Method for job scheduling of a printing robot and related device

Abstract

Embodiments of the present application relate to a method for scheduling jobs of printing robots and related equipment, the method comprising: obtaining current values of each evaluation factor corresponding to each printing robot; determining whether the current value of each evaluation factor exceeds the corresponding determination threshold to obtain a determination result; determining the actual weight proportion of each evaluation factor according to the determination result according to a preset weight adjustment rule; calculating a comprehensive scheduling score corresponding to each printing robot respectively; and determining a printing robot for executing a to-be-assigned job based on the comprehensive scheduling score. Since the calculated comprehensive scheduling score can accurately and truly reflect the current service capability of the printing robot, the scheduling server can make a scheduling decision from the perspective of global optimization, avoid assigning jobs to printing robots with hidden defects, thereby significantly reducing the interruption risk and failure rate in the job execution process, and effectively improving the overall job efficiency based on multiple printing robots.

Description

Technical Field

[0001] This application relates to the field of printing technology, and in particular to a method for scheduling printing robots and related equipment. Background Technology

[0002] With the continuous development of office automation and intelligent mobile robot technologies, printing robots with autonomous mobility are increasingly being applied in various office scenarios. These printing robots can autonomously navigate within a designated area, moving to the designated location to perform printing, scanning, and copying operations based on user-issued jobs. In actual deployment environments, multiple printing robots are typically configured to work collaboratively within the work area, allowing multiple users to issue jobs in parallel, with a central scheduling server managing the dispatch and retrieval of jobs.

[0003] Existing printing robot scheduling methods typically employ a first-come, first-served (FFS) strategy, assigning jobs to each robot sequentially based on their issuance time, or considering only the shortest physical path for a single job. However, because the working status of a printing robot changes in real time during job execution—for example, its remaining battery power gradually decreases, paper and consumables are consumed, and equipment malfunctions may occur—scheduling based on a fixed order or a single factor fails to comprehensively consider the real-time combined status of each robot. This can easily lead to jobs being assigned to seemingly usable but actually high-risk devices (such as those with insufficient battery power or running out of consumables), increasing the risk of job failure and reducing overall operational efficiency. Therefore, how to achieve multi-dimensional dynamic evaluation and intelligent scheduling of multiple printing robots is a pressing technical problem that needs to be solved. Summary of the Invention

[0004] This application provides a job scheduling method and related equipment for printing robots, which can improve the overall operating efficiency of printing robots.

[0005] According to a first aspect of the embodiments of this application, a job scheduling method for a printing robot is provided, applied to a scheduling server. The scheduling server is configured with multiple evaluation factors for evaluating the printing robot, and each evaluation factor is configured with a baseline weight and a judgment threshold. The method includes: The process involves: obtaining the current value of each evaluation factor for each printing robot; determining whether the current value of each evaluation factor exceeds the corresponding judgment threshold, and obtaining a judgment result; determining the actual weight ratio corresponding to each evaluation factor according to the judgment result and a preset weight adjustment rule; calculating the comprehensive scheduling score for each printing robot; wherein the comprehensive scheduling score is determined based on the current value of the evaluation factor and the corresponding actual weight ratio; determining the printing robot to execute the assigned job based on the comprehensive scheduling score; wherein the weight adjustment rule includes: when the current value of all evaluation factors does not exceed the corresponding judgment threshold, all evaluation factors are adjusted according to their respective benchmark weights. The first weight ratio determines the actual weight ratio; when the current value of an evaluation factor exceeds the corresponding judgment threshold, the evaluation factor exceeding the judgment threshold is determined to have an actual weight ratio according to a preset over-threshold weight ratio, and the actual weight ratios of the remaining evaluation factors are reduced to a second weight ratio proportionally according to their respective benchmark weights; when the current values ​​of two or more evaluation factors all exceed the corresponding judgment thresholds, the ratio of the benchmark weights of the two or more evaluation factors exceeding the judgment thresholds to the sum of the benchmark weights of all evaluation factors exceeding the judgment thresholds is used as the actual weight ratio of the corresponding evaluation factor, and the actual weight ratios of the remaining evaluation factors that do not exceed the judgment thresholds are determined to be zero.

[0006] Optionally, the evaluation factors include: remaining battery power, remaining paper, remaining consumables, equipment health, and target distance; the target distance is determined based on the distance from the current location of the printing robot to the target location.

[0007] Optionally, the method further includes: The system receives print jobs from users and places them in a job pool. When a new job is added to the job pool, or at preset time intervals, it recalculates the overall scheduling score of each printing robot. Based on the overall scheduling score of each printing robot, it reallocates all unassigned jobs in the job pool and jobs that have been assigned to printing robots but not yet completed, and generates or updates the scheduling table. The scheduling table contains the printing robot and delivery path information corresponding to the job assignment.

[0008] Optionally, the method further includes: When the target printing robot executes the target job dispatched based on the scheduling table, the scheduling server sets a timeout for the target job; if the target job is not completed within the timeout period, the status information of the target printing robot is obtained; if it is determined based on the status information that the target printing robot cannot continue to execute the target job, the target job is marked as an abnormal job and the abnormal job is recycled to the job pool to be processed; the abnormal job is re-dispatched, and the dispatch priority of the abnormal job is higher than that of the non-abnormal job.

[0009] Optionally, the method further includes: Receive an anomaly notification from the target printing robot. The anomaly notification indicates that the target printing robot is unable to continue executing the currently assigned target job due to an anomaly. Based on the anomaly notification, collect all unfinished jobs corresponding to the target printing robot and reassign them, and mark the target printing robot as offline.

[0010] Optionally, all unfinished jobs corresponding to the target printing robot are recycled, including: From the normal printing robots other than the target printing robot, identify the recycling robot to perform the recycling operation; use the recycling robot to recycle all unfinished jobs corresponding to the target printing robot.

[0011] Optionally, the cause of the anomaly may include at least one of the following: hardware failure of the printing robot, depletion of consumables, insufficient power, and path blockage.

[0012] Optionally, the timeout period is determined based on the type and / or complexity of the dispatched job.

[0013] According to a second aspect of the embodiments of this application, a job scheduling device for a printing robot is provided, applied to a scheduling server. The scheduling server is configured with multiple evaluation factors for evaluating the printing robot, and each evaluation factor is respectively configured with a benchmark weight and a judgment threshold. The device includes: The evaluation factor acquisition module is used to obtain the current value of each evaluation factor for each printing robot.

[0014] The judgment module is used to determine whether the current value of each evaluation factor exceeds the corresponding judgment threshold and obtain the judgment result.

[0015] The weight adjustment module is used to determine the actual weight ratio of each evaluation factor according to the judgment result and the preset weight adjustment rules.

[0016] The score calculation module is used to calculate the comprehensive scheduling score for each printing robot. The comprehensive scheduling score is determined based on the current value of the evaluation factors and their corresponding actual weight ratios.

[0017] The scheduling module is used to determine which printing robot will perform the assigned job based on the comprehensive scheduling score.

[0018] The weight adjustment rules include: When the current value of all evaluation factors does not exceed the corresponding judgment threshold, the actual weight ratio of all evaluation factors is determined according to the first weight ratio equal to their respective benchmark weights.

[0019] When the current value of an evaluation factor exceeds the corresponding judgment threshold, the evaluation factor exceeding the judgment threshold is assigned an actual weight ratio according to the preset over-threshold weight ratio, and the actual weight ratios of the remaining evaluation factors are reduced to the second weight ratio proportionally according to their respective benchmark weights.

[0020] When the current values ​​of two or more evaluation factors exceed the corresponding judgment threshold, the ratio of the benchmark weight of each of the two or more evaluation factors that exceed the judgment threshold to the sum of the benchmark weights of all evaluation factors that exceed the judgment threshold is used as the actual weight ratio of the corresponding evaluation factor. The actual weight ratio of the remaining evaluation factors that do not exceed the judgment threshold is determined to be zero.

[0021] According to a third aspect of the embodiments of this application, a server is provided. The server includes a memory and a processor, the memory storing a computer program, and the processor executing the program to implement the method as described above.

[0022] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the methods described in the embodiments of this application.

[0023] According to a fifth aspect of the embodiments of this application, a computer program product is provided, including a computer program that, when executed by a processor, implements the methods described above in the embodiments of this application. Attached Figure Description

[0024] More details, features, and advantages of embodiments of the present application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 A schematic diagram of the system architecture provided for an exemplary embodiment of this application; Figure 2 A schematic diagram illustrating a real-world application scenario provided for an exemplary embodiment of this application; Figure 3 A flowchart of a job scheduling method for a printing robot provided as an exemplary embodiment of this application; Figure 4 A schematic diagram of a real-time scheduling process provided for an exemplary embodiment of this application; Figure 5 A schematic block diagram of the functional modules of a job scheduling device for a printing robot provided in an exemplary embodiment of this application; Figure 6 A structural block diagram of a server provided for an exemplary embodiment of this application. Detailed Implementation

[0025] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While some embodiments of this application are shown in the drawings, it should be understood that embodiments of this application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the embodiments of this application. It should be understood that the accompanying drawings and embodiments of this application are for illustrative purposes only and are not intended to limit the scope of protection of this application.

