CN115130911A - Method and device for processing delivery tasks failed to execute by robot - Google Patents
Method and device for processing delivery tasks failed to execute by robot Download PDFInfo
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Abstract
The disclosure relates to the technical field of robot delivery, and provides a method for processing a delivery task failed to be executed by a robot. The method comprises the following steps: acquiring a target distribution task which is failed to be executed by an accessory robot in real time from an accessory system, wherein the accessory system comprises a plurality of accessory robots; generating an abnormal task corresponding to the target distribution task; determining an exception handling scheme based on the exception type of the exception task; and determining a target robot from a plurality of accessory robots in the accessory system, and commanding the target robot to execute a target distribution task according to the exception handling scheme. By adopting the technical means, the problem that in the prior art, the failed delivery tasks of the robot can only be manually analyzed and then a solution is given is solved.
Description
Technical Field
The present disclosure relates to the field of robot delivery technologies, and in particular, to a method and an apparatus for processing a delivery task that a robot fails to execute.
Background
With the development of robot technology, robots are applied more and more in the distribution field. In an accessory system, the accessory robot always fails to execute the distribution tasks, and for the situations, the prior art often manually analyzes the failed distribution tasks and then gives a solution.
In the course of implementing the disclosed concept, the inventors found that there are at least the following technical problems in the related art: the problem of performing a failed delivery task by the robot can only be analyzed manually and then a solution is given.
Disclosure of Invention
In view of this, embodiments of the present disclosure provide a method and an apparatus for processing a robot to execute a failed delivery task, an electronic device, and a computer-readable storage medium, so as to solve the problem in the prior art that the robot can only manually analyze the failed delivery task and then provide a solution.
In a first aspect of the embodiments of the present disclosure, a method for processing a failed delivery task performed by a robot is provided, including: acquiring a target distribution task of failure execution of an accessory robot in real time from an accessory system, wherein the accessory system comprises a plurality of accessory robots; generating an abnormal task corresponding to the target distribution task; determining an exception handling scheme based on the exception type of the exception task; and determining a target robot from a plurality of accessory robots in the accessory system, and commanding the target robot to execute a target distribution task according to the exception handling scheme.
In a second aspect of the embodiments of the present disclosure, there is provided a processing apparatus for a robot to execute a failed delivery task, including: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire a target delivery task which is executed by an accessory robot in failure from an accessory system in real time, and the accessory system comprises a plurality of accessory robots; the generating module is configured to generate an abnormal task corresponding to the target delivery task; a determination module configured to determine an exception handling scheme based on an exception type of the exception task; an execution module configured to determine a target robot from a plurality of accessory robots in the accessory system, and instruct the target robot to perform a target delivery task in accordance with the exception handling scheme.
In a third aspect of the embodiments of the present disclosure, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the above method when executing the computer program.
In a fourth aspect of the embodiments of the present disclosure, a computer-readable storage medium is provided, which stores a computer program, which when executed by a processor, implements the steps of the above-mentioned method.
Compared with the prior art, the embodiment of the disclosure has the following beneficial effects: acquiring a target distribution task which is failed to be executed by an accessory robot in real time from an accessory system, wherein the accessory system comprises a plurality of accessory robots; generating an abnormal task corresponding to the target distribution task; determining an exception handling scheme based on the exception type of the exception task; and determining a target robot from the plurality of accessory robots in the accessory system, and commanding the target robot to execute a target distribution task according to the exception handling scheme. By adopting the technical means, the problem that in the prior art, the failed delivery tasks of the robot can only be manually analyzed and then a solution is given can be solved, and the processing method for the failed delivery tasks of the robot can be implemented without manpower.
Drawings
To more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without inventive efforts.
FIG. 1 is a scenario diagram of an application scenario of an embodiment of the present disclosure;
fig. 2 is a flowchart illustrating a processing method for a robot to execute a failed delivery task according to an embodiment of the disclosure;
fig. 3 is a schematic structural diagram of a processing apparatus for a robot to execute a failed delivery task according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present disclosure.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the disclosed embodiments. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present disclosure with unnecessary detail.
A method and an apparatus for processing a robot to execute a failed delivery task according to an embodiment of the present disclosure will be described in detail below with reference to the accompanying drawings.
