Maintenance work order allocation method, device, equipment and storage medium

Abstract

The present invention discloses a maintenance work order allocation method, device, equipment and storage medium. The method comprises: obtaining a maintenance work order of a robot; determining the cause of the failure of the robot to be maintained according to the maintenance work order; determining a target maintenance personnel from at least one candidate maintenance personnel according to the failure cause; and allocating the maintenance work order to the target maintenance personnel. The embodiments of the present invention improve the allocation efficiency of maintenance work orders.

Description

Technical Field

[0001] The present invention relates to the field of automated processing technology, and in particular to a maintenance work order distribution method, device, equipment and storage medium. Background Art

[0002] With the continuous development of the field of robotics, the maintenance and repair of robots has gradually received more attention. The existing robot maintenance and repair process usually adopts the traditional repair process, and the intermediate process often requires a lot of human resources to process the maintenance work order, resulting in low efficiency in the allocation of maintenance work orders. Summary of the invention

[0003] The present invention provides a maintenance work order allocation method, device, equipment and storage medium to improve the allocation efficiency of maintenance work orders.

[0004] According to one aspect of the present invention, a maintenance work order allocation method is provided, the method comprising:

[0005] Get the robot's maintenance work order;

[0006] Determine the cause of the failure of the robot to be repaired according to the maintenance work order;

[0007] Determining a target maintenance personnel from at least one candidate maintenance personnel according to the cause of the fault;

[0008] The maintenance work order is assigned to the target maintenance personnel.

[0009] According to another aspect of the present invention, a maintenance work order distribution device is provided, the device comprising:

[0010] The maintenance work order acquisition module is used to obtain the maintenance work order of the robot;

[0011] A fault cause determination module, used to determine the fault cause of the robot to be repaired according to the maintenance work order;

[0012] A target maintenance personnel determination module, used to determine a target maintenance personnel from at least one candidate maintenance personnel according to the fault cause;

[0013] A maintenance work order allocation module is used to allocate the maintenance work order to the target maintenance personnel.

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

[0015] at least one processor; and

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

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

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

[0019] The embodiment of the present invention obtains the maintenance work order of the robot; determines the fault cause of the robot to be repaired according to the maintenance work order; determines the target maintenance personnel from at least one candidate maintenance personnel according to the fault cause; and allocates the maintenance work order to the target maintenance personnel. The above scheme determines the fault cause of the robot to be repaired according to the robot maintenance work order, and determines the corresponding target maintenance personnel according to the fault cause, thereby realizing the automatic determination of the fault cause and the target maintenance personnel, thereby realizing the automatic allocation of the maintenance work order, reducing personnel intervention, saving labor costs, and improving the allocation efficiency of the maintenance work order.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 is a flowchart of a maintenance work order allocation method provided according to Embodiment 1 of the present invention;

[0023] Figure 2 is a flowchart of a maintenance work order allocation method provided according to Embodiment 2 of the present invention;

[0024] Figure 3 is a structural schematic diagram of a maintenance work order distribution device provided according to Embodiment 3 of the present invention;

[0025] Figure 4 It is a structural schematic diagram of an electronic device for implementing the maintenance work order allocation method according to an embodiment of the present invention. DETAILED DESCRIPTION

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

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

[0028] Embodiment 1

[0029] Figure 1 A flowchart of a maintenance work order allocation method is provided for the first embodiment of the present invention. This embodiment is applicable to the case of automatically allocating maintenance work orders for robots. The method can be executed by a maintenance work order allocation device. The maintenance work order allocation device can be implemented in the form of hardware and / or software. The maintenance work order allocation device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0030] S110: Obtain a maintenance work order for the robot.

[0031] The maintenance work order may be a data form for repairing the robot generated when the robot fails. The maintenance work order may be automatically initiated to the management backend by the failed robot, or manually initiated to the management backend by relevant technicians. The management backend of the robot may manage all robots in the scene. The management backend may be a cloud server or a local server, which is not limited in this embodiment.

[0032] The maintenance work order may include at least one of the fault type of the robot, the robot identification, and the time of the fault. The fault type may include collisions between robots, spinning in place, and inability to dispatch robots.