[0026] It should be understood that the various steps described in the method implementation of this application may be performed in different orders and / or in parallel. Furthermore, the method implementation may include additional steps and / or omit the steps shown. The scope of this application is not limited in this respect.

[0027] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc., mentioned in the embodiments of this application are only used to distinguish different devices, modules, or units, and are not used to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0028] It should be noted that the terms "one" and "more" mentioned in the embodiments of this application are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more". The names of the messages or information exchanged between multiple devices in the embodiments of this application are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0029] As an optional but non-limiting implementation, in response to a user's active request, sending a prompt message to the user can be done via a pop-up window, where the prompt message can be presented in text format. Furthermore, the pop-up window can also include a selection control allowing the user to choose "agree" or "disagree" to provide personal information to the electronic device. It is understood that the above notification and user authorization process is merely illustrative and does not constitute a limitation on the implementation of this application's embodiments. Other methods that comply with relevant laws and regulations can also be applied to the implementation of this application's embodiments.

[0030] like Figure 1 As shown, Figure 1A system architecture diagram provided for an embodiment of this application is shown. The system includes: a scheduling server 110, at least one terminal 120, and multiple printing robots 130. Figure 1 The example shown is printing robot 131, printing robot 132... printing robot N). The scheduling server 110 is communicatively connected to the terminal 120 and each printing robot 130.

[0031] In this embodiment, the scheduling server 110 serves as the core control node of the system, used to receive jobs issued by the terminal 120, maintain the job pool to be processed, dispatch jobs to the printing robot 130, and collect status data reported by each printing robot 130 in real time.

[0032] Specifically, the scheduling server 110 has multiple preset evaluation factors for assessing the printing robot 130 (such as remaining battery power, paper balance, consumable balance, equipment health, target distance, etc.), and each evaluation factor is configured with a baseline weight and a judgment threshold. When a job needs to be assigned, the scheduling server 110 obtains the current value of each printing robot 130 for each evaluation factor, dynamically adjusts the actual weight ratio of each evaluation factor according to whether the current value exceeds the judgment threshold, calculates the comprehensive scheduling score of each printing robot 130, and finally selects the printing robot with the highest comprehensive scheduling score as the target device for job assignment.

[0033] Terminal 120 serves as the entry point for user interaction with the system. Users can edit and send print, scan, or copy jobs to the scheduling server 110 via terminal 120. Users do not need to manually specify the specific printing robot to perform the job on terminal 120; the scheduling server 110 selects the printing robots 130 and assigns the jobs.

[0034] The printing robot 130 is an intelligent device with autonomous mobility and printing capabilities, serving as the job execution end in the system. Each printing robot 130 can monitor its own network status, remaining battery power, current location, paper balance, consumable balance, and device health in real time, and periodically or event-drivenly report these status parameters to the scheduling server 110 via a wireless communication module. After receiving a job assigned by the scheduling server 110, the printing robot 130 autonomously moves to the target location to execute the corresponding task. If the printing robot 130 detects abnormal conditions such as hardware failure, depleted consumables, insufficient battery power, or path obstruction during job execution that prevent it from continuing to complete the job, it proactively sends an abnormality notification to the scheduling server 110 and returns the assigned but unfinished job. Simultaneously, the scheduling server 110 sets a timeout period for each assigned job. If communication is interrupted or the job is not completed within the timeout period, the scheduling server 110 proactively reclaims the job and reassigns it, thereby ensuring the final completion of the job and improving the system's robustness and job success rate.

[0035] Figure 2 This is a schematic diagram illustrating a practical application scenario provided by an embodiment of this application. The scenario exemplifies a collaborative scheduling system for multiple printing robots within an office building. In this example, the office building may contain multiple floors, each with multiple offices, housing multiple different companies. These companies can share multiple printing robots deployed within the building (such as...). Figure 1 The printing robot 131, printing robot 132, etc. are shown as examples in the example.

[0036] In traditional stand-alone or multi-machine independent management models, each company or department typically needs to configure its own printing equipment, resulting in high equipment procurement and maintenance costs, uneven equipment utilization, with some equipment remaining idle for extended periods while others operate under overload. This application's embodiment utilizes a centralized scheduling architecture, where a scheduling server manages and schedules all printing robots within a building. Multiple companies share the printing robots, effectively reducing hardware investment and consumable maintenance costs. Simultaneously, intelligent scheduling significantly improves overall equipment utilization and operational efficiency.

[0037] The specific scheduling interaction process is as follows: When an office worker in a company needs to issue printing, scanning, or copying jobs, they can send a job request to the scheduling server through their terminal. This job request may carry, or be automatically associated with, the user's location information (such as floor, office workstation, etc.), user permission information, and job attribute information (such as job type, number of pages, priority, etc.). After receiving the job, the scheduling server places it in the pending job pool. Subsequently, the scheduling server obtains real-time status data of all available printing robots, including the remaining battery power, paper balance, consumable balance, equipment health, and current values ​​of evaluation factors such as distance from the user's target location. For each printing robot, according to a preset weight adjustment rule, the actual weight ratio of each evaluation factor is determined based on whether the current value of each evaluation factor exceeds the corresponding judgment threshold, and then a weighted comprehensive scheduling score is calculated for each printing robot. Finally, the scheduling server selects the printing robot with the highest comprehensive scheduling score as the target printing robot and assigns the job to it. The assigned job may include path information planned by the scheduling server for this job, which comprehensively considers factors such as job priority, the current task sequence of the printing robot, and global path optimization. After receiving the job, the target printing robot autonomously travels to the user's location or a designated location according to the path, completes the corresponding printing, scanning or copying job, and delivers it to the user.

[0038] It should be noted that, in this embodiment, device health is used as one of the important evaluation factors for assessing the comprehensive service capabilities of the printing robot, and is used to quantitatively reflect the current health level of the printing robot's overall hardware. In an optional implementation, device health can be determined by summarizing the cumulative usage time of key hardware components, which may include, but are not limited to, mechanical transmission components such as gears and motors, and motion execution components. Specifically, the printing robot's status monitoring module can continuously record and statistically analyze the operating time of each key hardware component. The scheduling server can calculate the current value of device health based on the cumulative usage time of each hardware component, combined with its preset design life or maintenance cycle. The longer the cumulative usage time, the greater the wear and tear of the key hardware, and the lower the device health; conversely, hardware with shorter usage time or that has been maintained or replaced has a higher device health.

[0039] By linking device health with hardware usage time, this application embodiment can more objectively and accurately reflect the mechanical wear and performance degradation of the printing robot caused by long-term operation. This allows the comprehensive scheduling score to effectively avoid assigning high-load tasks to devices with severely aged hardware and a high risk of failure, further improving the rationality of scheduling decisions and the stability of system operation.

[0040] During job execution, the scheduling server continuously monitors the job status of each printing robot. If a target printing robot detects an anomaly such as hardware failure, depletion of consumables, insufficient power, or path obstruction during job execution and is unable to continue completing the job, it will proactively report the anomaly to the scheduling server. Upon receiving this information, the scheduling server reclaims all unfinished jobs of that printing robot, puts the reclaimed jobs back into the pending job pool, recalculates the overall scheduling score of each available printing robot, and reassigns the job to ensure that it can be taken over and completed by another suitable printing robot. At the same time, the scheduling server marks the abnormal printing robot as offline and generates a maintenance notification message to send to the maintenance personnel. In addition, the scheduling server sets a timeout period for each assigned job. If a job is not completed within the timeout period due to communication interruption or power failure of the printing robot, the scheduling server proactively reclaims the job, raises its priority, and reassigns it, thereby achieving seamless job takeover and ensuring the high availability and robustness of the entire shared printing service system.

[0041] Through the above solution, this embodiment enables multiple companies to share and schedule multiple printing robots within the same building, thereby reducing overall printing costs, maximizing equipment utilization and job execution efficiency, and significantly improving user experience.

[0042] In this embodiment, the hardware structure of each printing robot mainly includes the following functional modules: Mobility and Energy Module: The printing robot utilizes a wheeled mobility structure, enabling rapid and stable movement within the office area. It has an integrated power supply as an energy storage system, employing a high-energy-density battery to provide sustained battery life. When the battery level drops below a preset threshold, the robot can autonomously return to the printing robot charging station for automatic recharging. The charging station also features a modular structure for easy replacement of consumables such as full paper trays and toner cartridges, reducing the frequency of manual maintenance.

[0043] Printing module: The printing robot integrates printing components, including printing, scanning, and copying functions, and can work in conjunction with the intelligent storage compartment. The intelligent storage compartment has multiple storage compartments, each capable of independently storing printed paper, meeting the needs of multiple users for encrypted printing. This means that different users' print jobs are stored in separate compartments, and only the corresponding user can retrieve the prints after authentication, ensuring information security.

[0044] Perception and Interaction Module: The printing robot can be equipped with a touch screen display, supporting touch control. This allows for setting system information and controlling specific operations. When unattended, it can function as an information display screen, playing promotional videos, announcements, and other content. A camera is used for security verification, sharing facial information with the company's facial recognition access control system for user identity verification. A microphone and speaker combination enables human-machine dialogue; users can control the printing robot to perform corresponding actions via voice commands. The speaker can also serve as a mobile broadcasting device for emergency announcements (such as fires). Furthermore, the printing robot is equipped with an RFID card recognition module, sharing information with the company's access control card system. Users can swipe their cards to complete identity verification and retrieve the corresponding printed documents.

