the corresponding time tokens for the new execution stackers to ensure that the tasks can be completed as soon as possible.

[0103] The released time token is re-allocated to other stacker with the highest priority and the ability to use it on time in the waiting queue. When a time token is recycled and released to the public resource pool, the coordination module checks whether there are other stackers in the waiting queue that are applying for the public resource. The coordination module will preferentially select the stacker with the highest priority and the ability to arrive and use within the available time window of the time token, and re-allocate the time token to it.

[0104] The steps of obtaining the availability of the public resource and the predicted arrival time of the stacker include:

[0105] Fusing the data of the wheel encoder, the inertial measurement unit of the stacker and the positioning beacon in the aisle to obtain the position and speed of the stacker;

[0106] The stacker on-board controller sends an occupancy state query request to the public resource controller to obtain the physical occupancy state of the public resource;

[0107] The stacker on-board controller combines the physical occupancy state of the public resource, the average processing time of the public resource and the real-time monitoring of the sensor at the entrance of the public resource to predict the availability of the public resource;

[0108] According to the position and speed of the stacker, the distance from the stacker to the entrance of the public resource, the predicted arrival time of the stacker is calculated;

[0109] The stacker on-board controller and the coordination module communicate to report the predicted arrival time of the stacker and the availability of the public resource.

[0110] Among them, the fusion of the data of the wheel encoder, the inertial measurement unit of the stacker and the positioning beacon in the aisle aims to improve the accuracy and robustness of the position and speed information of the stacker through multi-sensor data fusion technology. The wheel encoder is used to provide the relative displacement information of the stacker, the inertial measurement unit provides the attitude and acceleration information of the stacker, and the positioning beacon in the aisle is configured to provide absolute position calibration points. These different sources of data are processed in real time to obtain the accurate real-time position and speed of the stacker.

[0111] Further, the stacker on-board controller is configured to send an occupancy state query request to the public resource controller, which aims to obtain the current physical occupancy state of the public resource. The physical occupancy state of the public resource refers to information such as whether the public resource has been occupied by other devices, the expected occupation time, etc. that directly reflects its current usage.

[0112] On this basis, the stacker on-board controller combines the acquired public resource physical occupancy state, the preset public resource average processing time, and the real-time monitoring data of the sensor at the public resource entrance to predict the future availability of the public resource. The real-time monitoring sensor can include an infrared sensor, a laser radar, or a visual sensor, etc., for detecting whether other stackers or obstacles are about to enter or leave the public resource area, so as to more accurately predict the availability thereof.

[0113] In addition, according to the current position and speed of the stacker, and in combination with the distance from the stacker to the public resource entrance, the estimated arrival time of the stacker can be calculated. The distance can be calculated through the pre-stored warehouse map and the lane topology information.

[0114] Finally, the stacker on-board controller communicates with the coordination module to report the calculated estimated arrival time of the stacker and the predicted availability of the public resource to the coordination module, so that the coordination module performs subsequent dynamic allocation of time tokens.

[0115] The step of calculating the estimated arrival time of the stacker includes:

[0116] The coordination module receives real-time position and real-time speed data provided by the stacker on-board positioning system;

[0117] The coordination module performs real-time filtering processing on the real-time position and real-time speed data to obtain the position and speed of the stacker;

[0118] According to the position of the stacker, the pre-stored warehouse map, and the lane topology information, the distance from the stacker to the public resource entrance is obtained;

[0119] The coordination module calculates the estimated arrival time of the stacker according to the position and speed of the stacker, in combination with the distance from the stacker to the public resource entrance, using a path tracking algorithm and a kinematics model.

[0120] Among them, the coordination module is the core of the entire scheduling system, responsible for receiving data from the stacker on-board positioning system. The stacker on-board positioning system is usually composed of multiple sensors, such as wheel encoders, inertial measurement units, and positioning beacons within the lane, which work together to provide real-time position and real-time speed data of the stacker. These raw data may contain noise or errors, therefore, the coordination module needs to perform real-time filtering processing on these real-time position and real-time speed data. Real-time filtering processing aims to remove noise in the data, improve the accuracy and stability of position and speed estimation, for example, Kalman filtering, extended Kalman filtering, or particle filtering algorithms can be used. Through filtering processing, more accurate position and speed of the stacker can be obtained.

[0121] Further, to calculate the distance from the stacker to the common resource entrance, the coordination module utilizes the pre-stored warehouse map and aisle topology information. The warehouse map provides the physical layout of the warehouse, including the geometry of the aisles, intersections, locations of common resources, etc. The aisle topology information describes the connection relationships and traffic rules between aisles. Combined with the current accurate position of the stacker, the coordination module can calculate the optimal path from the current position of the stacker to the target common resource entrance by a path planning algorithm (such as A* algorithm, Dijkstra algorithm or RRT algorithm), and thus obtain the distance of the path.

[0122] Finally, the coordination module calculates the predicted arrival time of the stacker according to its position and speed, combined with the calculated distance from the stacker to the common resource entrance, using a path tracking algorithm and a kinematic model. The path tracking algorithm is used to predict the motion trajectory of the stacker on the predetermined path, while the kinematic model describes the motion characteristics of the stacker at different speeds and accelerations. By considering these factors comprehensively, the time required for the stacker to reach the common resource entrance can be accurately predicted.

[0123] The steps of the coordination module for real-time filtering of real-time position and real-time speed data to obtain the position and speed of the stacker include:

[0124] The coordination module selects a filtering algorithm to filter the real-time position and real-time speed data to obtain filtered position and speed estimates.

[0125] The filtered position and speed estimates are the position and speed of the stacker.