[0033] For example, after confirming that the robot has failed, the relevant technicians can upload the maintenance work order to the management backend through the robot's display screen or mobile app, etc. Optionally, the robot can also automatically generate a maintenance work order and upload it to the management backend when confirming that it has failed.

[0034] S120: Determine the cause of the failure of the robot to be repaired according to the maintenance work order.

[0035] The robot to be repaired may be the current robot that has a fault, or another robot that has a fault with the current robot. The fault cause may be a specific cause of the robot's fault, such as an error in the robot's own parameter configuration.

[0036] For example, relevant technicians can conduct on-site surveys and determine the cause of the robot failure, and upload a maintenance work order with the cause of the failure marked to the management background, which can then obtain the cause of the failure of the robot to be repaired through the maintenance work order. Optionally, the management background can also automatically determine the robot to be repaired and its cause of failure based on the type of failure of the robot carried in the maintenance work order and the historical data of the robot stored in the data warehouse. The historical data of the robot stored in the data warehouse may include robot configuration data, robot operation data, and robot event record data.

[0037] S130: Determine a target maintenance personnel from at least one candidate maintenance personnel according to the cause of the fault.

[0038] The candidate maintenance personnel may be a technician who can perform online and / or offline maintenance on the robot that has a malfunction. The target maintenance personnel may be a technician who is selected from at least one candidate maintenance personnel and is responsible for maintaining the robot to be maintained.

[0039] Exemplarily, the management backend may select the technician who has the highest matching degree with the robot to be repaired from at least one candidate maintenance personnel as the target maintenance personnel according to the fault cause of the robot to be repaired. Specifically, the target maintenance personnel may be selected from at least one candidate maintenance personnel according to the region to which the robot to be repaired belongs and the fault cause, and the region to which the corresponding candidate maintenance personnel belongs and the fault category they are good at repairing. The fault category corresponds to the fault cause, and different maintenance personnel are good at handling different fault categories for different fault causes.

[0040] S140: Allocate the maintenance work order to the target maintenance personnel.

[0041] Exemplarily, the management backend may automatically assign the maintenance work order to the corresponding target maintenance personnel for online or offline processing.

[0042] The embodiment of the present invention obtains the maintenance work order of the robot; determines the fault cause of the robot to be repaired according to the maintenance work order; determines the target maintenance personnel from at least one candidate maintenance personnel according to the fault cause; and allocates the maintenance work order to the target maintenance personnel. The above scheme determines the fault cause of the robot to be repaired according to the robot maintenance work order, and determines the corresponding target maintenance personnel according to the fault cause, thereby realizing the automatic determination of the fault cause and the target maintenance personnel, thereby realizing the automatic allocation of the maintenance work order, reducing personnel intervention, saving labor costs, and improving the allocation efficiency of the maintenance work order.

[0043] Embodiment 2

[0044] Figure 2 This is a flow chart of a maintenance work order allocation method provided in Embodiment 2 of the present invention. This embodiment is optimized and improved on the basis of the above-mentioned technical solutions.

[0045] Furthermore, the step of "determining the cause of the failure of the robot to be repaired according to the maintenance work order" is refined into "determining the type of failure according to the maintenance work order; determining the data to be analyzed corresponding to the type of failure; analyzing the data to be analyzed to determine the cause of the failure of the robot to be repaired." to improve the method of determining the cause of the failure of the robot to be repaired.

[0046] Furthermore, the step of "determining a target maintenance personnel from at least one candidate maintenance personnel based on the cause of the fault" is refined into "generating a work order label corresponding to the maintenance work order based on the cause of the fault; obtaining a maintenance label corresponding to at least one candidate maintenance personnel; and determining a target maintenance personnel from at least one candidate maintenance personnel based on the work order label and the maintenance label." to improve the method of determining the target maintenance personnel.

[0047] like Figure 2 As shown, the method comprises the following specific steps:

[0048] S210: Obtain a maintenance work order for the robot.

[0049] S220. Determine the fault type according to the maintenance work order.

[0050] Among them, the robot's failure types may include the robot spinning in place, walking smoothly, robot collision, robot collision with humans, scheduling failure between robots, power-on inspection failure, screen abnormalities, wheels leaving marks on the ground, etc.