[0045] The perception and navigation module can include LDS (Laser Distance Sensor) and sensors such as distance, touch, and sonar. It can scan and perceive the surrounding environment, perform 3D mapping and path planning, and support the marking of the human workstation position, providing accurate spatial perception capabilities for the printing robot to autonomously navigate to the target position.

[0046] Status monitoring module and wireless communication module: The status monitoring module monitors various status parameters of the printing robot in real time, including but not limited to network status, remaining battery power, current location, distance to the nearest charging station, distance to the target location, remaining toner, and remaining paper quantity. It then reports these status parameters to the scheduling server via the wireless communication module. The wireless communication module supports multiple wireless transmission technologies such as Wi-Fi, Bluetooth, and Zigbee for data interaction with the scheduling server and base station, including transmitting print files, receiving control commands, and reporting status information.

[0047] The scheduling server, acting as the control center of the entire system, establishes a communication connection with each printing robot via a wireless communication module. The scheduling server can share employee information (such as work card information, facial information, workstation location, etc.), receive scanned images and documents to be printed from user terminals, and forward control commands to the printing robots, including but not limited to: controlling the printing robot to move to a fixed position, controlling the robot to autonomously navigate according to a specified map and path, and controlling the printing robot's screen to play promotional videos, praise images, holiday notices, and other multimedia content.

[0048] The aforementioned functional modules work together to enable the printing robot to not only possess complete autonomous movement and printing capabilities, but also to report its own multi-dimensional status data in real time. This provides a data foundation for the scheduling server to execute the multi-dimensional dynamic evaluation and scheduling method provided in this application. By comprehensively considering the current values ​​and dynamic weights of multiple evaluation factors such as the remaining power, paper balance, consumable balance, equipment health, and target distance of each printing robot, the scheduling server can make scheduling decisions from a globally optimal perspective, thereby improving the overall operation efficiency and equipment resource utilization of the system.

[0049] Based on the above embodiments, this application also provides a job scheduling method for a printing robot, applied to a scheduling server. The scheduling server is configured with multiple evaluation factors for assessing the printing robot, each evaluation factor having a corresponding baseline weight and a judgment threshold. Figure 3 As shown, the method may include the following steps: In step S310, the current value of each printing robot corresponding to each evaluation factor is obtained.

[0050] In this embodiment, the evaluation factors may include: remaining battery power, remaining paper, remaining consumables, equipment health, and target distance; the target distance may be determined based on the distance from the current location of the printing robot to the target location.

[0051] The scheduling server maintains communication with each printing robot via a wireless communication module. Each printing robot's status monitoring module collects multiple status parameters in real time, including but not limited to remaining battery power, paper balance, consumable balance, device health, and current position, and periodically or proactively reports these to the scheduling server when their status changes. Based on the received status data, the scheduling server obtains the current value of each evaluation factor for each printing robot. For the target distance evaluation factor, its current value is obtained after normalization based on the distance between the printing robot's current position and the target position.

[0052] In step S320, it is determined whether the current value of each evaluation factor exceeds the corresponding judgment threshold, and the judgment result is obtained.

[0053] The scheduling server can compare the current values ​​of each evaluation factor obtained in step S310 with the preset corresponding judgment thresholds one by one. For example, the judgment threshold for remaining power can be set to 20%, that is, when the remaining power is less than 20%, it is considered that the judgment threshold has been exceeded; the judgment threshold for remaining paper can be set to 10%; the judgment threshold for remaining consumables can be set to 10%; the judgment threshold for equipment health can be set to 30%; and the judgment threshold for target distance can be set to 20%. It should be noted that the specific values ​​of the above thresholds can be adjusted according to the actual application scenario and experience data, and the embodiment does not specifically limit them.

[0054] In step S330, based on the judgment result, the actual weight ratio corresponding to each evaluation factor is determined according to the preset weight adjustment rules.

[0055] The embodiment uses a threshold-triggered dynamic weight adjustment mechanism. When one or more key evaluation factors of the printing robot reach the judgment threshold, it indicates that the robot has obvious shortcomings or risks in the corresponding dimension. At this time, by dynamically increasing the weight of the evaluation factor, the comprehensive score can more sensitively reflect the impact of the shortcomings on the overall service capability.

[0056] In step S340, the comprehensive scheduling score for each printing robot is calculated. The comprehensive scheduling score is determined based on the current value of the evaluation factor and its corresponding actual weight ratio.

[0057] After determining the actual weight ratio of each evaluation factor, the scheduling server multiplies the current score of each evaluation factor for each available printing robot by its corresponding actual weight ratio, and then sums all the products to obtain the overall scheduling score for that printing robot. This overall scheduling score can be represented by the Service Ability Index (SAI). This overall scheduling score comprehensively reflects the overall suitability of the printing robot to complete the assigned task at the current moment, given the actual values ​​of each evaluation factor.

[0058] In this embodiment of the application, the central scheduling server calculates a SAI for each printing robot, which can be used to quantitatively evaluate the overall suitability of the printing robot in performing the assigned task.

[0059] In one alternative implementation, the Service Capability Index (SAI) is calculated using the following formula: SAI = α×a + β×b + γ×c + δ×d + ε×e (1) Where a represents the current value of remaining battery power, b represents the current value of remaining paper, c represents the current value of remaining consumables, d represents the current value of equipment health, and e represents the current value of target distance. a, b, c, d, and e are the current values ​​of each evaluation factor obtained in step S310, and these values ​​can be expressed as percentages or normalized values. α, β, γ, δ, and ε represent the actual weight ratios corresponding to the five evaluation factors: remaining battery power, remaining paper, remaining consumables, equipment health, and target distance. These actual weight ratios are dynamically determined in step S330 based on the judgment results and preset weight adjustment rules. Each actual weight ratio satisfies the following relationship: α + β + γ + δ + ε = 100%.

[0060] It should be noted that the current target distance value can be obtained through normalization to eliminate the influence of distance dimensions and make it comparable to the current values ​​of other evaluation factors. In an optional implementation, the current target distance value is calculated according to the following formula: Current distance to target = (Maximum distance set - walking distance to target) / Maximum distance set (2) The maximum distance is set as a preset distance parameter, which can be configured according to the actual deployment environment (such as the maximum span of a building); the walking distance to the target is the distance the printing robot needs to walk from its current position to the target position along the planned path. As can be seen from the above formula, the closer the printing robot is to the target position, the larger its current target distance value (closer to 1 or 100%), and the greater its contribution to SAI in the weighted calculation, which conforms to the scheduling logic that closer proximity is more suitable for job execution.

[0061] In this way, the scheduling server can comprehensively consider the real-time status of each printing robot in multiple dimensions such as resource status, equipment health and task distance when making a scheduling decision, and dynamically adjust the weight allocation according to whether each evaluation factor reaches the judgment threshold, so that the calculated service capability index can accurately reflect the real service capability of the printing robot and provide a basis for subsequent scheduling decisions.

[0062] In step S350, the printing robot to be assigned the task is determined based on the comprehensive scheduling score.

[0063] The scheduling server compares the overall scheduling scores of all available printing robots and selects the printing robot with the highest overall scheduling score as the target robot to which it assigns tasks. The higher the overall scheduling score, the more suitable the printing robot is for undertaking new tasks.

[0064] This application embodiment dynamically determines whether any factors exceed the judgment threshold based on the real-time acquired current values ​​of evaluation factors for each printing robot across multiple dimensions, and adaptively adjusts the actual weight ratio of each evaluation factor according to a preset weight adjustment rule. When the printing robot's various factors are in good condition, a balanced baseline weight is used for comprehensive scoring; when a factor is abnormal, its weight is amplified to make the scoring sensitively reflect potential risks; when multiple factors are abnormal simultaneously, the weights of non-abnormal factors are reset to zero, and scoring is based solely on the abnormal factor, ensuring that the printing robot is less likely to be mistakenly selected. The comprehensive scheduling score calculated in this way can accurately and realistically reflect the current service capability of the printing robot, enabling the scheduling server to make scheduling decisions from a globally optimal perspective, avoiding assigning jobs to printing robots with hidden defects, thereby significantly reducing the risk of interruption and failure rate during job execution, and effectively improving the overall job execution efficiency and resource utilization of the multi-printing robot system.

[0065] In this embodiment, the aforementioned weight adjustment rules may specifically include: (1) When the current value of all evaluation factors does not exceed the corresponding judgment threshold, all evaluation factors shall determine the actual weight ratio according to the first weight ratio equal to their respective benchmark weights.

[0066] When the current values ​​of all evaluation factors do not exceed their corresponding judgment thresholds, it indicates that the printing robot is in good condition in all aspects and has no obvious shortcomings. At this time, the actual weight ratio of all evaluation factors is determined according to a first weight ratio equal to their respective baseline weights. In one example, the baseline weights of each evaluation factor can be set as follows: remaining battery power 30%, remaining paper 25%, remaining consumables 20%, equipment health 5%, and target distance 20%.