[0126] The filtering algorithm can be understood as a mathematical processing method, whose purpose is to extract useful information from raw data containing noise and to smooth the data, thereby improving the accuracy and reliability of the data. In practical applications, the filtering algorithm can be selected according to the specific application scenario and data characteristics, for example, Kalman filtering, extended Kalman filtering, unscented Kalman filtering, particle filtering or moving average filtering, etc. By filtering the real-time position and real-time speed data, the influence of sensor noise, measurement errors and other interference factors on the data can be effectively removed.

[0127] Specifically, the filtering algorithm can predict the position and speed at the current time according to the motion model of the stacker and the sensor measurement model, and correct the prediction results combined with the actual measurement data, thereby obtaining an optimal estimate. This process can effectively suppress random noise and systematic errors in the data, ensuring that the obtained position and speed data have higher accuracy and stability.

[0128] The application further proposes that the step of deriving the distance of the stacker to the common resource entrance according to the position of the stacker, the pre-stored warehouse map and the aisle topology information comprises:

[0129] According to the position of the stacker, the pre-stored warehouse map and the aisle topology information, the stacker uses a path planning algorithm to calculate the optimal path of the stacker to the common resource entrance;

[0130] According to the optimal path of the stacker to the common resource entrance, the distance of the stacker to the common resource entrance is derived.

[0131] Specifically, the pre-stored warehouse map can be understood as a digital map containing detailed information such as warehouse layout, obstacles, passage width, common resource entrance position, etc. This map can be stored in the form of a grid map, a topological map or a hybrid map, etc. Its purpose is to provide accurate spatial information for path planning. Aisle topology information refers to data describing the logical structure of aisle connection relationships, traffic rules, one-way or two-way traffic restrictions, etc. in the warehouse, which helps the path planning algorithm to consider physical distance while taking into account actual traffic rules. The path planning algorithm refers to an algorithm used to calculate a path that meets a certain optimization goal (such as shortest distance, shortest time, obstacle avoidance, etc.) between a given starting point (the position of the stacker) and an ending point (the common resource entrance) according to the warehouse map and the aisle topology information. For example, A* algorithm, Dijkstra algorithm, RRT (Rapidly-exploring Random Tree) algorithm or PRM (Probabilistic Roadmap) algorithm, etc. can be used, and the purpose is to ensure that the calculated path is actually feasible and optimal. The optimal path refers to the best route from the current position of the stacker to the common resource entrance under all constraint conditions (such as obstacle avoidance, aisle rules, etc.) through the path planning algorithm. This "optimal" can be defined according to actual needs, such as shortest physical distance, shortest estimated time, lowest energy consumption, etc. According to the optimal path of the stacker to the common resource entrance, the distance of the stacker to the common resource entrance is derived, which means that after the optimal path is calculated, the length of the path is accumulated or integrated to obtain the total distance required for the stacker to travel along the optimal path.

[0132] Specifically, the pre-stored warehouse map and the aisle topology information provide comprehensive environmental data for path planning, enabling the path planning algorithm to fully consider physical obstacles, aisle structure and traffic restrictions within the warehouse. As a result, the calculated optimal path is not only the theoretically shortest path, but also an actually feasible and most efficient travel route. By accurately calculating the length of this optimal path, a more accurate distance of the stacker to the common resource entrance can be obtained. This accurate distance information is crucial for subsequent estimated arrival time calculation, thereby improving the accuracy of time token allocation and the overall scheduling efficiency of the system.

[0133] As a specific implementation, suppose a stacker crane is located in a warehouse environment with multiple intersecting aisles and fixed obstacles, and needs to travel to the public resource entrance. The coordination module first retrieves pre-stored warehouse map and aisle topology information, which details the connection methods, widths, and obstacle locations of aisles A, B, and C. Then, the coordination module invokes the A* path planning algorithm. This algorithm, starting from the stacker crane's current position and ending at the public resource entrance, calculates the optimal path—avoiding obstacles, following aisle traffic rules, and minimizing distance—based on the warehouse map and aisle topology information. For example, the optimal path might not be a straight line, but rather a route through aisle A, turning into aisle B, then into aisle C, finally reaching the public resource entrance. Once the optimal path is determined, the coordination module accumulates the lengths of each segment along this path to accurately calculate the actual travel distance from the stacker crane to the public resource entrance. This precise distance is then used to calculate the estimated arrival time of the stacker crane, ensuring more reasonable allocation of time tokens.

[0134] This application further proposes a step to offload unfinished high-priority tasks from one stacker crane to another. The aim is to ensure the effectiveness and reliability of task offloading through a refined evaluation and dynamic monitoring mechanism, thereby improving the robustness of the entire aisle stacker crane task scheduling method.

[0135] The steps for offloading high-priority tasks that have not been completed by a stacker crane to other stacker cranes include:

[0136] Continuously monitor the availability status of the stacker crane, including battery level, equipment health status, and environmental conditions of the aisle where the stacker crane is located;

[0137] Based on the task priority and task type of the stacker crane, several stacker cranes that can take over the task were initially selected.

[0138] For each initially selected stacker crane, based on its latest availability status, assess its current available capacity and task load, and predict the potential risks it may face while performing new tasks;

[0139] Adjust the candidate priority of stacker cranes or remove stacker cranes based on the predicted potential risks;

[0140] Before the stacker crane takes over and begins to perform its tasks, send the availability status query request again and monitor the environmental conditions of the aisle where the stacker crane is located again.

[0141] If monitoring detects a change in the availability of the replacement stacker crane, cancel the task assignment and restart the task routing process.

[0142] Specifically, continuous monitoring of the stacker crane's availability status refers to the system acquiring and analyzing the stacker crane's own operating parameters and external environmental information in real time. Battery power refers to the remaining charge in the stacker crane's power system, while equipment health status refers to the operating condition of key components such as mechanical parts and electrical systems, including motor wear and sensor malfunctions. The environmental conditions of the aisle where the stacker crane is located refer to the real-time environmental information of the aisle, such as the presence of obstacles, lighting conditions, temperature, and humidity. The purpose of this information is to comprehensively understand whether the stacker crane is capable of undertaking new tasks.