[0051] Exemplarily, the maintenance work order may include the fault type of the robot to be repaired, and the management backend may directly determine the fault type through the maintenance work order.

[0052] S230: Determine the data to be analyzed corresponding to the fault type.

[0053] The data to be analyzed may include at least one of the configuration data, event record data and operation data of the robot. The data to be analyzed may be stored in a data warehouse of the management background and updated in real time according to the operation status of the robot. The data warehouse may be a database storing robot-related data.

[0054] Among them, the configuration data of the robot may include camera height, roll angle and lateral offset data, etc. The event record data may include recording of all faults and events of the robot. For example, IMU (Inertial Measurement Unit) data status, positioning status and map resource acquisition status, etc., which may be encountered during the operation of the robot. Faults or events. For example, the robot collision plate is stuck, the sensor fails, the IMU data is abnormal, the target point database throws an exception, the sensor fails, and the laser radar has no data. The operation data may include data records of parameters during the operation of the robot. For example, food delivery data, including the starting point of the path, the delivery route, the delivery speed, the return speed, the approximate arrival distance and the running jitter amplitude. It can be understood that the data to be analyzed is automatically generated by the robot itself and its operation process.

[0055] It should be noted that the types of robot failures can be divided into at least two categories. One category can be self-failures that do not involve other robots, such as spinning in place or walking unsmoothly, etc. The other category can be inter-robot failures that involve other robots in addition to the robot itself, such as collisions between robots or scheduling failures between robots, etc. Different types of failures are handled differently.

[0056] Different fault types may correspond to different data to be analyzed, and the corresponding relationship between the fault type and the data to be analyzed may be obtained by relevant technicians based on the historical data of the robot stored in the data warehouse. The historical data may include the configuration data, event record data, and operation data of the robot.

[0057] Exemplarily, if the fault type is an inter-robot fault, and specifically a collision between robots, the data to be analyzed corresponding to the fault type may be event record data, for example, event record data such as collision records.

[0058] In an optional embodiment, if the fault type is an inter-robot fault, then before determining the data to be analyzed corresponding to the fault type, it also includes: determining at least two robots to be analyzed associated with the fault; accordingly, determining the data to be analyzed corresponding to the fault type includes: according to the fault type, obtaining the data to be analyzed corresponding to at least two robots to be analyzed.

[0059] Inter-robot failures may include collisions between robots and failures in inter-robot scheduling. If the fault type is an inter-robot fault, it can be determined that the number of robots causing the fault is at least two, but it is impossible to determine which robot actually failed among the at least two robots causing the fault. Therefore, at least two robots to be analyzed that are associated with the fault can be determined, and the data to be analyzed corresponding to the at least two robots to be analyzed can be obtained respectively. The robot to be analyzed can be a robot that has failed and needs to be analyzed to determine the cause of the failure.

[0060] Exemplarily, if the fault type is an inter-robot fault, at least two robots to be analyzed that have failed can be determined. According to the fault type, it can be determined that the inter-robot fault is a collision between robots or a scheduling failure between robots. According to the fault type, the data to be analyzed corresponding to at least two robots to be analyzed can be obtained from the data warehouse.

[0061] This optional embodiment determines at least two robots to be analyzed that are associated with the fault before determining the data to be analyzed corresponding to the fault type, and obtains the data to be analyzed corresponding to the at least two robots to be analyzed according to the fault type. This achieves the determination of at least two robots to be analyzed that have failed and the acquisition of the data to be analyzed corresponding to the robots to be analyzed, so that the robot that actually fails can be accurately determined based on the data to be analyzed of the robots to be analyzed, thereby reducing the workload of subsequent maintenance.

[0062] It should be noted that the maintenance work order is generated by the robot involved in the fault and sent to the management background. Optionally, when the fault type is an inter-robot fault, the maintenance work order may include the robot identifications of at least two robots to be analyzed that have failed, so that the management background can determine the at least two robots to be analyzed that have failed based on the robot identifications in the maintenance order. Optionally, when the fault type is an inter-robot fault and the maintenance work order only contains the information of the robot that sent the maintenance work order, the management background can automatically determine the robot to be analyzed based on the maintenance work order.