[0067] (2) When the current value of an evaluation factor exceeds the corresponding judgment threshold, the evaluation factor that exceeds the judgment threshold shall determine the actual weight ratio according to the preset over-threshold weight ratio, and the actual weight ratio of the remaining evaluation factors shall be reduced to the second weight ratio according to their respective benchmark weights.

[0068] When the current value of an evaluation factor exceeds its corresponding threshold, the evaluation factor exceeding the threshold is assigned an actual weight ratio according to a preset threshold weight ratio. The actual weight ratios of the remaining evaluation factors are proportionally reduced to a second weight ratio based on their respective baseline weights. In this case, the individual factor exceeding the threshold is given a significantly increased weight to highlight the impact of that weakness, while the remaining factors retain a certain weight to maintain the comprehensiveness of the score. The specific values ​​of the threshold weight ratio and the second weight ratio for each evaluation factor can be preset based on empirical data and stored in the scheduling server.

[0069] The over-threshold weight ratio refers to a specific weight value, significantly higher than the baseline weight, assigned to an evaluation factor when its current value exceeds its corresponding judgment threshold. This over-threshold weight ratio is a pre-set, fixed parameter stored in the scheduling server. Its function is to significantly increase the weight of the abnormal dimension in the comprehensive score when the printing robot exhibits an anomaly in a certain dimension. This ensures that the final calculated comprehensive scheduling score can sensitively and accurately reflect the negative impact of the anomaly on the overall service capability of the printing robot, thereby effectively avoiding assigning jobs to potentially risky equipment in scheduling decisions. For example, if the baseline weight of remaining battery power is 30%, and its corresponding over-threshold weight ratio is 60%, then when the remaining battery power of a printing robot falls below the judgment threshold of 20%, the actual weight of this evaluation factor, remaining battery power, is directly increased from 30% to 60%, ensuring that the risk factor of insufficient battery power dominates the scoring. The over-threshold weight ratio can be set according to specific circumstances, and the embodiments are not limited to this.

[0070] (3) When there are two or more evaluation factors whose current values ​​exceed the corresponding judgment threshold, the ratio of the benchmark weight of each of the two or more evaluation factors that exceed the judgment threshold to the sum of the benchmark weights of all evaluation factors that exceed the judgment threshold shall be used as the actual weight ratio of the corresponding evaluation factor, and the actual weight ratio of the remaining evaluation factors that do not exceed the judgment threshold shall be determined as zero.

[0071] When two or more evaluation factors have current values ​​exceeding their corresponding judgment thresholds, it indicates that the printing robot has serious defects in multiple dimensions and lacks the basic conditions for reliable task execution. In this case, the proportion of the baseline weight of each of the two or more evaluation factors exceeding the judgment threshold to the sum of the baseline weights of all evaluation factors exceeding the judgment threshold is used as the actual weight proportion of the corresponding evaluation factor, while the actual weight proportion of the remaining evaluation factors that do not exceed the judgment threshold is set to zero. Through this rule, the scoring calculation focuses entirely on the factors that have problems, ensuring that the overall scheduling score of the printing robot truly reflects its current unsuitability for undertaking new tasks, thus effectively excluding it from scheduling decisions.

[0072] For example, consider a printing robot. The robot's remaining battery power is currently 18%, below the 20% threshold; the remaining paper is currently 8%, below the 10% threshold. The base weights for these two factors are 30% and 25% respectively, totaling 55%. According to the weight adjustment rules of this embodiment, the actual weight ratio of remaining battery power = 30% / (30% + 25%) ≈ 55%; the actual weight ratio of remaining paper is = 25% / (30% + 25%) ≈ 45%. However, the three evaluation factors for which the printing robot performs well—remaining consumables, equipment health, and target distance—although their current values ​​do not trigger the thresholds, have their actual weight ratios set to zero. Therefore, the calculated comprehensive scheduling score only reflects the robot's true condition in these two weaknesses, significantly lowering its score and effectively excluding it from the scheduling decision.

[0073] Through the aforementioned weighting adjustment rules, this embodiment, in the extreme case where multiple factors simultaneously trigger thresholds, focuses the scoring entirely on the dimensions where problems have occurred. This prevents printing robots with insufficient key resources from obtaining artificially high overall scheduling scores based on good performance in other dimensions. This mechanism effectively avoids selecting printing robots with a high probability of failure as target devices, further ensuring the rationality of job assignment and the success rate of execution.

[0074] In this embodiment of the application, the weight adjustment rule in step S330 can be pre-configured and stored in the scheduling server. For ease of understanding, the following example, using a specific parameter configuration, illustrates the specific values ​​of the over-threshold weight ratio and the second weight ratio in the case of "when the current value of an evaluation factor exceeds the corresponding judgment threshold" in the weight adjustment rule.

[0075] In one optional configuration, the baseline weights, decision thresholds, and weight adjustment schemes for each evaluation factor are shown in Table 1 below: Table 1:

[0076] Based on the configuration content in the table above, it can be seen that when a certain evaluation factor of a printing robot triggers a preset judgment threshold, the scheduling server significantly increases the weight of that factor from the baseline weight to the super-threshold weight ratio. At the same time, the weights of the other factors are reduced proportionally according to their respective baseline weights, and the sum of the reduced weights and the super-threshold weights is still 100%.

[0077] For example, when the remaining battery power of the printing robot is below 20%, the actual weight of the remaining battery power increases from the default 30% to 60%. The actual weights of the other four evaluation factors are proportionally reduced according to the formula "default weight × (1-60%) / (1-30%)". That is, the weight of paper balance is adjusted to approximately 14%, the weight of consumable balance is adjusted to approximately 11%, the weight of equipment health is adjusted to approximately 3%, and the weight of target distance is adjusted to approximately 11%, while the sum of all actual weights remains 100%. Similarly, when the remaining paper balance is below 10%, the actual weight of the remaining paper balance increases to 60%, and the weights of the other factors are proportionally reduced; when the remaining consumable balance is below 10%, the actual weight of the remaining consumable balance increases to 50%, and the weights of the other factors are proportionally reduced; when the equipment health is below 30%, the actual weight of the equipment health increases to 30%, and the weights of the other factors are proportionally reduced; when the current target distance is below 20%, the actual weight of the target distance increases to 50%, and the weights of the other factors are proportionally reduced.

[0078] Through the aforementioned dynamic weight adjustment mechanism, this application embodiment can quickly enhance the influence of a certain evaluation factor in the overall score when a certain evaluation factor becomes abnormal, so that the overall scheduling score of the printing robot can sensitively reflect potential operational risks and avoid assigning jobs to equipment with obvious shortcomings, thereby effectively ensuring the success rate of job execution and the overall operating efficiency of the system.

[0079] Based on the weight adjustment rules listed in the parameter configuration example above, when each evaluation factor triggers the threshold under different combinations, the actual weight ratio of each factor after reallocation can be shown in Table 2 below.

[0080] Table 2:

[0081] Table 2 clearly shows the actual weight ratios of each evaluation factor under different threshold triggering scenarios. Among them, weight 0 is the default baseline weight when none of the evaluation factors trigger the threshold. Weights 1 to 5 correspond to the actual weight ratios of each factor when only one of the five factors—remaining power, remaining paper, remaining consumables, equipment health, and target distance—triggers the threshold. The last column provides an example of the weight allocation results calculated according to the above rule (3) when both remaining power and remaining paper trigger the threshold. That is, the two factors that reach the threshold are allocated the total weight according to their respective default weight ratios (remaining power 30% / (30%+25%)≈55%, remaining paper 25% / (30%+25%)≈45%), and the weights of the remaining factors that do not trigger the threshold are reset to 0%.

[0082] As can be seen from Table 2 above, through the dynamic weight adjustment rules provided in the embodiments of this application, when the printing robot is abnormal in a certain dimension, the weight of the abnormal dimension in the comprehensive score is significantly amplified; when multiple dimensions are abnormal at the same time, the scoring weight is completely concentrated on the abnormal dimension, so that the robot's comprehensive scheduling score can truly reflect its current state of not being suitable for undertaking new tasks, thereby effectively avoiding assigning tasks to equipment with potential risks.

[0083] Therefore, as shown in Table 2, when only one factor among all evaluation factors has a current value exceeding its corresponding threshold, the actual weight ratio of that factor is adjusted from the baseline weight to the preset threshold weight ratio; for the remaining evaluation factors that have not triggered the threshold, their actual weight ratios are reduced proportionally according to their respective baseline weights to ensure that the sum of all weights remains 100%. The specific calculation method for proportional reduction is as follows: the actual weight of each remaining factor = the baseline weight of that factor × (1 - threshold weight ratio) / (1 - the baseline weight of the factor that triggered the threshold). For example, referring to Table 2, when the remaining power of the printing robot is less than 20%, the actual weight of the remaining power is increased from the default 30% to 60%, and the actual weights of the other factors are adjusted as follows: paper balance weight = 25% × (1-60%) / (1-30%) ≈ 14%, consumable balance weight = 20% × (1-60%) / (1-30%) ≈ 11%, equipment health weight = 5% × (1-60%) / (1-30%) ≈ 3%, target distance weight = 20% × (1-60%) / (1-30%) ≈ 12% (wherein, in order to ensure that the sum of each column in Table 2 is 100%, the target distance weight is assigned 12% here, and the other columns in Table 2 are similar, and the embodiment is not limited to this).