Fig. 1 is a scene schematic diagram of an application scenario of an embodiment of the present disclosure. The application scenario may include terminal devices 101, 102, and 103, server 104, and network 105.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When terminal devices 101, 102, and 103 are hardware, they may be various electronic devices having a display screen and supporting communication with server 104, including but not limited to smart phones, robots, laptop portable computers, desktop computers, and the like (e.g., 102 may be a robot); when the terminal apparatuses 101, 102, and 103 are software, they can be installed in the electronic apparatus as above. The terminal devices 101, 102, and 103 may be implemented as a plurality of software or software modules, or may be implemented as a single software or software module, which is not limited by the embodiments of the present disclosure. Further, various applications, such as data processing applications, instant messaging tools, social platform software, search-type applications, shopping-type applications, etc., may be installed on the terminal devices 101, 102, and 103.
The server 104 may be a server providing various services, for example, a backend server receiving a request sent by a terminal device establishing a communication connection with the server, and the backend server may receive and analyze the request sent by the terminal device and generate a processing result. The server 104 may be a server, may also be a server cluster composed of a plurality of servers, or may also be a cloud computing service center, which is not limited in this disclosure.
The server 104 may be hardware or software. When the server 104 is hardware, it may be various electronic devices that provide various services to the terminal devices 101, 102, and 103. When the server 104 is software, it may be multiple software or software modules providing various services for the terminal devices 101, 102, and 103, or may be a single software or software module providing various services for the terminal devices 101, 102, and 103, which is not limited by the embodiment of the present disclosure.
The network 105 may be a wired network connected by a coaxial cable, a twisted pair and an optical fiber, or may be a wireless network that can interconnect various Communication devices without wiring, for example, Bluetooth (Bluetooth), Near Field Communication (NFC), Infrared (Infrared), and the like, which is not limited in the embodiment of the present disclosure.
The target user can establish a communication connection with the server 104 via the network 105 through the terminal devices 101, 102, and 103 to receive or transmit information or the like. It should be noted that the specific types, numbers and combinations of the terminal devices 101, 102 and 103, the server 104 and the network 105 may be adjusted according to the actual requirements of the application scenario, and the embodiment of the present disclosure does not limit this.
Fig. 2 is a flowchart illustrating a processing method for a robot to execute a failed delivery task according to an embodiment of the present disclosure. The processing method of the robot of fig. 2 to perform the failed delivery task may be performed by the terminal device or the server of fig. 1. As shown in fig. 2, the method for processing the robot to execute the failed delivery task includes:
s201, acquiring a target distribution task which is executed by an accessory robot in a failed manner in real time from an accessory system, wherein the accessory system comprises a plurality of accessory robots;
s202, generating an abnormal task corresponding to the target distribution task;
s203, determining an exception handling scheme based on the exception type of the exception task;
s204, determining a target robot from the plurality of accessory robots in the accessory system, and commanding the target robot to execute a target distribution task according to the exception handling scheme.
The disclosed embodiments can be understood to apply to an exception handling system that is responsible for handling delivery tasks that fail to be performed by an accessory robot in an accessory system. Exception types for the exception task, including: out of stock, user not available, robot malfunction, and other types, which may be parts damaged, parts lost, user returned, etc., the abnormal type of the abnormal task may be understood as a cause of failure to perform the target delivery task. The exception type based on the exception task may only determine the type of the exception handling scheme, and the specific scheme of the exception handling scheme further needs to be determined according to the type of the exception handling scheme and some information corresponding to the type. Through the embodiment of the disclosure, the exception handling system can automatically handle delivery tasks which are failed to execute by the accessory robot in the accessory system without the help of manpower, so that the labor cost is reduced, and meanwhile, the efficiency of the exception handling system is higher than that of the manpower, so that the delivery efficiency can also be improved.
According to the technical scheme provided by the embodiment of the disclosure, a target distribution task which is failed to be executed by an accessory robot is obtained from an accessory system in real time, wherein the accessory system comprises a plurality of accessory robots; generating an abnormal task corresponding to the target distribution task; determining an exception handling scheme based on the exception type of the exception task; and determining a target robot from the plurality of accessory robots in the accessory system, and commanding the target robot to execute a target distribution task according to the exception handling scheme. By adopting the technical means, the problem that in the prior art, the failed delivery tasks of the robot can only be manually analyzed and then a solution is given can be solved, and the processing method for the failed delivery tasks of the robot can be implemented without manpower.