[0143] The initial screening based on the stacker crane's task priority and task type means that the system will select a set of stacker cranes that are theoretically capable of executing the task from all idle or low-load stacker cranes, based on the urgency and resource requirements of the task to be dispatched. For example, if the task requires a specific grasping capability, only stacker cranes with that capability will be selected.

[0144] Specifically, assessing current available capacity and workload means, for each initially selected stacker crane, comprehensively judging its ability to efficiently handle new tasks based on its latest battery level, equipment health status, and currently assigned workload. Predicting potential risks involves estimating, based on historical data and current environmental information, the risks that the stacker crane may encounter during the execution of new tasks, such as failures, delays, or environmental changes. For example, if a stacker crane has low battery power, it is predicted that it may need to recharge during long-duration tasks, leading to delays.

[0145] Adjusting the candidate priority of a stacker crane or removing a stacker crane based on the predicted potential risk means that if a stacker crane is predicted to have a high potential risk, its priority in the candidate list will be reduced, or it may even be removed from the candidate list directly, in order to avoid diverting tasks to unstable stacker cranes.

[0146] In practical applications, sending an availability status query request again and monitoring the environmental conditions of the aisle where the replacement stacker crane is located before the replacement stacker crane begins to perform its tasks are to conduct a final confirmation before the tasks are officially assigned, to ensure that the status of the replacement stacker crane has not changed adversely in a short period of time, thereby reducing the risk of task execution.

[0147] If the availability of the replacement stacker crane changes again during monitoring, the task assignment is canceled and the task routing process is restarted. This is to cope with the dynamically changing warehouse environment and equipment status, ensure the flexibility and reliability of task routing, and avoid making wrong decisions due to information lag.

[0148] This application's solution effectively addresses the potential blindness and uncertainty in task allocation within the basic scheme by introducing a multi-stage, dynamic stacker crane availability status assessment and risk prediction mechanism. First, by continuously monitoring the stacker crane's availability status, including battery power, equipment health, and aisle environment conditions, a comprehensive data foundation is provided for subsequent screening and evaluation. Second, after initially identifying stacker cranes capable of taking over tasks, their capabilities and task loads are further assessed based on their latest availability status, and potential risks are predicted, making task allocation decisions more scientific and prudent. Finally, a secondary confirmation is performed before formal task allocation, i.e., a new availability status query request is sent and environmental conditions are monitored. A mechanism is set up to cancel allocation and restart the allocation process if the status changes, thus forming a closed-loop, adaptive task allocation strategy that significantly improves the success rate of task allocation and the overall scheduling efficiency of the system.

[0149] In some preferred embodiments, it is assumed that stacker crane A, while performing a high-priority task, is unable to use its acquired time token on time due to a temporary failure in its main aisle. In this case, the coordination module needs to offload the unfinished high-priority task from stacker crane A to other stacker cranes. First, the system continuously monitors the availability status of all other stacker cranes in the warehouse (e.g., stacker cranes B, C, and D), including their battery levels, equipment health status (e.g., whether the motors are operating normally), and the environmental conditions of their current aisle (e.g., whether there are other obstacles). Based on the task priority and task type of stacker crane A, the system initially screens stacker cranes B and C as potential replacements. Subsequently, the system assesses the current task load and availability of stacker cranes B and C based on their latest availability status and predicts potential risks that may occur during task replacement. For example, if stacker crane B's battery level is low, the system predicts that it may need to recharge while performing the high-priority task, resulting in delays; while stacker crane C is in good condition and has a low task load. Based on these predictions, the candidate priority of stacker crane B will be reduced, and stacker crane C will be selected as the optimal successor. Before stacker crane C begins executing its task, the system will send an availability status query request to stacker crane C again and monitor the environmental conditions of the aisle where stacker crane C is located again. If a critical sensor of stacker crane C is found to malfunction at this time, and its availability status changes, the system will immediately cancel the task assignment to stacker crane C and restart the task routing process to ensure that the task is always assigned to the most reliable stacker crane.

[0150] This application further proposes steps for determining whether a stacker crane is unable to use the acquired time token on time, including:

[0151] Collect operational data of the stacker crane and environmental data of the aisle where the stacker crane is located;

[0152] Analyze the performance trends of the stacker crane based on its operating data;

[0153] Analyze the changing trends of the roadway environment based on the environmental data of the stacker crane;

[0154] The stacker crane's performance trend, the change trend of the aisle environment, and the information of the time tokens already obtained by the stacker crane are matched to determine whether the stacker crane is unable to use the obtained time tokens on time.

[0155] If it is determined that the stacker crane cannot use the acquired time token on time, an alert will be triggered;

[0156] Initiate the intervention process, which includes sending instructions to the stacker crane or sending a time token adjustment request to the coordination module;

[0157] If the stacker still cannot use the acquired time tokens on time after intervention, the acquired time tokens will be immediately revoked and released to the public resource pool.