[0084] In this embodiment, if two factors among all evaluation factors have current values ​​exceeding their corresponding judgment thresholds, only these two triggering threshold evaluation factors are retained for scoring calculation. The actual weight ratio of these two factors is allocated according to their respective baseline weights relative to the sum of their baseline weights. The actual weight ratio of all other evaluation factors that have not triggered thresholds is set to zero. For example, when both remaining battery power and remaining paper are below their respective judgment thresholds, their actual weights are calculated as follows: Remaining battery power weight = 30% / (30% + 25%) ≈ 55%, remaining paper weight weight = 25% / (30% + 25%) ≈ 45%, and the weights of remaining consumables, equipment health, and target distance are all 0%.

[0085] In this embodiment, when the current values ​​of three or more evaluation factors exceed the corresponding judgment thresholds, the processing method is similar to the above principle, that is, only all evaluation factors that trigger the thresholds are retained to participate in the scoring calculation, and the actual weight ratio of these trigger threshold factors is allocated according to the ratio of their respective benchmark weights to the sum of the benchmark weights of all trigger threshold factors, and the actual weight ratio of the remaining evaluation factors that do not trigger the thresholds is set to zero.

[0086] By employing the aforementioned hierarchical, threshold-triggered dynamic weight adjustment principle, this embodiment of the application can comprehensively evaluate a printing robot using a balanced baseline weight when the robot is in good condition, amplify the scoring influence of the abnormal dimension when an anomaly occurs in a single dimension, and focus entirely on the abnormal dimension when serious defects occur simultaneously in multiple dimensions. This adaptive weight allocation mechanism enables the comprehensive scheduling score to sensitively and accurately reflect the true service capabilities of each printing robot, providing a reliable decision-making basis for the scheduling server to select the optimal target robot.

[0087] In the embodiments, a comparative analysis is conducted below using a specific application example involving 6 printing robots.

[0088] Suppose that six printing robots are deployed simultaneously in an office environment: printing robot A, printing robot B, printing robot C, printing robot D, printing robot E, and printing robot F. At a certain scheduling moment, the scheduling server obtains the current values ​​of each printing robot for five evaluation factors (each current value is a percentage, with a maximum of 100 points and a minimum of 0 points), as shown in Table 3 below.

[0089] Table 3:

[0090] According to the weight adjustment rules provided in this application, the scheduling server first performs a threshold judgment on the current value of the evaluation factors for each printing robot to determine the applicable weight type for each printing robot: Printing Robot A: None of the current values ​​of the evaluation factors have triggered the corresponding judgment thresholds (remaining power 70%>20%, remaining paper 40%>10%, remaining consumables 40%>10%, equipment health 70%>30%, target distance 20%≥20%), so the default weight is applied, i.e., weight 0.

[0091] Printing Robot B: The target distance is currently 18%, which is lower than the 20% threshold. None of the other factors have triggered the threshold, so this is a case of a single factor triggering the threshold, and a weight of 5 applies.

[0092] Printing Robot C: The current consumable balance is 8%, which is lower than the 10% threshold. None of the other factors have triggered the threshold, so it is a case of a single factor triggering the threshold, and the applicable weight is 3.

[0093] Printing Robot D: None of the current values ​​of the evaluation factors have triggered the corresponding judgment thresholds, so the default weights are applied, i.e., weights of 0.

[0094] Printing Robot E: The current remaining power is 15%, which is lower than the 20% threshold. None of the other factors have triggered the threshold, so it is a case of a single factor triggering the threshold, and the applicable weight is 1.

[0095] Printing robot F: The current remaining power is 18%, which is lower than the 20% threshold; the current remaining paper is 8%, which is lower than the 10% threshold. Both factors trigger the thresholds simultaneously, so principle two applies: the weight of remaining power = 30% / (30%+25%)≈55%, the weight of remaining paper = 25% / (30%+25%)≈45%, and the weight of other factors is 0%.

[0096] The comparison in Table 3 above clearly shows that: If a traditional fixed-weight scoring method is used, printing robot F scores 50 points, ranking highest among all printing robots. The scheduling server would then prioritize printing robot F as the target robot for job assignment. However, considering the current values ​​of the aforementioned evaluation factors, printing robot F has only 18% battery remaining and 8% paper remaining, both critical resources severely depleted. Despite its excellent performance in terms of consumables remaining, equipment health, and target distance, it is highly likely that the task will fail due to battery depletion or paper exhaustion during execution. Therefore, selecting printing robot F for the task is unreasonable and carries a high risk of task failure.

[0097] In contrast, using the method provided in this application, since both the remaining battery power and paper balance of printing robot F trigger the threshold, according to principle two above, the scheduling server calculates its SAI score based only on the remaining battery power (weight 55%) and paper balance (weight 45%), resulting in a score of 13 (18×55%+8×45%≈13.5, rounded to 13), the lowest score among all printing robots. Printing robot A, however, has a balanced state across all evaluation factors and has not triggered any thresholds. Its fixed-weight SAI score and dynamic-weight SAI score are both 47, ranking highest among the available robots. Therefore, the scheduling server selects printing robot A, which has the most balanced and healthiest overall state, as the target robot for the job, effectively avoiding the risk of assigning the job to a potentially problematic device.

[0098] Furthermore, during actual operation, the current values ​​of the evaluation factors for each printing robot change dynamically. For example, as the robot moves and performs tasks, the remaining power is gradually consumed, the target distance changes accordingly, and paper and consumables gradually decrease. Whenever the current value of any evaluation factor for any printing robot changes and triggers or exits the judgment threshold, the scheduling server can recalculate the robot's SAI score in the next scheduling cycle or when a new job arrives, thus achieving real-time dynamic tracking of the service capabilities of each printing robot.

[0099] Furthermore, experiments can be conducted to obtain empirical data on the resource consumption of each printing robot when performing typical tasks. For example, in the application environment assumed in this example, the experiment yielded the following empirical data: the printing robot consumes 1% of its power for every 100 meters it travels; it consumes 2% of its power for every 100 pages it prints; and it consumes 3% of its consumables for every 100 pages it prints. The scheduling server can combine the above empirical data with the estimated workload of the tasks to be assigned (such as estimated travel distance and number of pages printed) to predict the current values ​​of each evaluation factor after the task is executed. This allows the server to further consider the state changes after task execution when calculating the SAI score, thereby further improving the accuracy and foresight of scheduling decisions.

[0100] In summary, this application's embodiment, through a threshold-triggered dynamic weight adjustment mechanism, effectively eliminates printing robots with serious deficiencies in key resource dimensions, avoiding the misselection problems that may occur with traditional fixed-weight scoring methods. The system ultimately selects the printing robot with the most balanced overall state and the most suitable for performing the job, thereby significantly improving the job execution success rate and the overall system operating efficiency.

[0101] Based on the above embodiments, in another embodiment provided in this application, the method may further include the following steps: In step S360, the print job issued by the user is received and placed in the job pool to be processed.

[0102] Users submit print, scan, or copy jobs to the scheduling server via their terminals. These jobs may include parameters such as user identification information, target location information, job type, and workload. Upon receiving the job, the scheduling server places it in a pending job pool for unified management. The pending job pool is a collection of jobs maintained by the scheduling server, used to store all received but not yet assigned or completed jobs. Users do not need to manually specify the specific printing robot to execute the job on their terminals; the scheduling server will automatically select the optimal device and assign the job in subsequent steps.

[0103] In step S370, when a new job is added to the job pool, or at preset time intervals, the overall scheduling score of each printing robot is recalculated.

[0104] In this embodiment, the scheduling server employs a dual-trigger mechanism for recalculating the overall scheduling score. The first trigger condition is event-triggered, meaning that when a new job is added to the job pool, the scheduling server immediately initiates a global score calculation. The second trigger condition is timed-triggered, meaning that regardless of whether a new job is added, the scheduling server automatically initiates a global score calculation every preset time period (e.g., every 5 minutes). This dual-trigger mechanism ensures both rapid response when a new job arrives and that the system can periodically perceive the dynamic changes in the status of each printing robot and adjust the scheduling strategy accordingly. During each recalculation, the scheduling server follows the methods described in steps S310 to S340 above to obtain the latest current values ​​of the evaluation factors for each printing robot, performs threshold judgment and dynamic weight adjustment, and then calculates the updated overall scheduling score for each printing robot.

[0105] In step S380, based on the comprehensive scheduling score of each printing robot, all unassigned jobs in the job pool to be processed and jobs that have been assigned to each printing robot but have not yet been completed are reassigned, and a scheduling table is generated or updated; wherein, the scheduling table contains the printing robot and delivery path information corresponding to the job assignment.

[0106] In this step, the scheduling server is not limited to assigning only newly added individual jobs, but also performs a global re-planning of all incomplete jobs within the system based on the updated comprehensive scheduling scores of each printing robot. Specifically, the scheduling server includes unassigned jobs in the pending job pool, along with jobs already dispatched to printing robots but not yet started or in progress, into the scope of re-assignment. Based on the current comprehensive scheduling score ranking of each printing robot, each job is re-matched to the most suitable printing robot, and a corresponding delivery path is planned for each job. After completing the global re-planning, the scheduling server generates a new scheduling table or updates the existing one. The scheduling table includes at least the job identifier, the target printing robot identifier, and the planned path information for that job. When the task sequence or path of a printing robot changes, the scheduling server synchronously sends the updated scheduling information to the corresponding printing robot via the wireless communication module, and the printing robot adjusts its job execution order and travel path accordingly.

