CN114683268A - Robot task decision method, device, equipment and storage medium - Google Patents
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1679—Programme controls characterised by the tasks executed
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06316—Sequencing of tasks or work
Abstract
The application provides a robot task decision method, a device, equipment and a storage medium, and relates to the technical field of robots. The robot task decision method comprises the following steps: if a cancel command of the first subtask is received, determining the relevance of the first subtask and at least one second subtask included in a target task to which the first subtask belongs under a preset task decision dimension, wherein the at least one second subtask is other subtasks behind the first subtask in the target task under the preset task decision dimension; and according to the relevance, making a cancellation decision on the target task. According to the task canceling method and device, when the first subtask in the target task is cancelled, the relevance between the second subtask and the first subtask under the unified target task can be considered, and the target task is cancelled and decided according to the relevance, so that the problem that after the task in the prior art is cancelled, a robot cannot normally execute the task, and execution errors or execution confusion are easily caused is solved.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a robot task decision method, a device, equipment and a storage medium.
Background
With the development of artificial intelligence technology, robots are applied to various fields in life more and more commonly. Among them, the service robot provides great convenience for people's life, and its application is wider and more popular.
The robot may receive a single task or a plurality of tasks simultaneously during use, and in the case where the robot receives a plurality of tasks simultaneously, the tasks are sequentially executed in the order of task arrangement. I.e. if one of the tasks is cancelled, the robot will still perform the next task in order.
However, the tasks received by the robot are not always independent tasks, and once a certain task associated with each other is cancelled, the robot may not normally execute the next task, so that a task execution error or a task execution confusion problem may occur.
Disclosure of Invention
The present invention is directed to provide a method, an apparatus, a device and a storage medium for deciding a task of a robot, so as to solve the problem that the robot cannot execute the task normally after the task is cancelled, which is likely to cause an execution error or an execution confusion.
In order to achieve the above purpose, the embodiment of the present invention adopts the following technical solutions:
in a first aspect, an embodiment of the present invention provides a robot task decision method, including:
if a cancel command of a first subtask is received, determining the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs under a preset task decision dimension, wherein the at least one second subtask is other subtasks behind the first subtask in the target task under the preset task decision dimension;
and according to the relevance, carrying out a cancellation decision on the target task.
Optionally, the making a cancellation decision for the target task according to the relevance includes:
and if the at least one second subtask and the first subtask have relevance, canceling the target task and executing a next task of the target task in a task stack.
Optionally, the making a cancellation decision for the target task according to the relevance further includes:
and if a target subtask which is not related to the first subtask exists in the at least one second subtask, canceling the first subtask and executing the target subtask.
Optionally, the determining the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension includes:
determining the at least one second subtask according to the belonging domain mark of the first subtask, wherein the at least one second subtask and the first subtask have the same belonging domain mark, and the belonging domain mark is used for indicating the target task;
and respectively determining the relevance of the first subtask and the at least one second subtask according to the relevance mark between the first subtask and the at least one second subtask.
Optionally, before the determining the at least one second subtask according to the domain flag of the first subtask, the method further includes:
splitting each task in the task stack under the preset task decision dimension to obtain a plurality of subtasks of each task under the preset task decision dimension;
and performing the marking operation of the domain of each subtask, and performing the associated marking operation between the subtasks in each task.
Optionally, the splitting each task in the task stack in the preset task decision dimension to obtain a plurality of subtasks of each task in the preset task decision dimension includes:
splitting each task according to the description mark corresponding to the preset task decision dimension in each task to obtain a plurality of subtasks of each task under the preset task decision dimension.
Optionally, if the preset task decision dimension includes: if a plurality of task decision dimensions are provided, the determining of the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension includes:
determining an association of the first subtask with the at least one second subtask in each task decision dimension;
the step of making a cancellation decision for the target task according to the relevance comprises the following steps:
and performing cancellation decision on the target task according to the relevance of each task decision dimension.
Optionally, the determining the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension includes:
and if the task sources of the first subtask and the at least one second subtask are the same, determining the relevance of the first subtask and the at least one second subtask under the preset task decision dimension.
Optionally, the method further comprises:
and if the task sources of the first subtask and the at least one second subtask are different, canceling the first subtask and executing a next subtask of the first subtask in the at least one second subtask.