[0158] Specifically, collecting operational data of the stacker crane and environmental data of the aisle where the stacker crane is located refers to the system continuously acquiring various real-time parameters of the stacker crane during operation, such as speed, acceleration, motor load, and battery level, as well as environmental information within the aisle, such as obstacle detection, ground conditions, and light intensity. This data can originate from onboard sensors on the stacker crane, environmental sensors within the aisle, and the central control system. Analyzing the performance trend of the stacker crane based on its operational data can be understood as processing and modeling historical and real-time operational data to predict the stacker crane's performance over a future period, such as identifying potential failure risks, speed decline trends, or abnormal energy consumption. Simultaneously, analyzing the changing trends of the aisle environment based on the environmental data of the stacker crane's aisle refers to assessing the potential impact of aisle environmental factors on the stacker crane's operation, such as obstacle movement paths, congestion, or the likelihood of unforeseen events. In practical applications, the stacker crane's performance trend, the changing trend of the aisle environment, and the information of the time tokens already acquired by the stacker crane are matched to determine whether the stacker crane will be unable to use the acquired time tokens on time. The purpose is to comprehensively consider the stacker crane's own state and the external environment to make a more comprehensive and accurate predictive judgment. For example, if the stacker crane's performance trend shows that its speed will continue to be lower than expected, and the aisle environment trend indicates that congestion may occur ahead, the system will determine that the stacker crane may not be able to arrive on time and use the acquired time tokens. Furthermore, if it is determined that the stacker crane cannot use the acquired time tokens on time, an early warning is triggered to promptly notify relevant systems or operators so that preventive measures can be taken. Subsequently, an intervention process is initiated, which may include sending instructions to the stacker crane, such as adjusting its operating speed, changing its travel path, or sending a time token adjustment request to the coordination module to attempt to renegotiate or adjust the available time window of the time tokens. Therefore, if the stacker crane still cannot use the time token it has obtained on time after intervention, the system will immediately reclaim the time token it has obtained and release it to the public resource pool, thereby ensuring that the public resources can be efficiently utilized by other waiting stacker cranes and avoiding resource idleness or waste.

[0159] In some preferred embodiments, it is assumed that a stacker crane has obtained a time token to occupy a public intersection for the next 5 minutes. The system continuously collects motor load data, speed data, and obstacle sensor data in the aisle ahead of the stacker crane. Through analysis, the system finds that the stacker crane's motor load is continuously increasing, its speed is showing a slight decreasing trend, and a sensor in the aisle ahead has detected a slowly moving obstacle. Based on the trend analysis of these operational and environmental data, the system predicts that the stacker crane may not be able to arrive at and successfully pass through the public intersection within 5 minutes. At this point, the system triggers an alert and initiates an intervention process. The intervention process may first send instructions to the stacker crane, requesting it to fine-tune its operating speed or attempt to plan a slightly different path to avoid the obstacle. Simultaneously, the system may also send a time token adjustment request to the coordination module, attempting to extend the available time window of the stacker crane's time token by 1 minute. If, after these interventions, the stacker crane's operating status and environmental conditions improve, enabling it to use the time token on time, then it does not need to be revoked. However, if the stacker still fails to arrive on time after intervention, for example, due to obstacles moving too slowly or the stacker itself malfunctioning, the system will immediately reclaim the time tokens already acquired by the stacker and release them to the public resource pool so that the coordination module can reassign them to other waiting stackers, thereby minimizing the idle time of the public resources.

[0160] This application further proposes a step of reassigning the released time token to another stacker crane in the waiting queue that has the highest priority and can be used on time, specifically including:

[0161] Select the stacker with the highest priority that can arrive within the available time window of the released time token from the waiting queue as the initial candidate stacker;

[0162] Send a pre-allocated token notification to the initial candidate stacker cranes. The pre-allocated token notification contains the public resource ID of the released time token, the available time window, and the deadline for confirmation response.

[0163] After receiving the pre-assigned token notification, the onboard controller of the preliminary candidate stacker crane performs a self-check, which includes checking the battery level, drive system health status and the latest accuracy report of the vehicle positioning system.

[0164] Based on its own status self-check results, the preliminary candidate stacker crane onboard controller rehearses the path from the current location to the public resource and continues to execute subsequent tasks;

[0165] During the path rehearsal process, the onboard controller of the preliminary candidate stacker crane sends query requests to the resources that must be passed through the path of the subsequent tasks of the preliminary candidate stacker crane to obtain the real-time availability of the resources that must be passed through the path.

[0166] Based on the path rehearsal results, the onboard controller of the preliminary candidate stacker crane calculates the estimated time for the preliminary candidate stacker crane to arrive at the pre-allocated public resource and assesses whether the preliminary candidate stacker crane can arrive within the available time window of the released time token.

[0167] The onboard controller of the initial candidate stacker crane, combined with the real-time availability of the resources required by the path, evaluates the success rate of time token application on the path of subsequent tasks of the initial candidate stacker crane;

[0168] Based on the evaluation results, the onboard controller of the initial candidate stacker crane generates a response, which includes a time token acceptance response or a time token rejection response.

[0169] The coordination module receives responses from the initial candidate stacker cranes;

[0170] The coordination module waits for responses from all preliminary candidate stacker cranes before confirming the response deadline;

[0171] If the coordination module receives a receive time token response and does not receive any other conflicting receive time token responses before the confirmation response deadline, it will finally assign the time token to the initial candidate stacker.

[0172] If all initial candidate stacker cranes reject the time token response, or if no time token response is received before the confirmation deadline, the time token is released back to the public resource pool, and the next highest priority stacker crane is selected from the waiting queue, repeating the pre-allocation and response process.

[0173] Specifically, "preliminary candidate stacker cranes" refer to potential replacement stacker cranes selected from the waiting queue based on their task priority and a preliminary assessment of their ability to arrive at the public resource within the available time window of the released time token. These stacker cranes are the primary considerations before the system conducts a refined evaluation.

[0174] The "Pre-allocated Token Notification" is a communication message sent by the coordination module to preliminary candidate stacker cranes, containing detailed information about the time token to be allocated. Its purpose is to inform the stacker crane of the key attributes of the time token so that it can conduct self-assessment and decision-making. Specifically, the "Public Resource ID" uniquely identifies the public resource corresponding to the time token; the "Available Time Window" specifies the time range within which the time token can be used; and the "Confirmation Response Deadline" requires the stacker crane to submit its response to the coordination module before this time.