[0107] The method provided in this embodiment enables complete closed-loop scheduling from job reception, status awareness, dynamic scoring to global replanning. Unlike existing technologies that allocate tasks independently for each new job, this embodiment deeply integrates task scheduling and path planning through periodic or event-driven reallocation under a dual-trigger mechanism. When the status of any printing robot changes (e.g., battery power decreases, resources are released after completing a task) or a high-priority task is added, the global job allocation scheme and travel path can be automatically adjusted to minimize the total execution path of all tasks and balance the load of each printing robot, thereby continuously maintaining the optimal state of overall system job execution efficiency in a dynamically changing multi-robot environment.

[0108] Based on the above embodiments, in another embodiment provided in this application, to further improve the system's fault tolerance and job execution reliability, the scheduling server introduces a job timeout detection and automatic job recycling mechanism after job dispatching. Specifically, the method may further include the following steps: In step S381, when the target printing robot executes the target job dispatched based on the scheduling table, the scheduling server sets a timeout period for the target job.

[0109] When dispatching jobs to the target printing robot, the scheduling server sets a corresponding timeout for each dispatched job based on attributes such as job type, workload, and complexity. For example, jobs that print more pages or cover a longer distance can have a longer timeout, while simple single-page printing jobs can have a shorter timeout. The timeouts for each job type can be pre-configured and stored in the scheduling server for use during dispatch.

[0110] In this embodiment, the timeout period can be determined based on the type and / or complexity of the dispatched job and pre-configured and stored in the scheduling server. Job types may include print jobs, scan jobs, and copy jobs, with different types having different execution times. For example, scan jobs typically only involve page-by-page scanning of the original and image transmission, and their execution speed is relatively fast; print jobs may include a travel process in addition to printing output; copy jobs combine both scanning and printing, and typically take longer. Job complexity may include factors such as the number of pages, file size, and estimated travel distance. For example, the more pages, the larger the file, and the longer the travel distance, the longer the execution time required for the job will increase accordingly.

[0111] The scheduling server can comprehensively consider the job type and / or complexity information mentioned above to estimate a reasonable expected execution time for each dispatched job, and add a certain time redundancy to this expected time to determine the timeout period for the job. The timeout period set in this way can adapt to the actual execution needs of different types and scales of jobs, avoiding frequent false alarms due to excessively short timeouts, and can also promptly activate the timeout recovery mechanism when real anomalies occur during job execution, ensuring the accuracy and timeliness of anomaly detection.

[0112] In step S382, if the target job is not completed within the timeout period, the status information of the target printing robot is obtained.

[0113] The scheduling server monitors the execution time of each dispatched job. When the execution time of a job exceeds its set timeout period without receiving a completion confirmation from the printing robot, the scheduling server proactively sends a status query request to the corresponding target printing robot to obtain its current status information. This status information may include network connection status, remaining battery power, current job execution progress, and fault codes. This mechanism is particularly suitable for scenarios where the printing robot is passively disconnected due to communication interruptions or unexpected power outages. In such cases, the scheduling server cannot obtain information about the robot's abnormal status through proactive reporting, making timeout detection a crucial means of detecting anomalies.

[0114] In step S383, when it is determined based on the status information that the target printing robot cannot continue to perform the target job, the target job is marked as an abnormal job and the abnormal job is recycled to the job pool to be processed.

[0115] The scheduling server determines whether the printing robot is capable of continuing its job based on the acquired status information. If the status information indicates that the printing robot cannot continue its job due to hardware failure, power depletion, consumable exhaustion, path blockage, or communication interruption, the scheduling server marks the target job as an abnormal job, removes it from the current printing robot's task sequence, and reclaims it in the pending job pool for reassignment. Simultaneously, if there are other unfinished jobs on the printing robot, the scheduling server can also reclaim these jobs.

[0116] In step S384, the abnormal job is reassigned, and the abnormal job is assigned a higher priority than the non-abnormal job.

[0117] Abnormal jobs returned to the pending job pool are given a higher priority than newly assigned jobs when they are re-scheduled. When the scheduling server performs the next round of reallocation, it prioritizes assigning suitable printing robots to these abnormal jobs. The purpose of this is that abnormal jobs have already experienced an execution interruption, and user waiting time has exceeded expectations. By increasing their priority, it ensures that the job is processed as quickly as possible after the system restores available resources, reducing the overall user waiting time and improving the user experience.

[0118] Through the aforementioned task timeout detection and automatic job recovery mechanism, when the printing robot is unable to actively report due to communication interruptions, power outages, or other reasons, the scheduling server can still promptly detect the problem and recover the job through the timeout detection mechanism. This ensures that all jobs can be recovered in a timely manner and reassigned to other healthy printing robots for execution, achieving seamless job takeover and automatic recovery, and significantly improving the overall robustness of the system and the job execution success rate.

[0119] Based on the above embodiments, in another embodiment provided in this application, to further improve the exception handling system, the scheduling server also sets up a response handling mechanism for exceptions actively reported by the printing robot. Specifically, the method may further include the following steps: In step S391, an abnormal notification message is received from the target printing robot. The abnormal notification message indicates that the target printing robot is unable to continue performing the currently assigned target job due to an abnormal reason.

[0120] During actual operation, the printing robot continuously monitors key parameters through its own status monitoring module. When it detects an abnormality that prevents it from completing assigned jobs, the printing robot proactively sends an anomaly notification to the scheduling server. This notification may include the anomaly type, current job progress, and a list of unfinished jobs. Possible causes of anomalies include, but are not limited to: hardware malfunction (such as damaged printing components or jammed wheels), depletion of consumables (such as running out of toner or ink), insufficient power (insufficient remaining power to support the current job and its return journey), and path obstruction (the planned path is blocked by obstacles and cannot be bypassed).

[0121] In step S392, based on the abnormal notification information, all unfinished jobs corresponding to the target printing robot are collected and reassigned, and the target printing robot is marked as offline.

[0122] Upon receiving an anomaly notification from the printing robot, the scheduling server performs the following actions: First, it reclaims all dispatched but unexecuted or incomplete jobs on the target printing robot and moves them to the pending job pool. Second, it marks the target printing robot as offline, preventing it from participating in subsequent comprehensive scheduling score calculations and job assignments, thus avoiding the assignment of new jobs to already faulty equipment. Simultaneously, the scheduling server generates a maintenance notification and sends it to maintenance personnel, informing them that the corresponding printing robot has experienced an anomaly and requires maintenance or consumable replenishment. Jobs reclaimed to the pending job pool will be reassigned in subsequent scheduling processes according to the aforementioned global reallocation mechanism, prioritizing or sequentially assigning them to other healthy printing robots with higher comprehensive scheduling scores.

[0123] Through the aforementioned robot-initiated anomaly feedback mechanism, this embodiment can function alone or in conjunction with the server-side timeout detection mechanism to form a complete dual-mode anomaly detection and processing closed loop. When the printing robot possesses autonomous perception and proactive communication capabilities, it can proactively report anomaly information, immediately notifying the scheduling server of the fault situation and triggering rapid job recovery and redistribution, minimizing job interruption time. When the printing robot is unable to proactively report due to extreme circumstances such as communication interruption or power outage, the scheduling server passively detects the anomaly and intervenes through the timeout detection mechanism. These two mechanisms complement each other, covering various possible fault scenarios and ensuring that, under any anomaly, user-issued jobs can be automatically taken over and ultimately completed by the system. Users do not need to manually intervene or resubmit jobs, achieving truly seamless fault-tolerant scheduling and significantly improving the reliability and user experience of the entire printing robot service system.

[0124] Based on the above embodiments, in another embodiment provided in this application, in order to detail how to recover all unfinished jobs corresponding to the target printing robot, step S392 may specifically include the following steps: In step S3921, a recycling robot is determined from the normal printing robots other than the target printing robot to perform the recycling operation.

[0125] When the scheduling server receives an anomaly notification from the target printing robot, or confirms through a timeout detection mechanism that the target printing robot cannot continue its work, in addition to marking the target printing robot as offline, it also needs to reclaim any unfinished tasks. In this embodiment, the reclamation operation is not performed manually, but rather the scheduling server selects one of the normal printing robots in the current system (excluding the target printing robot) as the reclamation robot. The selection of the reclamation robot can be based on the aforementioned multi-dimensional dynamic evaluation mechanism, i.e., calculating the comprehensive scheduling score of each normal printing robot, and selecting the printing robot with the highest comprehensive scheduling score and relatively close to the target printing robot as the reclamation robot, to ensure the efficiency and reliability of the reclamation operation.

[0126] In step S3922, all unfinished jobs corresponding to the target printing robot are recovered by the recycling robot.