In step S202, an abnormal task corresponding to the target delivery task is generated, including: obtaining target related information of a target distribution task, wherein the target related information comprises: a robot code of an accessory robot that executes the target delivery task, a time at which the target delivery task fails to be executed, a reason why the target delivery task fails to be executed, and target task information of the target delivery task; and generating an abnormal task corresponding to the target delivery task based on the target related information, wherein the abnormal type of the abnormal task is determined based on the reason of the failure of executing the target delivery task.
Target task information, including: a target user and an accessory corresponding to the target delivery task (the accessory is an article to which the target delivery task is to be delivered, and the target user is an owner or a receiver of the accessory), a contact address and an address of the target user, a time period corresponding to the target delivery task (the target delivery task is to be executed and completed in the time period), and the like. The exception task may include one or more pieces of information among the target related information.
In step S202, an exception handling scheme is determined based on the exception type of the exception task, including: when the abnormal type of the abnormal task is the out-of-stock, determining that the abnormal processing scheme is a replenishment processing scheme; when the exception type of the exception task is that the user cannot receive the exception task, determining that the exception handling scheme is a distribution handling scheme; when the abnormal type of the abnormal task is the robot fault, determining that the abnormal handling scheme is the robot fault handling scheme; and when the exception type of the exception task is other types, determining that the exception processing scheme is other processing schemes.
The exception type based on the exception task may only determine the type of the exception handling scheme, and the specific scheme of the exception handling scheme further needs to be determined according to the type of the exception handling scheme and some information corresponding to the type. For example, when the exception type of the exception task is out-of-stock, determining that the exception handling scheme is a replenishment handling scheme, wherein the specific scheme of the replenishment handling scheme is to replenish the stock according to the arrival time and then determine the re-delivery time; if the exception type of the exception task is that the user cannot receive the exception task, determining that the exception handling scheme is a distribution handling scheme, acquiring a historical distribution record of a target user corresponding to the target distribution task, and determining a specific scheme of the distribution handling scheme according to the historical distribution record; if the abnormal type of the abnormal task is a robot fault, determining that the abnormal handling scheme is a robot fault handling scheme, and processing robot information of the accessory robot for executing the target distribution task by using an equipment mechanism diagnosis model to obtain a specific scheme of the robot fault handling scheme; and if the exception type of the exception task is other types, determining that the exception handling scheme is other handling schemes.
Other types may be component damage, component loss, customer return, etc., and when other types are component damage and component loss, etc., other processing schemes may be replenishment processing schemes; while the other type is customer return, etc., the other processing scheme may be a return processing scheme.
When the exception type of the exception task is that the user cannot receive the exception task, determining that the exception handling scheme is a distribution handling scheme, wherein the method comprises the following steps: obtaining a historical delivery record of a target user corresponding to a target delivery task, wherein the historical delivery record comprises: a plurality of delivery records and the time period of each delivery record; and determining a target time for re-executing the target delivery task according to the historical delivery record so as to determine a delivery processing scheme.
The time period to which each delivery record belongs is the execution time or completion time of the delivery record. If the abnormal type of the abnormal task is that the user cannot receive the abnormal task, the time period for executing the target distribution task is inconvenient for the target user. A time period for which delivery of the parts to the target customer is often successful may be determined based on a record of prior delivery success, and the target delivery task may be re-executed during that time period, i.e., the target time.
When the abnormal type of the abnormal task is the robot fault, determining that the abnormal handling scheme is the robot fault handling scheme, wherein the method comprises the following steps: acquiring an expert diagnosis knowledge base about a robot fault and robot information of an accessory robot performing a target delivery task; determining a plurality of fault events and one or more reason events corresponding to each fault event based on an expert diagnosis knowledge base; generating a fault tree by an equipment mechanism analysis method based on a plurality of fault events and one or more reason events corresponding to each fault event; constructing a robot mechanism diagnosis model according to the fault tree; processing the robot information by using the equipment mechanism diagnosis model to obtain fault information corresponding to the accessory robot for executing the target distribution task; and determining a robot fault processing scheme based on the fault information.