[0175] "Self-check" is the process by which the onboard controller of the preliminary candidate stacker crane performs a comprehensive check on its own operating status after receiving the pre-assigned token notification. This includes checking the "battery power" to ensure sufficient energy to complete the task; checking the "drive system health status" to assess the reliability of its mechanical and electrical systems; and checking the "updated accuracy report of the onboard positioning system" to ensure the accuracy of its position and speed data, which is crucial for accurate path planning and time estimation.

[0176] "Rehearsing the path from the current location to the common resource and continuing to execute subsequent tasks" means that the initial candidate stacker crane onboard controller must not only plan the path to the common resource, but also integrate the use of that common resource with the execution path of its subsequent tasks to form a coherent overall path plan. Its purpose is to evaluate the feasibility of the entire task chain, not just the use of a single common resource.

[0177] "Path-bound resources" refer to other public resources that must be traversed on the path of the initial candidate stacker crane, in addition to the public resources currently to be allocated. The purpose of querying their "real-time availability" is to ensure that the task will not be interrupted or delayed due to the unavailability of other critical resources before or after reaching the current public resource.

[0178] "Time Token Application Success Rate" is a comprehensive assessment by the onboard controller of the initial candidate stacker crane, based on its own status, path rehearsal results, and the real-time availability of resources required by the path, regarding the likelihood of obtaining the time tokens needed for subsequent tasks. Its purpose is to help the stacker crane more accurately determine whether it can successfully complete the entire task, rather than simply using the currently released time tokens.

[0179] "Receive Time Token Response or Reject Time Token Response" is a decision signal sent by the onboard controller of the initial candidate stacker crane to the coordination module based on its comprehensive evaluation results. A "receive" response indicates that the stacker crane is confident in using the equipment on time and completing the task, while a "reject" response indicates that the stacker crane believes it cannot meet the requirements.

[0180] The "Confirm Response Deadline" is a time point set by the coordination module to collect all preliminary candidate stacker crane responses, with the aim of ensuring that a final allocation decision is made within a reasonable timeframe.

[0181] "Conflicting Receive Time Token Responses" refers to a situation where the coordination module receives multiple initial candidate stacker cranes' receive responses for the same time token before the response confirmation deadline. In this case, the coordination module needs to determine the final allocation based on a pre-defined conflict resolution strategy (e.g., comparing priorities again or more detailed evaluation results).

[0182] "Released back to the public resource pool" means that when all initial candidate stackers reject the time token, or no valid acceptance response is received before the deadline, the time token will become available again, waiting for the next allocation.

[0183] This application's solution addresses the potential blindness issue in time token redistribution by introducing bidirectional interaction between the stacker crane's onboard controller and the coordination module, along with the stacker crane's own intelligent evaluation mechanism. Specifically, after a time token is released, the coordination module first performs a preliminary screening to identify potential successors. Then, by sending pre-allocated token notifications to these preliminary candidate stacker cranes, decision-making power and evaluation responsibility are partially delegated to the stacker crane's onboard controller. Upon receiving the notification, the stacker crane's onboard controller no longer passively accepts instructions but actively performs a self-check, comprehensively evaluating its battery level, drive system health, and positioning accuracy to ensure its hardware meets task requirements. More importantly, the stacker crane's onboard controller rehearses the complete path from its current location to a shared resource and continues executing subsequent tasks, actively querying the real-time availability of resources along the path to comprehensively assess the feasibility of the entire task chain. This evaluation, based on the stacker crane's own real-time data and future path rehearsals, can more accurately predict whether the stacker crane can arrive and successfully complete the task within the available time window of the released time token and assess the success rate of time token applications for subsequent tasks. Ultimately, the stacker crane's onboard controller sends an accept or reject response to the coordination module based on its detailed evaluation results, thereby avoiding incorrect allocation due to information asymmetry. The coordination module is responsible for collecting and coordinating these responses, handling potential conflicts before the response deadline, and ultimately making the optimal and reliable allocation decision.

[0184] In some preferred embodiments, it is assumed that at some point, stacker A fails to use its acquired time token for public resource X on time due to a malfunction. This time token is then reclaimed by the coordination module and released to the public resource pool. At this time, stacker B, stacker C, and stacker D are waiting in the waiting queue to use public resource X, with stacker B having the highest priority.

[0185] First, the coordination module selects stacker B from the waiting queue as a preliminary candidate stacker because it has the highest priority and is preliminarily judged to be able to arrive within the available time window of the released time token.

[0186] Subsequently, the coordination module sends a pre-allocated token notification to stacker B, which includes the ID of public resource X, the available time window for the released time token (e.g., within 10 minutes from the current time), and the deadline for confirming the response (e.g., 5 minutes later).

[0187] Upon receiving the notification, the onboard controller of stacker crane B immediately performed a self-check. It found that the battery had sufficient power, the drive system was in good health, and the latest accuracy report from the onboard positioning system showed accurate positioning.

[0188] Based on the self-test results, the onboard controller of stacker crane B begins to rehearse the path from its current position to common resource X and then continues to execute its subsequent tasks. During the path rehearsal, stacker crane B discovers that its subsequent tasks require traversing common resource Y. Therefore, the onboard controller of stacker crane B sends a query request to common resource Y to obtain its real-time availability. Assume that common resource Y is currently available.

[0189] Based on the path rehearsal results, the onboard controller of stacker crane B calculates its estimated arrival time at public resource X to be 8 minutes, which is within the available time window (10 minutes) of the released time token. Simultaneously, considering the real-time availability of public resource Y, stacker crane B assesses a high success rate for time token requests on its subsequent task paths.