[0063] In an optional embodiment, if the maintenance work order only contains the current robot information, at least two robots to be analyzed that are associated with the fault are determined, including: obtaining the first operating data of the current robot, the first operating data including the fault time and the fault coordinates; obtaining the second operating data of other robots in the current robot's working scene; and determining at least two robots to be analyzed based on the first operating data and the second operating data.

[0064] The current robot may be a robot that sends a maintenance work order. The current robot information may include information such as the robot identification of the current robot, the time when the fault occurs, and the location where the fault is sent. The first operation data may include the time of the fault and the coordinates of the fault. The time when the current robot fails and the specific location where the fault is sent may be determined based on the time and coordinates of the fault.

[0065] The current robot working scene may include at least two robots. The working scene may be, for example, a food delivery scene. Other robots may be robots other than the current robot working in the robot working scene. The second operating data may include operating data corresponding to other robots. For example, the second operating data may include configuration parameters, event record data, etc. of other robots. The event record data may include fault event records related to a fault of the robot, such as fault time, fault coordinates, etc.

[0066] Exemplarily, if the acquired maintenance work order only contains the current robot information, the first operating data of the current robot can be obtained, including the fault time and fault coordinates, etc.; at the same time, the second operating data of other robots in the current robot's working scene can be obtained, including fault event records of faults that have occurred, and the fault time and fault coordinates in the first operating data, as well as the fault event records in the corresponding second operating data of other robots, can be inferred in reverse order from other robots that collided with the current robot at the fault time of the current robot and passed through the fault coordinate position of the current robot, and the current robot and other robots that collided with the current robot are used as robots to be analyzed.

[0067] This optional embodiment realizes automated determination of the robot to be analyzed by determining at least two robots to be analyzed based on the first operating data corresponding to the current robot and the second operating data corresponding to other robots, and determines other robots that have malfunctioned with the current robot by analyzing the operating data of other robots in the current robot scene, thereby improving the accuracy of the robot to be analyzed and effectively solving the problem of determining the robot to be analyzed when the maintenance work order only contains the current robot information.

[0068] S240: Analyze the data to be analyzed and determine the cause of the failure of the robot to be repaired.

[0069] The robot to be repaired may be a robot that actually has a fault, the robot to be repaired may be the current robot or another robot that has a fault with the current robot, and the robot to be repaired may be a robot to be analyzed that is associated with the fault.

[0070] It is understandable that different fault types correspond to different fault causes, and the corresponding fault cause can be determined specifically based on the data to be analyzed corresponding to the fault type.

[0071] For example, the fault causes corresponding to the fault type of collision between robots may include abnormal robot sensors that cannot receive data normally; faulty robot sensors that cannot receive correct data; incorrect sensor configuration parameters, such as installation height that does not match the actual height, etc. Specifically, it is possible to determine whether the robot sensor fails when a collision occurs based on the event record data reported in real time by the robot in the data to be analyzed, and further determine whether the sensor is working properly based on the image, location route information, system log and other information reported by the robot.

[0072] For example, a scheduling failure between robots may cause at least two robots to appear at the same place at the same time, blocking each other from passing. The causes of the scheduling failure between robots may include errors in the robot's own scheduling, errors in route planning, or excessive speed during operation. The management backend can determine the walking routes of each robot when a scheduling failure occurs through the real-time route data and location data of the robot stored in the data warehouse. If the walking routes of multiple robots overlap, it can be determined that the cause of the failure is a route planning problem.

[0073] The management backend can automatically analyze the data to be analyzed corresponding to the fault type in the maintenance work order, thereby determining the cause of the failure of the robot to be repaired, such as robot sensor failure, path planning error, etc.

[0074] S250. Generate a work order label corresponding to the maintenance work order according to the cause of the fault.

[0075] The work order label may include at least one of the cause of the fault, the region to which the robot to be repaired belongs, the robot type of the robot to be repaired, and the robot identification, etc. The robot type may be, for example, a food delivery robot, a disinfection robot, a hotel robot, etc.

[0076] Exemplarily, after determining the fault cause corresponding to the robot to be repaired, the management background can automatically generate a work order label corresponding to the maintenance work order corresponding to the robot to be repaired, so as to facilitate the subsequent allocation of relevant maintenance personnel according to the work order label.