The expert diagnosis knowledge base comprises diagnosis knowledge in a large number of robot fault diagnosis fields, such as fault reasons which a fault event of a robot may correspond to. The fault tree is a special inverted tree-like logical causal graph that describes causal relationships between various events in the system using event symbols, logic gate symbols, and transition symbols. The fault event includes a description of a phenomenon that the robot fails, and the cause event includes a description of a cause of the robot failing. Because redundant information, repeated information and conflict information exist in the expert diagnosis knowledge base, the equipment mechanism analysis method can assist the corresponding relation between the fault event and the reason event, so that the corresponding relation between the fault event and the reason event is more definite. Or the device mechanism analysis method can also be understood as the application to the expert diagnostic knowledge base. The fault tree has a plurality of corresponding relations between fault events and reason events, so that the robot mechanism diagnosis model realizes the corresponding relations between the fault events and the reason events by means of a mathematical formula based on an expert diagnosis knowledge base, for example, a corresponding reason event can be output by inputting a fault event to the robot mechanism diagnosis model. The robot information is work and state information of an accessory robot that performs a target delivery task, and includes: the operation and state of the motor, the operation and state of the host, the running result of the distribution program and the like. For example, the robot information is processed by using the device mechanism diagnosis model, and if the accessory robot executing the target distribution task is found to be in a motor fault, the robot fault processing scheme is determined by using a maintenance program corresponding to the motor fault.
In step S204, a target robot is determined from the plurality of accessory robots in the accessory system, and the target robot is instructed to perform a target delivery task according to an exception handling scheme, including: acquiring task information of each accessory robot in the accessory system and target task information of a target distribution task; determining a first destination and a first delivery time period corresponding to each accessory robot based on the task information of each accessory robot; determining a target robot from a plurality of accessory robots in the accessory system based on a first destination and a first delivery time period corresponding to each accessory robot and a second destination and a second delivery time period, and commanding the target robot to execute a target delivery task according to an exception handling scheme; the target task information comprises: a second destination and a second delivery period.
Each of the accessory robots can receive a plurality of delivery tasks at a time, task information of each of the accessory robots is information on all the delivery tasks received by the accessory robot, and target task information is only information of a target delivery task. The first destination is the same destination that the maximum number of delivery tasks among all the delivery tasks of one accessory robot has. For example, if an accessory robot has three delivery tasks, where the destinations of both delivery tasks are S-ground, then the first destination of the accessory robot is S-ground. The first delivery time period is a time period of the same delivery that the maximum number of delivery tasks among all the delivery tasks of one component robot has. The second destination is a destination of the target delivery task, and the second delivery period is a period to which the target delivery task belongs.
The target robot is determined from the plurality of accessory robots in the accessory system based on the first destination and the first delivery period corresponding to each accessory robot, and the second destination and the second delivery period, that is, the accessory robot in which the first destination and the second destination are the same among the plurality of accessory robots and the first delivery period and the second delivery period are the same.
In step S204, a target robot is determined from the plurality of accessory robots in the accessory system, and the target robot is instructed to perform a target delivery task according to an exception handling scheme, including: acquiring task information of each accessory robot in the accessory system and target task information of a target distribution task; determining a first accessory category corresponding to each accessory robot based on the task information of each accessory robot; determining a target robot from a plurality of accessory robots in the accessory system based on the first accessory type and the second accessory type corresponding to each accessory robot, and commanding the target robot to execute a target distribution task according to an exception handling scheme; the target task information comprises: a second accessory category.
The accessory categories can include express delivery and takeaway, or include ordinary express delivery and urgent express delivery, or ordinary express delivery and valuable express delivery, and the like. And determining a target robot from the plurality of accessory robots in the accessory system based on the first accessory type corresponding to each accessory robot and the second accessory type, namely searching for an accessory robot with the same first accessory type and second accessory type from the plurality of accessory robots.
All the above optional technical solutions may be combined arbitrarily to form optional embodiments of the present application, and are not described in detail herein.
The following are embodiments of the disclosed apparatus that may be used to perform embodiments of the disclosed methods. For details not disclosed in the embodiments of the apparatus of the present disclosure, refer to the embodiments of the method of the present disclosure.