Optionally, the preset task decision dimension includes at least one of the following dimensions: a temporal order dimension, a spatial dimension, a semantic viscosity dimension.
In a second aspect, an embodiment of the present application further provides a robot task decision device, including: a determination module and a decision module, wherein:
the determining module is configured to determine, if a cancel command of a first subtask is received, a relevance between the first subtask and at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension, where the at least one second subtask is another subtask after the first subtask in the target task in the preset task decision dimension;
and the decision module is used for carrying out cancellation decision on the target task according to the relevance.
Optionally, the decision module is specifically configured to cancel the target task and execute a next task of the target task in a task stack if the at least one second subtask and the first subtask both have a correlation.
Optionally, the decision module is specifically configured to, if a target subtask that is not associated with the first subtask exists in the at least one second subtask, cancel the first subtask, and execute the target subtask.
Optionally, the determining module is specifically configured to determine the at least one second subtask according to a belonging domain flag of the first subtask, where the at least one second subtask and the first subtask have a same belonging domain flag, and the belonging domain flag is used to indicate the target task; and respectively determining the relevance of the first subtask and the at least one second subtask according to the relevance mark between the first subtask and the at least one second subtask.
Optionally, the determining module is specifically configured to determine whether the first subtask and the at least one second subtask have relevance according to association indication information between the first subtask and the at least one second subtask, respectively.
Optionally, the apparatus further comprises: split module and mark module, wherein:
the splitting module is used for splitting each task in the task stack under the preset task decision dimension to obtain a plurality of subtasks of each task under the preset task decision dimension;
the marking module is used for marking the domain of each subtask and marking the association between the subtasks in each task.
Optionally, the splitting module is specifically configured to split each task according to the description flag corresponding to the preset task decision dimension in each task, so as to obtain a plurality of subtasks of each task under the preset task decision dimension.
Optionally, the determining module is specifically configured to determine relevance of the first subtask to the at least one second subtask in each task decision dimension;
the decision module is specifically configured to make a cancellation decision for the target task according to the relevance of each task decision dimension.
Optionally, the determining module is specifically configured to determine, if the task sources of the first subtask and the at least one second subtask are the same, the relevance between the first subtask and the at least one second subtask in the preset task decision dimension.
Optionally, the decision module is specifically configured to cancel the first subtask and execute a next subtask of the first subtask in the at least one second subtask if the task sources of the first subtask and the at least one second subtask are different.
In a third aspect, an embodiment of the present application further provides a robot task decision device, including: a memory and a processor, wherein the memory stores a computer program executable by the processor, and the processor implements any of the robot task decision methods provided by the first aspect when executing the computer program.
In a fourth aspect, an embodiment of the present application further provides a storage medium, where a computer program is stored on the storage medium, and when the computer program is read and executed, the method for deciding a task of a robot provided in the first aspect is implemented.
The beneficial effect of this application is:
in the robot task decision method, the device, the equipment and the storage medium, after a cancel command of a first subtask is received, the relevance of the first subtask and at least one second subtask is determined, wherein the second subtask is other subtasks behind the first subtask in a target task under a preset task decision dimension; and then carrying out cancellation decision on the target task according to the relevance. According to the method, after a cancel command of the first subtask is received, the first subtask is canceled, and the target task is canceled according to the relevance, so that the related target task and the first subtask are canceled together due to the relevance between the considered subtasks, and the problem that the related tasks are mistaken or confused in task execution due to the fact that one of the related tasks is canceled is solved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
FIG. 1 is a schematic flow chart of a robot task decision method according to the present invention;
FIG. 2 is a schematic flow chart of a robot task decision method according to the present invention;
FIG. 3 is a schematic flow chart of a robot task decision method according to the present invention;
FIG. 4 is a schematic flow chart of a robot task decision method according to the present invention;
FIG. 5 is a schematic flow chart of a robot task decision method according to the present invention;
fig. 6 is a schematic structural diagram of a robot task decision flow according to another embodiment of the present disclosure;
FIG. 7 is a schematic diagram of a robot task decision device according to an embodiment of the present disclosure;
FIG. 8 is a schematic diagram of a robot task decision device according to an embodiment of the present disclosure;
fig. 9 is a schematic diagram of a robot task decision device according to an embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention.