[0077] S260: Obtain a maintenance label corresponding to at least one candidate maintenance personnel.

[0078] The maintenance label may include at least one of the region where the maintenance personnel belongs, their areas of expertise, the types of faults they are responsible for handling, and the types of robots they can handle.

[0079] Among them, the candidate maintenance personnel can be maintenance personnel who are pre-registered or registered in the management background and can solve robot failures.

[0080] Exemplarily, the management backend can directly obtain the maintenance tag corresponding to the candidate maintenance personnel, and the candidate maintenance personnel can manually modify or update their own maintenance tag through the management backend. Optionally, the management backend can also automatically update the maintenance tag corresponding to the candidate maintenance personnel based on the maintenance work orders processed by the candidate maintenance personnel in the historical period.

[0081] S270: Determine a target maintenance personnel from at least one candidate maintenance personnel according to the work order tag and the maintenance tag.

[0082] The management backend can determine the candidate maintenance personnel with the highest tag content matching degree as the target maintenance personnel based on the work order tag of the robot to be repaired and the maintenance tag corresponding to at least one candidate maintenance personnel. For example, if the work order tag of the robot to be repaired includes the cause of the failure being a robot sensor failure and the robot type being a food delivery robot, then correspondingly, based on the work order tag, a candidate maintenance personnel whose maintenance tag includes the area of ​​expertise being solving robot sensor failures and the robot type that can be handled being a food delivery robot can be selected from at least one candidate maintenance personnel as the target maintenance personnel.

[0083] Optionally, for faults that can be attempted to be resolved online, candidate maintenance personnel who can support online fault handling can be given priority when assigning maintenance work orders. For faults that fail to be resolved online, or cannot be resolved online and require on-site fault handling, they can be selected from candidate maintenance personnel who support offline fault handling to reduce labor costs.

[0084] It should be noted that for some fault causes that can be handled online, such as the configuration problem of the robot's own parameters, the management background can handle them without assigning corresponding target maintenance personnel. For such fault causes, automatic processing by the management background can improve the maintenance efficiency of the robot to be repaired. For example, if the fault cause is that the sensor installation height parameter does not match the actual height, the sensor installation height parameter can be automatically adjusted.

[0085] In an optional embodiment, a target maintenance personnel is determined from at least one candidate maintenance personnel based on the cause of the fault, including: judging whether to use a preset fault handling method to perform automated fault handling on the current robot based on the cause of the fault of the current robot; if not, determining the target maintenance personnel from at least one candidate maintenance personnel based on the cause of the fault.

[0086] The fault handling method may be preset by relevant technical personnel. Different fault handling methods may be used for different fault causes.

[0087] Exemplarily, based on the cause of the current robot's failure, determine whether a preset fault handling method can be used to automatically handle the current robot. For example, the fault causes that can be automatically handled may include problems with the robot's own parameter configuration; if so, the preset fault handling method can be used to automatically handle the current robot.

[0088] Specifically, the management background analyzes the current robot's own configuration data, for example, whether the food delivery speed is too fast, whether the pitch angle and rotation angle of the camera are too large or too small, etc. Analyze the current robot's operating data, for example, analyze the historical food delivery speed, operating speed, determine the relationship between speed and obstacles, and adjust the speed. Analyze the photos reported by the robot's vision system to see if the viewing angle in the photo meets the requirements. Configuration parameters that do not meet or satisfy the requirements can be automatically adjusted by the management background. For example, the management background can obtain the parameters of other robots of the same type that are operating normally in the scene, and determine whether they are consistent with the configuration parameters of the current robot. If not, try to use the configuration parameters of the normally operating robot to overwrite the configuration parameters of the current robot, thereby updating the current robot's own configuration data.

[0089] For example, if the fault is caused by a path planning problem that leads to a scheduling problem for the current robot, the management backend can also analyze the running trajectory of the current robot to determine whether there is a path planning conflict with other robots in the scene. Determine the frequency of robots passing through a certain path at a certain moment. If the frequency of different robots passing through the same path at a certain moment is high, it indicates that the path is likely to be congested, and detours should be given priority when planning the path.