Fig. 3 is a schematic diagram of a processing apparatus for a robot to execute a failed delivery task according to an embodiment of the present disclosure. As shown in fig. 3, the processing device for the robot to execute the failed delivery job includes:
an obtaining module 301, configured to obtain, in real time, a target delivery task that an accessory robot fails to execute from an accessory system, where the accessory system includes a plurality of accessory robots;
a generating module 302 configured to generate an abnormal task corresponding to the target delivery task;
a determination module 303 configured to determine an exception handling scheme based on the exception type of the exception task;
an execution module 304 configured to determine a target robot from the plurality of accessory robots in the accessory system, and instruct the target robot to perform the target delivery task in accordance with the exception handling scheme.
The disclosed embodiments can be understood to apply to an exception handling system that is responsible for handling delivery tasks that fail to be performed by an accessory robot in an accessory system. Exception types for the exception task, including: out of stock, user not available, robot malfunction, and other types, which may be parts damaged, parts lost, user returned, etc., the abnormal type of the abnormal task may be understood as a cause of failure to perform the target delivery task. The exception type based on the exception task may only determine the type of the exception handling scheme, and the specific scheme of the exception handling scheme further needs to be determined according to the type of the exception handling scheme and some information corresponding to the type. Through the embodiment of the disclosure, the exception handling system can automatically handle the delivery task of the accessory robot in the accessory system, manual work is not needed, and then the labor cost is reduced.
According to the technical scheme provided by the embodiment of the disclosure, the target delivery tasks of the accessory robots, which fail to execute, are obtained in real time from the accessory system, wherein the accessory system comprises a plurality of accessory robots; generating an abnormal task corresponding to the target distribution task; determining an exception handling scheme based on the exception type of the exception task; and determining a target robot from a plurality of accessory robots in the accessory system, and commanding the target robot to execute a target distribution task according to the exception handling scheme. By adopting the technical means, the problem that in the prior art, the failed delivery tasks of the robot can only be manually analyzed and then a solution is given can be solved, and the processing method for the failed delivery tasks of the robot can be implemented without manpower.
Optionally, the generating module 302 is further configured to execute a robot code of the part robot of the target delivery task, a time at which the target delivery task failed to be executed, a reason why the target delivery task failed to be executed, target task information of the target delivery task; and generating an abnormal task corresponding to the target delivery task based on the target related information, wherein the abnormal type of the abnormal task is determined based on the reason of the failure of executing the target delivery task.
Target task information, including: a target user and an accessory corresponding to the target delivery task (the accessory is an article to which the target delivery task is to be delivered, and the target user is an owner or a receiver of the accessory), a contact address and an address of the target user, a time period corresponding to the target delivery task (the target delivery task is to be executed and completed in the time period), and the like. The exception task may include one or more pieces of information among the target related information.
Optionally, the generating module 302 is further configured to determine that the exception handling scheme is a replenishment handling scheme when the exception type of the exception task is a stock shortage; when the exception type of the exception task is that the user cannot receive the exception task, determining that the exception handling scheme is a distribution handling scheme; when the abnormal type of the abnormal task is the robot fault, determining that the abnormal handling scheme is the robot fault handling scheme; and when the exception type of the exception task is other types, determining that the exception processing scheme is other processing schemes.
The exception type based on the exception task may only determine the type of the exception handling scheme, and the specific scheme of the exception handling scheme further needs to be determined according to the type of the exception handling scheme and some information corresponding to the type. For example, when the abnormal type of the abnormal task is the shortage, determining that the abnormal processing scheme is a replenishment processing scheme, wherein the specific scheme of the replenishment processing scheme is to replenish the goods according to the arrival time and then determining the re-delivery time; if the exception type of the exception task is that the user cannot receive the exception task, determining that the exception handling scheme is a distribution handling scheme, acquiring a historical distribution record of a target user corresponding to the target distribution task, and determining a specific scheme of the distribution handling scheme according to the historical distribution record; if the abnormal type of the abnormal task is a robot fault, determining that the abnormal handling scheme is a robot fault handling scheme, and processing robot information of the accessory robot for executing the target distribution task by using an equipment mechanism diagnosis model to obtain a specific scheme of the robot fault handling scheme; and if the exception type of the exception task is other types, determining that the exception handling scheme is other handling schemes.