The robot according to the following embodiments of the present application may be a service robot, and may be, for example: the professional field service robot may be a personal or home service robot. The embodiment of the present application does not limit the specific type of the robot as long as the robot can perform the task.
In practical application, when a robot receives a task execution command, the tasks are sequentially stored in a preset task stack according to the execution sequence of the tasks, and in the task execution process, the tasks are sequentially executed according to the arrangement sequence of the tasks in the task stack. In the conventional technology, the robot only executes tasks in sequence mechanically according to the arrangement sequence of the tasks in the task stack, and even if one task is cancelled, the robot still executes the next task of the task stack corresponding to the cancelled task. However, in the actual use process, a plurality of tasks issued to the robot by the user may not be mutually independent tasks, the tasks are associated with each other, for the associated tasks, only the preceding task is normally executed, the subsequent task can be normally executed, once the preceding task is cancelled, the task cannot be normally executed, if the robot still executes the associated task, a task execution error or confusion may occur, so that the task execution of the robot is not accurate enough, and the use experience of the user is seriously affected.
Therefore, in order to avoid that the robot can normally execute the task under the condition that the task is cancelled, and no task execution error or confusion occurs, under the condition that a task cancellation command is received, the relevance between the cancelled task and other tasks needs to be accurately determined, and other tasks related to the cancelled task are accurately mined and found based on the relevance, so that accurate task decision is realized, the influence of the related task on the task execution of the robot after the task is cancelled is avoided, the normal execution of the task is ensured, and the error or confusion execution is avoided.
The robot task decision method provided by the present application is illustrated by a number of examples as follows. Fig. 1 is a flowchart illustrating a robot task decision method according to an embodiment of the present invention, where the robot task decision method may be implemented by a robot controller built in the robot or an external controller communicatively connected to the robot. As shown in fig. 1, the method may include:
s101: and if a cancel command of the first subtask is received, determining the relevance of the first subtask and at least one second subtask included in a target task to which the first subtask belongs under a preset task decision dimension.
The robot may be a service robot, for example. The robot has an input device thereon to receive externally input task commands, such as a task execution command, or a task cancel command, etc. The input device may include, for example, a voice input device, and accordingly, the cancel command may be a cancel command input by a user through voice, and the input device may further include, for example: the communication interface is a wireless communication interface or a wired communication interface, and accordingly, the cancel command may be a text or other cancel command input by a user through an external device such as a terminal interface. The obtaining manner of the specific cancel command may be flexibly adjusted according to the user's needs, and the above is only an exemplary illustration, and is not limited thereto.
It should be noted that the task execution command is also called a task issuing command, and the acquisition form of the task execution command may be similar to the task canceling command, which is not limited in the present application.
The cancel command may include: identification information of the first subtask to indicate that the first subtask is cancelled. The cancelled first subtask may be at least one subtask and is not limited to one subtask. When the cancelled task is determined to be the first subtask based on the cancellation command, other subtasks after the first subtask in the target task may be determined to be the second subtask in a preset task decision dimension. In the event that the first subtask and the at least one second subtask are determined, an association between the first subtask and the second subtask may be determined. The association may be used to indicate whether an execution association exists for the first subtask and the second subtask. If the first subtask and the second subtask have execution association, it is determined that the first subtask is an execution condition of the second subtask, and once the first subtask is cancelled and cannot be normally executed, the second subtask cannot be normally executed.
In an embodiment of the present application, for example, when the received task issuing command includes a plurality of subtasks, the plurality of subtasks may form one task, which is also called a main task or a large task. The method comprises the steps that information of at least one task is sequentially stored in a preset task stack of the robot, and each task is composed of a plurality of subtasks which are sequentially arranged. In this implementation, when a cancel command of a first subtask is received, it may be determined that a task to which the first subtask belongs is the target task from the task stack, and then at least one task subsequent to the first subtask is determined from the target task as the at least one second subtask. The multiple subtasks in the task may be determined by multiple subtask identifications in one task issuing command at the same time. That is, each task in the task stack may correspond to one task issuing command, for example, and each task identifies, for each sub-task included in the task issuing command, a plurality of sub-tasks corresponding to the plurality of sub-tasks in the task issuing command, for example.