[0190] Based on the above evaluation results, the stacker crane B's onboard controller generates a receive time token response and sends it to the coordination module.

[0191] Before confirming the response deadline, the coordination module waits for responses from other initial candidate stacker cranes (in this example, only stacker crane B). Since only a response from stacker crane B to receive the time token was received, and there were no other conflicting responses, the coordination module ultimately assigns the time token to stacker crane B.

[0192] Thus, stacker crane B obtains a time token for public resource X and adjusts its operating speed according to the specified time to proceed to public resource X to perform its task. This refined evaluation and response mechanism ensures that the released time tokens are allocated to stacker cranes that are truly capable of using them on time, thereby avoiding the risk of resources being ineffectively occupied again.

[0193] The following steps are included after dynamically allocating time tokens:

[0194] The coordination module sends a command to the stacker crane that has obtained the time token, and the command contains the time specified by the time token.

[0195] The stacker crane adjusts its operating speed according to the time specified by the time token.

[0196] Specifically, after successfully allocating a time token to the stacker crane, the coordination module generates an instruction containing the time specified by that time token. This instruction can be understood as a scheduling command, the core of which is to inform the stacker crane when it can begin or end its occupation of a specific public resource. This instruction is sent via the wireless communication network to the onboard controller of the stacker crane that obtained the time token. The time specified by the time token can be a point in time, such as the expected time when the stacker crane arrives at the public resource entrance, or it can be a time window, such as the start and end times when the stacker crane is allowed to occupy the public resource.

[0197] Furthermore, after receiving the instruction from the coordination module, the stacker crane's onboard controller parses the time specified in the time token within the instruction. Based on this time information, the stacker crane's internal motion control system is triggered to adjust the stacker crane's operating speed. For example, if the instruction specifies that the stacker crane needs to arrive at the public resource entrance at a particular time, the stacker crane will calculate the required average speed based on its current position, speed, and distance to the public resource entrance, and accelerate or decelerate accordingly. This speed adjustment can be continuous or segmented to ensure that the stacker crane arrives at or departs from the public resource precisely at the specified time.

[0198] This application also discloses a roadway stacker crane task scheduling system, applied to a roadway stacker crane task scheduling method. The system includes:

[0199] The management module is used to register public resources and manage their status information.

[0200] The planning module assigns tasks to the stacker crane and calculates the task execution path of the stacker crane based on the task. If the task execution path needs to pass through public resources, it estimates the time period during which the stacker crane occupies the public resources and requests time tokens for the public resources from the coordination module.

[0201] The coordination module dynamically allocates time tokens based on the stacker crane's task priority, the availability of public resources, the stacker crane's estimated arrival time, and the overall system load. If the stacker crane obtains a time token, its running speed is adjusted according to the time specified by the time token.

[0202] The monitoring module continuously monitors the operating status of the stacker crane, as well as the environmental conditions of the main aisle and temporary work aisles of the stacker crane. Based on the operating status and environmental conditions, it determines whether the stacker crane is unable to use the obtained time tokens on time.

[0203] If the release module determines that the stacker cannot use the acquired time tokens on time, it immediately reclaims the acquired time tokens and releases them to the public resource pool.

[0204] The escape module plans an escape path for the stacker crane based on its task priority and re-applies for time tokens for the public resources required along the escape path.

[0205] The routing module routes high-priority tasks that have not been completed by the stacker crane to other stacker cranes and requests time tokens for the rerouted tasks.

[0206] The allocation module reassigns the released time tokens to other stacker cranes in the waiting queue that have the highest priority and can be used on time.

[0207] The management module is used to register public resources and manage their status information. Specifically, the management module can be a standalone software service or a component integrated into a central dispatch system. It communicates with warehouse infrastructure (such as sensors and public resource controllers) to collect information such as the occupancy status, estimated idle time, and maintenance plans of public resources in real time, and stores this information in a database. For example, the management module can receive signals from sensors at the entrance and exit of public resources to update the real-time occupancy status of the public resources.

[0208] The planning module assigns tasks to stacker cranes and calculates their execution paths based on the tasks. If the execution path requires access to shared resources, it estimates the time the stacker crane will occupy the shared resources and requests time tokens for the shared resources from the coordination module. The planning module can integrate path planning algorithms and task allocation logic, generating optimal execution paths for stacker cranes based on the warehouse map, aisle topology information, and the current location and status of the stacker cranes. When the path involves shared resources, the planning module estimates the time period of occupation based on the stacker crane's expected speed and the length of the shared resources, and generates a time token request to send to the coordination module.

[0209] The coordination module dynamically allocates time tokens based on the stacker crane's task priority, the availability of shared resources, the stacker crane's estimated arrival time, and the overall system load. If a stacker crane obtains a time token, it adjusts its operating speed according to the time specified in the token. The coordination module is the core decision-making unit of the system; it receives time token requests from the planning module and makes real-time decisions by comprehensively considering multiple factors. For example, the coordination module can use algorithms such as priority queues and time window conflict detection to ensure that shared resources are allocated efficiently and without conflict. Once allocation is successful, the coordination module sends instructions to the stacker crane to adjust its operating speed according to the specified time.

[0210] The monitoring module continuously monitors the stacker crane's operating status and the environmental conditions of its main and temporary work aisles. Based on the operating status and environmental conditions, it determines whether the stacker crane will be unable to use the acquired time tokens on time. The monitoring module integrates data from various sensors (such as onboard sensors on the stacker crane and aisle environmental sensors) to collect real-time data on the stacker crane's position, speed, battery level, equipment health status, and environmental data such as temperature, humidity, and obstacles within the aisles. The monitoring module analyzes this data to identify potential anomalies, such as abnormal speed drops in the stacker crane or aisle blockages, thereby determining whether the stacker crane may be unable to use the acquired time tokens on time.