Other types may be component damage, component loss, customer return, etc., and when other types are component damage and component loss, etc., other processing schemes may be replenishment processing schemes; while the other type is customer return, etc., the other processing scheme may be a return processing scheme.
Optionally, the determining module 303 is further configured to obtain a historical delivery record of the target user corresponding to the target delivery task, where the historical delivery record includes: a plurality of delivery records and the time period of each delivery record; and determining a target time for re-executing the target delivery task according to the historical delivery record so as to determine a delivery processing scheme.
The time period to which each delivery record belongs is the execution time or completion time of the delivery record. If the exception type of the exception task is that the user cannot receive the exception type, the time period for executing the target delivery task may be inconvenient for the target user. A time period for which delivery of the parts to the target customer is often successful may be determined based on a record of prior delivery success, and the target delivery task may be re-executed during that time period, i.e., the target time.
Optionally, the determining module 303 is further configured to obtain an expert diagnostic knowledge base about the robot fault and robot information of the accessory robot performing the target delivery task; determining a plurality of fault events and one or more reason events corresponding to each fault event based on an expert diagnosis knowledge base; generating a fault tree by an equipment mechanism analysis method based on a plurality of fault events and one or more reason events corresponding to each fault event; constructing a robot mechanism diagnosis model according to the fault tree; processing the robot information by using the equipment mechanism diagnosis model to obtain fault information corresponding to the accessory robot for executing the target distribution task; and determining a robot fault processing scheme based on the fault information.
The expert diagnosis knowledge base comprises diagnosis knowledge in a large number of robot fault diagnosis fields, such as fault reasons which a fault event of a robot may correspond to. The fault tree is a special inverted tree-like logical causal graph that describes causal relationships between various events in the system using event symbols, logic gate symbols, and transition symbols. The fault event includes a description of a phenomenon that the robot fails, and the cause event includes a description of a cause of the robot failing. Because redundant information, repeated information and conflict information exist in the expert diagnosis knowledge base, the equipment mechanism analysis method can assist the corresponding relation between the fault event and the reason event, so that the corresponding relation between the fault event and the reason event is more definite. Or the device mechanism analysis method can also be understood as the application to the expert diagnostic knowledge base. The fault tree has a plurality of corresponding relations between fault events and reason events, so that the robot mechanism diagnosis model realizes the corresponding relations between the fault events and the reason events by means of a mathematical formula based on an expert diagnosis knowledge base, for example, a corresponding reason event can be output by inputting a fault event to the robot mechanism diagnosis model. The robot information is work and state information of an accessory robot that performs a target delivery task, and includes: the operation and state of the motor, the operation and state of the host machine, the running result of the distribution program and the like. For example, the robot information is processed by using the device mechanism diagnosis model, and if the accessory robot executing the target distribution task is found to be in a motor fault, the robot fault processing scheme is determined by using a maintenance program corresponding to the motor fault.
Optionally, the execution module 304 is further configured to obtain task information of each accessory robot in the accessory system and target task information of the target delivery task; determining a first destination and a first delivery time period corresponding to each accessory robot based on the task information of each accessory robot; determining a target robot from a plurality of accessory robots in the accessory system based on a first destination and a first delivery time period corresponding to each accessory robot and a second destination and a second delivery time period, and commanding the target robot to execute a target delivery task according to an exception handling scheme; the target task information comprises: a second destination and a second delivery period.
Each of the accessory robots can receive a plurality of delivery tasks at a time, task information of each of the accessory robots is information on all the delivery tasks received by the accessory robot, and target task information is only information of a target delivery task. The first destination is the same destination that the maximum number of all the delivery tasks of one accessory robot has. For example, if an accessory robot has three delivery tasks, where the destinations of both delivery tasks are S-ground, then the first destination of the accessory robot is S-ground. The first delivery period is a period of time in which the maximum number of delivery tasks among all the delivery tasks of one accessory robot have the same delivery. The second destination is a destination of the target delivery task, and the second delivery period is a period to which the target delivery task belongs.
The target robot is determined from the plurality of accessory robots in the accessory system based on the first destination and the first delivery period corresponding to each accessory robot, and the second destination and the second delivery period, that is, the accessory robot in which the first destination and the second destination are the same among the plurality of accessory robots and the first delivery period and the second delivery period are the same.