[0127] After identifying the retrieval robot, the scheduling server issues a retrieval command to it. This command includes the target printing robot's current location and a list of jobs to be retrieved. Upon receiving the command, the retrieval robot autonomously moves to the target printing robot's location, following a path planned by its positioning and navigation module. Upon arrival, the retrieval robot establishes a short-range wireless communication connection with the target printing robot to obtain electronic data (such as documents to be printed, scanned task information, etc.) corresponding to unfinished jobs on the target robot. Alternatively, for printed but not yet delivered paper documents in the target printing robot's intelligent storage compartment, the retrieval robot can retrieve them using a robotic arm or other transfer mechanism and transfer them to its own intelligent storage compartment. After completing the data and / or document retrieval, the retrieval robot reports the retrieved job data to the scheduling server via its wireless communication module. The scheduling server then places the retrieved jobs into a pending job pool, awaiting subsequent redistribution.

[0128] Through the above steps, in this embodiment, when a printing robot malfunctions and cannot continue its work, the scheduling server does not need to wait for manual intervention. Instead, it automatically assigns another healthy printing robot as a retrieval robot to proactively retrieve the unfinished job from the malfunctioning robot. The retrieval process is completed autonomously and collaboratively by the system. The retrieved job is reinstated into the pending job pool and participates in global scheduling, ultimately being executed by another healthy printing robot until completion. This mechanism effectively reduces the cost of manual intervention and job delays caused by robot malfunctions, further enhancing the automation level and fault tolerance of the entire printing robot service system.

[0129] Figure 4 This is a schematic diagram of a real-time scheduling process provided in an embodiment of this application. Figure 4As shown, this process demonstrates the complete closed-loop process of the scheduling server from receiving user jobs to completing job dispatch and exception handling, specifically including the following main steps: S41, Distribute the assignment.

[0130] Users submit print, scan, or copy jobs to the scheduling server via their terminals. Upon receiving the job, the scheduling server places it in a pending job pool for unified management. The pending job pool is a collection of jobs maintained by the scheduling server, used to store all received but not yet assigned or completed jobs.

[0131] S42, calculate the overall scheduling score for each printing robot.

[0132] The scheduling server triggers global scheduling calculations in two scenarios: first, when a new job is added to the pending job pool (event trigger); and second, at preset time intervals (e.g., every 5 minutes) (timed trigger). After triggering, the scheduling server obtains the current values ​​of each printing robot within the system for each evaluation factor, including remaining battery power, paper balance, consumable balance, equipment health, and target distance. Based on whether the current value of each evaluation factor exceeds the corresponding threshold, the actual weight ratio of each evaluation factor is determined according to preset weight adjustment rules, and then the Service Capability Index (SAI) of each printing robot, i.e., the comprehensive scheduling score, is calculated.

[0133] S43, Dispatch the task.

[0134] The scheduling server, based on the overall scheduling score of each printing robot, reallocates all unassigned jobs in the job pool and jobs already assigned to printing robots but not yet completed, and generates or updates the scheduling table. The scheduling table contains the target printing robot corresponding to the job assignment and the planned delivery path information for that job. The scheduling server synchronously sends the task information and path information from the scheduling table to the corresponding printing robot A, which then executes the corresponding job.

[0135] S44, report status.

[0136] During job execution, the scheduling server sets a timeout period for each dispatched job. Printing robot A monitors its own status in real time. If it detects that it cannot continue to complete the job due to abnormal reasons such as hardware failure, depletion of consumables, insufficient power, or path blockage, it will proactively send an abnormality notification message to the scheduling server.

[0137] S45, if a timeout or an abnormality occurs, mark printing robot A as offline.

[0138] After receiving the abnormal notification information sent by the printing robot, the scheduling server reclaims all unfinished jobs on the printing robot, puts them back into the pending job pool, marks the printing robot as offline, and generates a maintenance notification information to send to the maintenance personnel.

[0139] On the other hand, if the scheduling server is unable to obtain the job execution status of the printing robot due to communication interruption or power failure, and the job execution time exceeds the preset timeout period, the scheduling server will actively check the status of the printing robot. After confirming that it cannot continue to execute the job, the scheduling server will mark the timed-out job as an abnormal job.

[0140] S46, migrate all jobs to printing robot B.

[0141] The scheduling server retrieves all unfinished jobs from the printing robots and adds them to the pending job pool. After prioritizing these jobs, they are redistributed. This redistribution process re-enters the global scheduling calculation phase, where the scheduling server, based on the latest overall scheduling score of each printing robot, reassigns the retrieved jobs to the healthiest printing robot B with the best overall performance.

[0142] S47, Dispatch work.

[0143] The scheduling server assigns jobs to printing robot B, which has the highest overall scheduling score, based on the latest overall scheduling score of each printing robot.

[0144] S48, takeover confirmed.

[0145] After receiving a job from the scheduling server, printing robot B can send a confirmation message to the scheduling server to take over the job and execute it.

[0146] Through the complete real-time scheduling process described above, this embodiment of the application achieves closed-loop management across the entire chain, from job reception, status awareness, dynamic scoring, global replanning, job dispatch, execution monitoring to anomaly detection and automatic recovery. The system can continuously perceive the status of each device in a dynamically changing multi-robot environment, adaptively adjust scheduling strategies, and automatically recover and take over jobs in various abnormal scenarios, ensuring that all user-issued jobs are ultimately executed reliably.

[0147] It should be noted that, in this embodiment, the scheduling server calculates the overall scheduling score for each printing robot not only at a single moment, but dynamically under multiple triggering conditions to ensure that the scheduling decision reflects the latest status of each printing robot and the system as a whole in real time. Specifically, the scheduling server calculates or recalculates the overall scheduling score for each printing robot under the following circumstances: (1) When a new task arrives.

[0148] When a user submits a new print, scan, or copy job to the scheduling server via their terminal, the job is placed in the pending job pool, and the scheduling server immediately triggers a global comprehensive scheduling score calculation. This mechanism ensures that the new job can be assigned to the most suitable printing robot in the current state for execution in the shortest possible time, achieving rapid response to new jobs.

[0149] (2) When the timer period arrives.

[0150] The scheduling server automatically triggers a global comprehensive scheduling score calculation every preset time period (e.g., every 5 minutes), regardless of whether any new jobs are added during this period. Since the remaining power, paper balance, consumable balance, and current position of each printing robot continuously change over time during operation, the timed calculation mechanism can periodically sense these changes and adjust the comprehensive scheduling score of each printing robot in a timely manner, providing the latest scoring basis for subsequent scheduling decisions.

[0151] (3) When the state of the printing robot changes significantly.

[0152] When the current value of any evaluation factor for a printing robot changes significantly and crosses the corresponding judgment threshold—for example, the remaining battery power drops from above 20% to below 20%, or the paper balance drops from sufficient to below 10%—the printing robot can proactively report a status update to the scheduling server. This triggers the scheduling server to recalculate the overall scheduling score for all printing robots. This event-driven mechanism ensures that the scheduling server can detect and adjust the scoring as soon as a potential risk arises in a printing robot, avoiding the assignment of jobs to devices whose status has deteriorated within the scheduled intervals.

[0153] (4) When the job is completed or an abnormality occurs.

[0154] When a printing robot completes a task, its task queue changes, available resources are released, or a printing robot is unable to continue executing a task due to an abnormality and returns the task, the task allocation pattern within the system changes. At this time, the scheduling server recalculates the overall scheduling score and performs global replanning based on the updated status of each printing robot and the task load.

[0155] (5) When the printing robot joins or leaves the system.

[0156] When a new printing robot registers and joins the system, or when a printing robot is marked as offline and leaves the system due to malfunction, maintenance, or other reasons, the composition of the available robot cluster changes. The scheduling server recalculates the overall scheduling score of the remaining available printing robots and reallocates jobs in the pending job pool.

[0157] By setting the above-mentioned multiple triggering conditions, this application embodiment constructs a dual-trigger mechanism that combines event-driven and timed polling, ensuring that the scheduling server can update the comprehensive scheduling score of each printing robot in a timely manner when various events affecting scheduling decisions occur, so that the scheduling decision is always based on the latest and most accurate equipment status information, thereby ensuring that the system maintains the globally optimal scheduling effect in a dynamically changing multi-robot environment.

[0158] By dividing each functional module according to its corresponding function, this application provides a job scheduling device for a printing robot. The job scheduling device for the printing robot can be a server or a chip applied to a server. Figure 5 A schematic block diagram of the functional modules of a job scheduling device for a printing robot provided as an exemplary embodiment of this application. Figure 5 As shown, the job scheduling device for the printing robot includes: The evaluation factor acquisition module 51 is used to acquire the current value of each printing robot corresponding to each evaluation factor.

[0159] The judgment module 52 is used to determine whether the current value of each evaluation factor exceeds the corresponding judgment threshold and obtain the judgment result.

[0160] The weight adjustment module 53 is used to determine the actual weight ratio of each evaluation factor according to the judgment result and the preset weight adjustment rules.

[0161] The score calculation module 54 is used to calculate the comprehensive scheduling score for each printing robot. The comprehensive scheduling score is determined based on the current value of the evaluation factor and the corresponding actual weight ratio.

[0162] The scheduling module 55 is used to determine the printing robot to perform the assigned job based on the comprehensive scheduling score.

[0163] The weight adjustment rules include: When the current value of all evaluation factors does not exceed the corresponding judgment threshold, the actual weight ratio of all evaluation factors is determined according to the first weight ratio equal to their respective benchmark weights.