[0211] The release module is used to immediately reclaim the time tokens acquired by a stacker crane if it determines that the stacker crane cannot use them on time, and release the time tokens to the public resource pool. When the monitoring module detects that a stacker crane cannot use a time token on time, the release module will immediately perform the token reclamation operation. This includes sending a cancellation command to the stacker crane, updating the status of the time token to available, and re-adding it to the public resource pool for other stacker cranes to request.

[0212] The escape module plans an escape path for the stacker crane based on its task priority and re-requests time tokens for shared resources along the escape path. When a stacker crane encounters an obstacle or malfunctions and becomes stuck, the escape module plans a safe and efficient escape path based on its current location, task priority, and the real-time status of the warehouse. Simultaneously, the escape module re-requests time tokens from the coordination module for the shared resources required along this escape path, ensuring the stacker crane can successfully escape its predicament.

[0213] The task allocation module is used to offload high-priority tasks that are not yet completed on a stacker crane to other stacker cranes and to request time tokens for the offloaded tasks. To minimize the impact of unforeseen events on overall system efficiency, the task allocation module identifies high-priority tasks that are stuck on a stacker crane. Then, based on factors such as the availability of other stacker cranes, task load, and location, the module selects a suitable stacker crane to take over these tasks. Once a task is offloaded, the module requests the corresponding time token from the coordination module for the new executing stacker crane to ensure that the task can be completed as quickly as possible.

[0214] The allocation module reassigns released time tokens to other stacker cranes in the waiting queue that have the highest priority and can be used on time. When a time token is reclaimed by the release module and released to the public resource pool, the allocation module checks if any other stacker cranes in the waiting queue are requesting the same public resource. The allocation module prioritizes the stacker crane with the highest priority that can arrive and use the time token within its available time window, and reassigns the time token to it. This maximizes the utilization of public resources, reduces resource idle time, and improves the overall system efficiency.

[0215] The content disclosed above is only a preferred and feasible embodiment of the present invention, and is not intended to limit the scope of protection of the present invention. Therefore, all equivalent technical changes made based on the content of the present invention specification and drawings are included within the scope of protection of the present invention. Furthermore, the elements therein can be updated as technology develops.

Claims

1. A method for scheduling tasks of a stacker crane in a roadway, characterized in that, The method includes the following steps: Register public resources and manage their status information; Assign tasks to the stacker crane and calculate the task execution path of the stacker crane based on the task. If the task execution path needs to pass through public resources, estimate the time period during which the stacker crane occupies the public resources and apply for time tokens for the public resources from the coordination module. The coordination module dynamically allocates time tokens based on the stacker crane's task priority, the availability of public resources, the stacker crane's estimated arrival time, and the overall system load. If the stacker crane obtains a time token, its running speed is adjusted according to the time specified by the time token. Continuously monitor the operating status of the stacker crane, as well as the environmental conditions of the main aisle and temporary operation aisles of the stacker crane. Based on the operating status and environmental conditions, determine whether the stacker crane is unable to use the obtained time tokens on time. If it is determined that the stacker cannot use the acquired time tokens on time, the acquired time tokens of the stacker will be immediately revoked and released to the public resource pool; Based on the stacker crane's task priority, plan an escape route for the stacker crane and re-apply for time tokens for the public resources required along the escape route; Distribute high-priority tasks that are not completed by the stacker crane to other stacker cranes, and request time tokens for the distributed tasks; The released time tokens are reassigned to the other stacker cranes in the waiting queue that have the highest priority and can be used on time.

2. The method for scheduling stacker crane tasks in a roadway as described in claim 1, characterized in that, The steps for obtaining the availability of public resources and the estimated arrival time of the stacker crane include: By integrating data from the stacker crane's wheel encoders, inertial measurement units, and positioning beacons within the aisle, the position and speed of the stacker crane can be obtained. The stacker crane's onboard controller sends an occupancy status query request to the public resource controller to obtain the physical occupancy status of the public resource. The stacker crane's onboard controller combines the physical occupancy status of public resources, the average processing time of public resources, and real-time monitoring of sensors at the entrance of public resources to predict the availability of public resources. Calculate the estimated arrival time of the stacker crane based on its location and speed, and the distance from the stacker crane to the public resource entrance. The stacker crane's onboard controller and coordination module communicate to report the stacker crane's estimated arrival time and the availability of public resources.

3. The method for scheduling stacker crane tasks in a roadway as described in claim 2, characterized in that, The steps for calculating the estimated arrival time of a stacker crane include: The coordination module receives real-time position and speed data from the stacker crane's onboard positioning system; The coordination module performs real-time filtering on the real-time position and speed data to obtain the position and speed of the stacker crane. The distance from the stacker crane to the public resource entrance is determined based on the location of the stacker crane, the pre-stored warehouse map, and the aisle topology information. The coordination module calculates the estimated arrival time of the stacker crane based on its location and speed, combined with the distance from the stacker crane to the public resource entrance, using path tracing algorithms and kinematic models.

4. The method for scheduling stacker crane tasks in a roadway as described in claim 3, characterized in that, The coordination module performs real-time filtering on the real-time position and speed data to obtain the stacker crane's position and speed. The steps include: The coordination module selects a filtering algorithm to filter the real-time position and velocity data to obtain filtered position and velocity estimates. The filtered position and velocity estimates are the position and velocity of the stacker crane.

5. The method for scheduling stacker crane tasks in a roadway as described in claim 3, characterized in that, The steps for determining the distance from the stacker crane to the public resource entrance based on the stacker crane's location, pre-stored warehouse map, and aisle topology information include: Based on the location of the stacker crane, the pre-stored warehouse map, and the aisle topology information, the stacker crane is identified, and the optimal path from the stacker crane to the public resource entrance is calculated using a path planning algorithm. The distance from the stacker crane to the public resource entrance is determined based on the optimal path from the stacker crane to the public resource entrance.