Optionally, the execution module 304 is further configured to obtain task information of each accessory robot in the accessory system and target task information of the target delivery task; determining a first accessory category corresponding to each accessory robot based on the task information of each accessory robot; determining a target robot from a plurality of accessory robots in the accessory system based on the first accessory type and the second accessory type corresponding to each accessory robot, and commanding the target robot to execute a target distribution task according to an exception handling scheme; the target task information comprises: a second accessory category.
The accessory categories can include express delivery and takeaway, or include ordinary express delivery and urgent express delivery, or ordinary express delivery and valuable express delivery, and the like. The target robot is determined from the plurality of accessory robots in the accessory system based on the first accessory category and the second accessory category corresponding to each accessory robot, that is, an accessory robot having the same first accessory category and the same second accessory category is searched for from among the plurality of accessory robots.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.
Fig. 4 is a schematic diagram of an electronic device 4 provided by the embodiment of the present disclosure. As shown in fig. 4, the electronic apparatus 4 of this embodiment includes: a processor 401, a memory 402 and a computer program 403 stored in the memory 402 and executable on the processor 401. The steps in the various method embodiments described above are implemented when the processor 401 executes the computer program 403. Alternatively, the processor 401 implements the functions of the respective modules/units in the above-described respective apparatus embodiments when executing the computer program 403.
Illustratively, the computer program 403 may be partitioned into one or more modules/units, which are stored in the memory 402 and executed by the processor 401 to accomplish the present disclosure. One or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 403 in the electronic device 4.
The electronic device 4 may be a desktop computer, a notebook, a palm computer, a cloud server, or other electronic devices. The electronic device 4 may include, but is not limited to, a processor 401 and a memory 402. Those skilled in the art will appreciate that fig. 4 is merely an example of the electronic device 4, and does not constitute a limitation of the electronic device 4, and may include more or less components than those shown, or combine certain components, or different components, e.g., the electronic device may also include input-output devices, network access devices, buses, etc.
The Processor 401 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 402 may be an internal storage unit of the electronic device 4, for example, a hard disk or a memory of the electronic device 4. The memory 402 may also be an external storage device of the electronic device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the electronic device 4. Further, the memory 402 may also include both internal storage units of the electronic device 4 and external storage devices. The memory 402 is used for storing computer programs and other programs and data required by the electronic device. The memory 402 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules, so as to perform all or part of the functions described above. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only used for distinguishing one functional unit from another, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
In the embodiments provided in the present disclosure, it should be understood that the disclosed apparatus/electronic device and method may be implemented in other ways. For example, the above-described apparatus/electronic device embodiments are merely illustrative, and for example, a module or a unit may be divided into only one logical function, and may be implemented in other ways, and multiple units or components may be combined or integrated into another system, or some features may be omitted or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow in the method of the above embodiments may be realized by the present disclosure, and the computer program may be stored in a computer readable storage medium to instruct related hardware, and when the computer program is executed by a processor, the steps of the above method embodiments may be realized. The computer program may comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain suitable additions or additions that may be required in accordance with legislative and patent practices within the jurisdiction, for example, in some jurisdictions, computer readable media may not include electrical carrier signals or telecommunications signals in accordance with legislative and patent practices.
The above examples are only intended to illustrate the technical solutions of the present disclosure, not to limit them; although the present disclosure has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the embodiments of the present disclosure, and they should be construed as being included in the scope of the present disclosure.
Claims (10)
1. A method for processing a failed delivery task performed by a robot, the method comprising:
acquiring a target delivery task which is failed to be executed by an accessory robot in real time from an accessory system, wherein the accessory system comprises a plurality of accessory robots;
generating an abnormal task corresponding to the target distribution task;
determining an exception handling scheme based on the exception type of the exception task;
determining a target robot from a plurality of accessory robots in an accessory system, and commanding the target robot to perform the target delivery task according to the exception handling scheme.