[0090] This optional embodiment determines whether to use a preset fault handling method to automatically handle the current robot's fault based on the cause of the current robot's fault, thereby realizing automatic handling of the current robot's fault through the management background, saving labor costs while improving the maintenance efficiency of the current robot.

[0091] S280: Allocate the maintenance work order to the target maintenance personnel.

[0092] It is understandable that in order to more quickly and accurately determine the cause of the failure of the robot to be repaired, the management background can manage the failure type and the data to be analyzed corresponding to the failure type.

[0093] In an optional embodiment, based on the storage data of at least one robot acquired in a historical time period, fault types with the same data to be analyzed are merged; and fault types with different data to be analyzed are classified; wherein the storage data of the robot includes at least one of the configuration data, event record data and operation data of the robot.

[0094] Exemplarily, the management background can manage the fault types of maintenance work orders reported by the robot. For example, it can organize and analyze the robot's stored data in historical time periods, determine the data to be analyzed corresponding to the fault type, and segment and filter each fault type and / or data to be analyzed, merge fault types with the same data to be analyzed, and classify fault types with different data to be analyzed.

[0095] For example, if data analysis finds that the possible causes of a robot colliding with objects and a robot colliding with people are the same, and the data to be analyzed are also the same, then the robot collision and robot collision options in the maintenance work order reporting page can be merged to facilitate subsequent retrieval of the same data to be analyzed.

[0096] Optionally, the management backend can also dynamically add, delete or modify the fault type and the data to be analyzed corresponding to the fault type.

[0097] This optional embodiment merges fault types with the same data to be analyzed based on the storage data of at least one robot acquired in a historical time period, and classifies fault types with different data to be analyzed, thereby achieving management of fault types and the data to be analyzed corresponding to the fault types, and can more quickly and accurately determine the cause of the fault of the robot to be repaired, thereby improving the efficiency of allocating maintenance work orders.

[0098] This embodiment scheme realizes the automatic determination of the fault cause of the robot to be repaired by analyzing the data to be analyzed corresponding to the fault type in the maintenance work order and determining the fault cause of the robot to be repaired. The fault cause is determined by analyzing the data to be analyzed, which improves the accuracy of determining the fault cause. By determining the target maintenance personnel from at least one candidate maintenance personnel according to the work order label generated by the fault cause and the maintenance label obtained, the target maintenance personnel is accurately determined, thereby realizing the automatic allocation of maintenance work orders, reducing personnel intervention, saving labor costs, and improving the allocation efficiency of maintenance work orders.

[0099] Embodiment 3

[0100] Figure 3This is a schematic diagram of the structure of a maintenance work order distribution device provided in the third embodiment of the present invention. The maintenance work order distribution device provided in the embodiment of the present invention can be applied to the situation of automatically distributing maintenance work orders of robots. The device can be implemented in software and / or hardware. Figure 3 As shown, the device specifically includes: a maintenance work order acquisition module 301, a fault cause determination module 302, a target maintenance personnel determination module 303 and a maintenance work order allocation module 304.

[0101] A maintenance work order acquisition module 301 is used to acquire a maintenance work order of the robot;

[0102] A fault cause determination module 302 is used to determine the fault cause of the robot to be repaired according to the maintenance work order;

[0103] A target maintenance personnel determination module 303 is used to determine a target maintenance personnel from at least one candidate maintenance personnel according to the fault cause;

[0104] The maintenance work order allocation module 304 is used to allocate the maintenance work order to the target maintenance personnel.

[0105] The embodiment of the present invention obtains the maintenance work order of the robot; determines the fault cause of the robot to be repaired according to the maintenance work order; determines the target maintenance personnel from at least one candidate maintenance personnel according to the fault cause; and allocates the maintenance work order to the target maintenance personnel. The above scheme determines the fault cause of the robot to be repaired according to the robot maintenance work order, and determines the corresponding target maintenance personnel according to the fault cause, thereby realizing the automatic determination of the fault cause and the target maintenance personnel, thereby realizing the automatic allocation of the maintenance work order, reducing personnel intervention, saving labor costs, and improving the allocation efficiency of the maintenance work order.

[0106] Optionally, the fault cause determination module includes:

[0107] A fault type determination unit, used to determine the fault type according to the maintenance work order;

[0108] a to-be-analyzed data determining unit, used to determine the to-be-analyzed data corresponding to the fault type;

[0109] The fault cause determination unit is used to analyze the data to be analyzed and determine the fault cause of the robot to be repaired.