[0164] When the current value of an evaluation factor exceeds the corresponding judgment threshold, the evaluation factor exceeding the judgment threshold is assigned an actual weight ratio according to the preset over-threshold weight ratio, and the actual weight ratios of the remaining evaluation factors are reduced to the second weight ratio proportionally according to their respective benchmark weights.

[0165] When the current values ​​of two or more evaluation factors exceed the corresponding judgment threshold, the ratio of the benchmark weight of each of the two or more evaluation factors that exceed the judgment threshold to the sum of the benchmark weights of all evaluation factors that exceed the judgment threshold is used as the actual weight ratio of the corresponding evaluation factor. The actual weight ratio of the remaining evaluation factors that do not exceed the judgment threshold is determined to be zero.

[0166] In another embodiment provided in this application, the evaluation factors include: remaining power, remaining paper, remaining consumables, equipment health, and target distance; the target distance is determined based on the distance from the current location of the printing robot to the target location.

[0167] In another embodiment provided in this application, the device further includes a scheduling table update generation module, specifically used for: The system receives print jobs from users and places them in a job pool. When a new job is added to the job pool, or at preset time intervals, it recalculates the overall scheduling score of each printing robot. Based on the overall scheduling score of each printing robot, it reallocates all unassigned jobs in the job pool and jobs that have been assigned to printing robots but not yet completed, and generates or updates the scheduling table. The scheduling table contains the printing robot and delivery path information corresponding to the job assignment.

[0168] In another embodiment provided in this application, the device further includes a first job dispatch module, specifically used for: When the target printing robot executes the target job dispatched based on the scheduling table, the scheduling server sets a timeout for the target job; if the target job is not completed within the timeout period, the status information of the target printing robot is obtained; if it is determined based on the status information that the target printing robot cannot continue to execute the target job, the target job is marked as an abnormal job and the abnormal job is recycled to the job pool to be processed; the abnormal job is re-dispatched, and the dispatch priority of the abnormal job is higher than that of the non-abnormal job.

[0169] In another embodiment provided in this application, the device further includes a second job dispatch module, specifically used for: Receive an anomaly notification from the target printing robot. The anomaly notification indicates that the target printing robot is unable to continue executing the currently assigned target job due to an anomaly. Based on the anomaly notification, collect all unfinished jobs corresponding to the target printing robot and reassign them, and mark the target printing robot as offline.

[0170] In another embodiment provided in this application, the second job dispatch module is further used for: From the normal printing robots other than the target printing robot, identify the recycling robot to perform the recycling operation; use the recycling robot to recycle all unfinished jobs corresponding to the target printing robot.

[0171] In another embodiment provided in this application, the cause of the abnormality includes at least one of the following: hardware failure of the printing robot, depletion of consumables, insufficient power, and path blockage.

[0172] In yet another embodiment provided in this application, the timeout period is determined based on the type and / or complexity of the dispatched job.

[0173] This application also provides a server, such as... Figure 6 As shown, Figure 6 This is a schematic diagram of the structure of a server provided in an embodiment of this application. The server can specifically be the scheduling server described above, including a processor 1901, a communication interface 1902, a memory 1903, and a communication bus 1904. The processor 1901, the communication interface 1902, and the memory 1903 communicate with each other through the communication bus 1904.

[0174] Memory 1903 is used to store computer programs; The processor 1901, when executing the program stored in the memory 1903, implements the method described above in the embodiments of this application.

[0175] The communication bus mentioned in the above server can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0176] The communication interface is used for communication between the aforementioned server and other devices.

[0177] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0178] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0179] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the methods described above in the embodiments of this application.

[0180] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the methods described above in the embodiments of this application.

[0181] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state disk (SSD)).

[0182] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0183] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments for devices, servers, and computer-readable storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0184] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A job scheduling method for a printing robot, characterized in that, The method is applied to a scheduling server, which is configured with multiple evaluation factors for evaluating a printing robot, each of which has a corresponding baseline weight and a judgment threshold; the method includes: Obtain the current value of each printing robot corresponding to each of the evaluation factors; Determine whether the current value of each evaluation factor exceeds the corresponding judgment threshold to obtain the judgment result; Based on the judgment results, the actual weight ratio corresponding to each evaluation factor is determined according to the preset weight adjustment rules; Calculate the comprehensive scheduling score for each printing robot; wherein the comprehensive scheduling score is determined based on the current value of the evaluation factor and the corresponding actual weight ratio; The printing robot to be assigned the task is determined based on the comprehensive scheduling score; The weight adjustment rules include: When the current value of all evaluation factors does not exceed the corresponding judgment threshold, all evaluation factors are determined to have an actual weight ratio equal to their respective benchmark weights. When the current value of an evaluation factor exceeds the corresponding judgment threshold, the evaluation factor that exceeds the judgment threshold is determined to have an actual weight ratio according to the preset over-threshold weight ratio, and the actual weight ratios of the remaining evaluation factors are reduced to the second weight ratio proportionally according to their respective benchmark weights. When the current values ​​of two or more evaluation factors exceed the corresponding judgment threshold, the ratio of the benchmark weight of each of the two or more evaluation factors that exceed the judgment threshold to the sum of the benchmark weights of all evaluation factors that exceed the judgment threshold is used as the actual weight ratio of the corresponding evaluation factor, and the actual weight ratio of the remaining evaluation factors that do not exceed the judgment threshold is determined to be zero.

2. The method according to claim 1, characterized in that, The evaluation factors include: remaining battery power, remaining paper, remaining consumables, equipment health, and target distance; the target distance is determined based on the distance from the current location of the printing robot to the target location.

3. The method according to claim 1, characterized in that, The method further includes: Receive print jobs from users and place the print jobs in the job pool; When a new job is added to the job pool, or at preset time intervals, the overall scheduling score of each printing robot is recalculated. Based on the comprehensive scheduling score of each printing robot, all unassigned jobs in the pending job pool and jobs that have been assigned to each printing robot but not yet completed are reallocated, and a scheduling table is generated or updated; wherein, the scheduling table contains the printing robot and delivery path information corresponding to the job assignment.

4. The method according to claim 3, characterized in that, The method further includes: When the target printing robot executes the target job dispatched based on the scheduling table, the scheduling server sets a timeout for the target job; If the target task is not completed within the timeout period, obtain the status information of the target printing robot; When it is determined based on the status information that the target printing robot cannot continue to execute the target job, the target job is marked as an abnormal job and the abnormal job is returned to the job pool to be processed. The abnormal job is reassigned, and the abnormal job is assigned a higher priority than the non-abnormal job.

5. The method according to claim 3, characterized in that, The method further includes: Receive an anomaly notification message sent by the target printing robot, the anomaly notification message indicating that the target printing robot is unable to continue performing the currently assigned target job due to an anomaly; Based on the anomaly notification information, all unfinished jobs corresponding to the target printing robot are collected and reassigned, and the target printing robot is marked as offline.

6. The method according to claim 5, characterized in that, The recycling of all unfinished jobs corresponding to the target printing robot includes: From the normal printing robots other than the target printing robot, determine the recycling robot to perform the recycling operation; The recycling robot collects all unfinished jobs corresponding to the target printing robot.

7. The method according to claim 5, characterized in that, The causes of the abnormality include at least one of the following: hardware failure of the printing robot, depletion of consumables, insufficient power, and path blockage.

8. The method according to claim 4, characterized in that, The timeout period is determined based on the type and / or complexity of the dispatched job.

9. A job scheduling device for a printing robot, characterized in that, The device is applied to a scheduling server, which is configured with multiple evaluation factors for evaluating the printing robot, each of which has a corresponding baseline weight and a judgment threshold; the device includes: The evaluation factor acquisition module is used to acquire the current value of each printing robot corresponding to each of the evaluation factors; The judgment module is used to determine whether the current value of each evaluation factor exceeds the corresponding judgment threshold, and to obtain the judgment result; The weight adjustment module is used to determine the actual weight ratio of each evaluation factor according to the judgment result and a preset weight adjustment rule. The score calculation module is used to calculate the comprehensive scheduling score for each printing robot; wherein the comprehensive scheduling score is determined based on the current value of the evaluation factor and the corresponding actual weight ratio. The scheduling module is used to determine the printing robot to perform the assigned job based on the comprehensive scheduling score; The weight adjustment rules include: When the current value of all evaluation factors does not exceed the corresponding judgment threshold, all evaluation factors are determined to have an actual weight ratio equal to their respective benchmark weights. When the current value of an evaluation factor exceeds the corresponding judgment threshold, the evaluation factor that exceeds the judgment threshold is determined to have an actual weight ratio according to the preset over-threshold weight ratio, and the actual weight ratios of the remaining evaluation factors are reduced to the second weight ratio proportionally according to their respective benchmark weights. When the current values ​​of two or more evaluation factors exceed the corresponding judgment threshold, the ratio of the benchmark weight of each of the two or more evaluation factors that exceed the judgment threshold to the sum of the benchmark weights of all evaluation factors that exceed the judgment threshold is used as the actual weight ratio of the corresponding evaluation factor, and the actual weight ratio of the remaining evaluation factors that do not exceed the judgment threshold is determined to be zero.

10. A server, characterized in that, The method includes a memory and a processor, wherein the memory stores a computer program that can run on the processor, and the processor executes the computer program to implement the method as described in any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 8.

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