2. The method of claim 1, wherein the generating of the exception task corresponding to the target delivery task comprises:
obtaining target related information of the target distribution task, wherein the target related information comprises: a robot code of an accessory robot that executes the target delivery task, a time at which the target delivery task fails to be executed, a reason why the target delivery task fails to be executed, and target task information of the target delivery task;
and generating an abnormal task corresponding to the target delivery task based on the target related information, wherein the abnormal type of the abnormal task is determined based on the reason of the failure of executing the target delivery task.
3. The method of claim 1, wherein determining an exception handling scheme based on the exception type for the exception task comprises:
when the exception type of the exception task is out-of-stock, determining the exception handling scheme to be a replenishment handling scheme;
when the exception type of the exception task is that the user cannot receive the exception task, determining that the exception handling scheme is a distribution handling scheme;
when the abnormal type of the abnormal task is a robot fault, determining that the abnormal handling scheme is a robot fault handling scheme;
and when the exception type of the exception task is other types, determining that the exception handling scheme is other handling schemes.
4. The method of claim 3, wherein when the exception type of the exception task is not receivable by the user, determining that the exception handling scheme is a dispatch handling scheme comprises:
obtaining a historical delivery record of a target user corresponding to the target delivery task, wherein the historical delivery record comprises: a plurality of delivery records and the time period of each delivery record;
and determining the target time for re-executing the target delivery task according to the historical delivery record so as to determine the delivery processing scheme.
5. The method of claim 3, wherein when the exception type of the exception task is a robot fault, determining that the exception handling scheme is a robot fault handling scheme comprises:
acquiring an expert diagnosis knowledge base about robot faults and robot information of an accessory robot performing the target delivery task;
determining a plurality of fault events and one or more cause events corresponding to each fault event based on the expert diagnosis knowledge base;
generating a fault tree by an equipment mechanism analysis method based on a plurality of fault events and one or more reason events corresponding to each fault event;
constructing a robot mechanism diagnosis model according to the fault tree;
processing the robot information by using the equipment mechanism diagnosis model to obtain fault information corresponding to the accessory robot executing the target distribution task;
and determining the robot fault processing scheme based on the fault information.
6. The method of claim 1, wherein the determining a target robot from a plurality of accessory robots in an accessory system, the target robot being commanded to perform the target delivery task in accordance with the exception handling scheme, comprises:
acquiring task information of each accessory robot in the accessory system and target task information of the target distribution task;
determining a first destination and a first distribution time period corresponding to each accessory robot based on the task information of each accessory robot;
determining the target robot from the plurality of accessory robots in the accessory system based on a first destination and a first delivery time period corresponding to each accessory robot, and a second destination and a second delivery time period, and commanding the target robot to perform the target delivery task according to the exception handling scheme;
wherein, the target task information includes: a second destination and a second delivery period.
7. The method of claim 1, wherein said determining a target robot from a plurality of accessory robots in an accessory system, said target robot being commanded to perform said target delivery task in accordance with said exception handling scheme, comprises:
acquiring task information of each accessory robot in the accessory system and target task information of the target distribution task;
determining a first accessory category corresponding to each accessory robot based on the task information of each accessory robot;
determining the target robot from a plurality of accessory robots in the accessory system based on a first accessory category and a second accessory category corresponding to each accessory robot, and commanding the target robot to perform the target delivery task according to the exception handling scheme;
wherein the target task information includes: a second accessory category.
8. A processing apparatus for a robot to execute a failed delivery job, comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is configured to acquire a target delivery task which is executed by an accessory robot in failure from an accessory system in real time, and the accessory system comprises a plurality of accessory robots;
the generating module is configured to generate an abnormal task corresponding to the target delivery task;
a determination module configured to determine an exception handling scheme based on an exception type of the exception task;
an execution module configured to determine a target robot from a plurality of accessory robots in an accessory system, the target robot being instructed to perform the target delivery task in accordance with the exception handling scheme.
9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116468232A (en) * | 2023-04-06 | 2023-07-21 | 宝驷智慧物流(珠海)有限公司 | Method, device, equipment and medium for exception handling |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116468232A (en) * | 2023-04-06 | 2023-07-21 | 宝驷智慧物流(珠海)有限公司 | Method, device, equipment and medium for exception handling |
| CN116468232B (en) * | 2023-04-06 | 2024-01-19 | 宝驷智慧物流(珠海)有限公司 | Method, device, equipment and medium for exception handling |
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