[0110] Optionally, if the fault type is an inter-robot fault, the fault cause determination module further includes:

[0111] A to-be-analyzed robot determining unit, used to determine at least two to-be-analyzed robots associated with the fault;

[0112] Accordingly, the to-be-analyzed data determination unit includes:

[0113] The to-be-analyzed data acquisition subunit is used to acquire the to-be-analyzed data corresponding to the at least two to-be-analyzed robots according to the fault type.

[0114] Optionally, if the maintenance work order only includes current robot information, the to-be-analyzed robot determination unit includes:

[0115] A first operation data acquisition subunit is used to acquire first operation data of the current robot, wherein the first operation data includes a fault time and a fault coordinate;

[0116] A second operation data acquisition subunit, used to acquire second operation data of other robots in the current robot working scene;

[0117] The to-be-analyzed robot determination subunit is configured to determine the at least two to-be-analyzed robots according to the first operating data and the second operating data.

[0118] Optionally, the target maintenance personnel determination module includes:

[0119] A work order label generating unit, used to generate a work order label corresponding to the maintenance work order according to the fault cause;

[0120] A maintenance label acquisition unit, used to acquire a maintenance label corresponding to at least one candidate maintenance personnel;

[0121] The first target maintenance personnel determination unit is used to determine a target maintenance personnel from at least one candidate maintenance personnel according to the work order label and the maintenance label.

[0122] Optionally, the work order label includes at least one of the fault cause, the region to which the robot to be repaired belongs, and the robot type of the robot to be repaired.

[0123] Optionally, the device further comprises:

[0124] A fault type merging module, configured to merge fault types having the same data to be analyzed based on stored data of at least one robot acquired in a historical time period; and

[0125] A fault type classification module, used for classifying fault types with different data to be analyzed;

[0126] The storage data of the robot includes at least one of the configuration data, event record data and operation data of the robot.

[0127] Optionally, the target maintenance personnel determination module 303 includes:

[0128] A fault handling judgment unit, used to judge whether to use a preset fault handling method to perform automatic fault handling on the current robot according to the fault cause of the current robot;

[0129] The second target maintenance personnel determination unit is used to determine a target maintenance personnel from at least one candidate maintenance personnel according to the cause of the fault if the preset fault handling method is not used to perform automated fault handling on the current robot.

[0130] The maintenance work order allocation device provided in the embodiment of the present invention can execute the maintenance work order allocation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0131] Embodiment 4

[0132] Figure 4 A schematic diagram of the structure of an electronic device 40 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0133] like Figure 4 As shown, the electronic device 40 includes at least one processor 41, and a memory connected to the at least one processor 41, such as a read-only memory (ROM) 42, a random access memory (RAM) 43, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 41 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 42 or the computer program loaded from the storage unit 48 to the random access memory (RAM) 43. In the RAM 43, various programs and data required for the operation of the electronic device 40 can also be stored. The processor 41, the ROM 42, and the RAM 43 are connected to each other through a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0134] A number of components in the electronic device 40 are connected to the I / O interface 45, including: an input unit 46, such as a keyboard, a mouse, etc.; an output unit 47, such as various types of displays, speakers, etc.; a storage unit 48, such as a disk, an optical disk, etc.; and a communication unit 49, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 49 allows the electronic device 40 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0135] The processor 41 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 41 executes the various methods and processes described above, such as a maintenance work order allocation method.

[0136] In some embodiments, the maintenance work order allocation method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 48. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 40 via the ROM 42 and / or the communication unit 49. When the computer program is loaded into the RAM 43 and executed by the processor 41, one or more steps of the maintenance work order allocation method described above can be performed. Alternatively, in other embodiments, the processor 41 can be configured to execute the maintenance work order allocation method in any other appropriate manner (for example, by means of firmware).