6. The method for scheduling stacker crane tasks in a roadway as described in claim 1, characterized in that, The steps for offloading high-priority tasks that have not been completed by a stacker crane to other stacker cranes include: Continuously monitor the availability status of the stacker crane, including battery level, equipment health status, and environmental conditions of the aisle where the stacker crane is located; Based on the task priority and task type of the stacker crane, several stacker cranes that can take over the task were initially selected. For each initially selected stacker crane, based on its latest availability status, assess its current available capacity and task load, and predict the potential risks it may face while performing new tasks; Adjust the candidate priority of stacker cranes or remove stacker cranes based on the predicted potential risks; Before the stacker crane takes over and begins to perform its tasks, send the availability status query request again and monitor the environmental conditions of the aisle where the stacker crane is located again. If monitoring detects a change in the availability of the replacement stacker crane, cancel the task assignment and restart the task routing process.

7. The method for scheduling stacker crane tasks in a roadway as described in claim 1, characterized in that, The steps to determine whether a stacker crane is unable to use the acquired time token on time include: Collect operational data of the stacker crane and environmental data of the aisle where the stacker crane is located; Analyze the performance trends of the stacker crane based on its operating data; Analyze the changing trends of the roadway environment based on the environmental data of the stacker crane; The stacker crane's performance trend, the change trend of the aisle environment, and the information of the time tokens already obtained by the stacker crane are matched to determine whether the stacker crane is unable to use the obtained time tokens on time. If it is determined that the stacker crane cannot use the acquired time token on time, an alert will be triggered; Initiate the intervention process, which includes sending instructions to the stacker crane or sending a time token adjustment request to the coordination module; If the stacker still cannot use the acquired time tokens on time after intervention, the acquired time tokens will be immediately revoked and released to the public resource pool.

8. The method for scheduling stacker crane tasks in a roadway as described in claim 1, characterized in that, The steps for reassigning the released time tokens to the highest-priority stacker in the waiting queue that can be used on time include: Select the stacker with the highest priority that can arrive within the available time window of the released time token from the waiting queue as the initial candidate stacker; Send a pre-allocated token notification to the initial candidate stacker cranes. The pre-allocated token notification contains the public resource ID of the released time token, the available time window, and the deadline for confirmation response. After receiving the pre-assigned token notification, the onboard controller of the preliminary candidate stacker crane performs a self-check, which includes checking the battery level, drive system health status and the latest accuracy report of the vehicle positioning system. Based on its own status self-check results, the preliminary candidate stacker crane onboard controller rehearses the path from the current location to the public resource and continues to execute subsequent tasks; During the path rehearsal process, the onboard controller of the preliminary candidate stacker crane sends query requests to the resources that must be passed through the path of the subsequent tasks of the preliminary candidate stacker crane to obtain the real-time availability of the resources that must be passed through the path. Based on the path rehearsal results, the onboard controller of the preliminary candidate stacker crane calculates the estimated time for the preliminary candidate stacker crane to arrive at the pre-allocated public resource and assesses whether the preliminary candidate stacker crane can arrive within the available time window of the released time token. The onboard controller of the initial candidate stacker crane, combined with the real-time availability of the resources required by the path, evaluates the success rate of time token application on the path of subsequent tasks of the initial candidate stacker crane; Based on the evaluation results, the onboard controller of the initial candidate stacker crane generates a response, which includes a time token acceptance response or a time token rejection response. The coordination module receives responses from the initial candidate stacker cranes; The coordination module waits for responses from all preliminary candidate stacker cranes before confirming the response deadline; If the coordination module receives a receive time token response and does not receive any other conflicting receive time token responses before the confirmation response deadline, it will finally assign the time token to the initial candidate stacker. If all initial candidate stacker cranes reject the time token response, or if no time token response is received before the confirmation deadline, the time token is released back to the public resource pool, and the next highest priority stacker crane is selected from the waiting queue, repeating the pre-allocation and response process.

9. The method for scheduling stacker crane tasks in a roadway as described in claim 1, characterized in that, The following steps are included after dynamically allocating time tokens: The coordination module sends a command to the stacker crane that has obtained the time token, and the command contains the time specified by the time token. The stacker crane adjusts its operating speed according to the time specified by the time token.

10. A roadway stacker crane task scheduling system, applied to the roadway stacker crane task scheduling method as described in claim 1, characterized in that, The system includes: The management module is used to register public resources and manage their status information. The planning module assigns tasks to the stacker crane and calculates the task execution path of the stacker crane based on the task. If the task execution path needs to pass through public resources, it estimates the time period during which the stacker crane occupies the public resources and requests time tokens for the public resources from the coordination module. The coordination module dynamically allocates time tokens based on the stacker crane's task priority, the availability of public resources, the stacker crane's estimated arrival time, and the overall system load. If the stacker crane obtains a time token, its running speed is adjusted according to the time specified by the time token. The monitoring module continuously monitors the operating status of the stacker crane, as well as the environmental conditions of the main aisle and temporary work aisles of the stacker crane. Based on the operating status and environmental conditions, it determines whether the stacker crane is unable to use the obtained time tokens on time. If the release module determines that the stacker cannot use the acquired time tokens on time, it immediately reclaims the acquired time tokens and releases them to the public resource pool. The escape module plans an escape path for the stacker crane based on its task priority and re-applies for time tokens for the public resources required along the escape path. The routing module routes high-priority tasks that have not been completed by the stacker crane to other stacker cranes and requests time tokens for the rerouted tasks. The allocation module reassigns the released time tokens to other stacker cranes in the waiting queue that have the highest priority and can be used on time.

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