[0137] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0138] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0139] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0140] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0141] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0142] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0143] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0144] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A maintenance work order allocation method, characterized in that: include: Get the robot's maintenance work order; Determine the fault type according to the maintenance work order; wherein the fault type includes: self-fault and inter-robot fault, and the inter-robot fault includes robot collision and scheduling failure between robots; Determining data to be analyzed corresponding to the fault type; Analyze the data to be analyzed to determine the cause of the failure of the robot to be repaired; Determining a target maintenance personnel from at least one candidate maintenance personnel according to the cause of the fault; Allocating the maintenance work order to the target maintenance personnel; Wherein, if the fault type is an inter-robot fault, before determining the data to be analyzed corresponding to the fault type, the method further includes: Identify at least two robots to be analyzed that are associated with the fault; Accordingly, the determining of the data to be analyzed corresponding to the fault type includes: According to the fault type, obtaining the data to be analyzed corresponding to the at least two robots to be analyzed; Wherein, if the maintenance work order only includes the current robot information, then determining at least two robots to be analyzed associated with the fault includes: Acquire first operating data of the current robot, where the first operating data includes a fault time and a fault coordinate; Acquire second operation data of other robots in the current robot working scene; wherein the second operation data includes configuration parameters and event record data of other robots, and the event record data includes fault time and fault coordinates; The at least two robots to be analyzed are determined according to the first operating data and the second operating data.

2. The method according to claim 1, characterized in that The step of determining a target maintenance personnel from at least one candidate maintenance personnel according to the fault cause comprises: Generate a work order label corresponding to the maintenance work order according to the fault cause; Obtain a maintenance label corresponding to at least one candidate maintenance personnel; A target maintenance personnel is determined from at least one candidate maintenance personnel according to the work order label and the maintenance label.

3. The method according to claim 2, characterized in that The work order label includes at least one of the fault cause, the region to which the robot to be repaired belongs, and the robot type of the robot to be repaired.

4. The method according to claim 1, characterized in that The method further comprises: Merging fault types having the same data to be analyzed based on stored data of at least one robot acquired in a historical time period; and Classify the fault types with different data to be analyzed; The storage data of the robot includes at least one of the configuration data, event record data and operation data of the robot.

5. The method according to claim 1, characterized in that The step of determining a target maintenance personnel from at least one candidate maintenance personnel according to the fault cause comprises: According to the fault cause of the current robot, determining whether to use a preset fault handling method to automatically handle the fault of the current robot; If not, determining a target maintenance personnel from at least one candidate maintenance personnel according to the fault cause.

6. A maintenance work order distribution device, characterized in that: include: The maintenance work order acquisition module is used to obtain the maintenance work order of the robot; A fault cause determination module, comprising: a fault type determination unit, a data to be analyzed determination unit and a fault cause determination unit; The fault type determination unit is used to determine the fault type according to the maintenance work order; wherein the fault type includes: self-fault and inter-robot fault, and the inter-robot fault includes robot collision and scheduling failure between robots; The to-be-analyzed data determining unit is used to determine the to-be-analyzed data corresponding to the fault type; The fault cause determination unit is used to analyze the data to be analyzed and determine the fault cause of the robot to be repaired; A target maintenance personnel determination module, used to determine a target maintenance personnel from at least one candidate maintenance personnel according to the fault cause; A maintenance work order allocation module, used to allocate the maintenance work order to the target maintenance personnel; Wherein, if the fault type is an inter-robot fault, the fault cause determination module further includes: A to-be-analyzed robot determining unit, used to determine at least two to-be-analyzed robots associated with the fault; Accordingly, the to-be-analyzed data determination unit includes: A to-be-analyzed data acquisition subunit, configured to acquire, according to the fault type, the to-be-analyzed data corresponding to the at least two to-be-analyzed robots; Wherein, if the maintenance work order only contains the current robot information, the robot determination unit to be analyzed includes: A first operation data acquisition subunit is used to acquire first operation data of the current robot, wherein the first operation data includes a fault time and a fault coordinate; A second operation data acquisition subunit is used to acquire second operation data of other robots in the current robot working scene; wherein the second operation data includes configuration parameters and event record data of other robots, and the event record data includes fault time and fault coordinates; The to-be-analyzed robot determination subunit is configured to determine the at least two to-be-analyzed robots according to the first operating data and the second operating data.

7. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the maintenance work order allocation method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the maintenance work order allocation method according to any one of claims 1 to 5 when executed.

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