S102: and according to the relevance, carrying out a cancellation decision on the target task.
For example, whether the first subtask is in execution association with each second subtask may be determined according to the association, and based on the result of the determination of the execution association between the first subtask and each second subtask, it is determined whether the second subtask needs to be cancelled after the first subtask is cancelled, so as to determine whether to cancel part of the subtasks in the target task or cancel the entire target task, thereby implementing a cancellation decision for the target task.
In other possible embodiments, it may also be determined whether to execute the second subtask or cancel the second subtask, for example, according to the closeness of the relationship between each second subtask and the first subtask, for example, for some second subtasks that need to be relied on for the first subtask, that is, the second subtask that can be correctly executed only after the first subtask is successfully executed, may be determined as a second subtask that has a close relationship with the first subtask, for such subtasks, may be cancelled together after the first subtask is cancelled, for a second subtask that has no relationship with the first subtask, or has an insufficiently close relationship, for example, may be executed after the first subtask is cancelled, it should be understood that the above embodiments are merely illustrative, and specific decision manners and decision contents of the cancellation decisions of specific target tasks, can be flexibly adjusted according to the needs of users, and is not limited to the embodiments.
The task cancellation may be, for example, deleting identification information corresponding to the task in the task stack.
In the robot task decision method provided by this embodiment, under the condition that a cancel command of a first subtask is received, the relevance between a second subtask and the first subtask in a target task may be determined, and then a cancel decision may be performed on the target task according to the relevance to determine whether to cancel part of the subtasks in the target task or cancel the entire target task, so as to reduce the influence of the relevance between the subtasks on the execution of subsequent tasks after the first subtask is cancelled as much as possible, and effectively ensure that the robot recognizes the normal execution task after the first subtask is cancelled, thereby avoiding the occurrence of task execution errors or execution confusion of the robot, and improving the user experience.
Optionally, in some possible embodiments, S102 may include, for example: and if the at least one second subtask and the first subtask have relevance, canceling the target task and executing a next task of the target task in the task stack.
Wherein, the task stack includes at least one task, that is, if each second subtask under the target task to which the first subtask belongs has relevance to the first subtask under the preset task decision dimension, it indicates that each second subtask has execution relevance to the first subtask, that is, the execution of each second subtask needs to depend on the normal execution of the first subtask, and only after the first subtask is executed successfully, other second subtasks under the target task can be executed successfully, if the first subtask is cancelled, the first subtask cannot be executed normally, so that other second subtasks may not be executed normally, and therefore the whole target task needs to be cancelled, that is, the identification information of the first subtask and at least one second subtask in the whole target task is deleted from the task stack, so that the robot can determine that the next task of the target task in the task stack is to be executed, and performs the next task.
And under the condition that the at least one second subtask and the first subtask have relevance, the whole target task is cancelled, namely the first subtask is cancelled, and the at least one subtask with the relevance is cancelled, so that the execution relevance between the subtasks when the first subtask is cancelled is effectively reduced, the influence on the execution of subsequent tasks is reduced, and the robot can normally execute the next task.
In other possible embodiments, S102 may further include, for example: and if the target subtask which is not related to the first subtask exists in the at least one second subtask, canceling the first subtask and executing the target subtask.
If a second subtask which is not related to the first subtask exists in a second subtask corresponding to the first subtask in the target task, determining that the second subtask which is not related to the first subtask is the target subtask, and the target subtask and the first subtask belong to the same target task, but because the second subtask does not have the relationship, even if the first subtask is cancelled, the execution of the target subtask cannot be influenced, so that the whole target task does not need to be cancelled; however, for the second subtasks except the target subtask in the target task, because of the relevance with the first subtask, the second subtasks except the target subtask need to be cancelled together with the first subtask and executed, so that the robot can normally execute the target subtask.
In the method for determining whether the second subtasks need to be executed or cancelled in the target task, whether the second subtasks have an association relationship with the first subtasks or not is fully considered, and for the target subtasks without associations, the target subtasks can be continuously executed without being influenced by the cancellation of the first subtasks, and the whole target task does not need to be cancelled.
Optionally, on the basis of the above embodiment, another embodiment of the present application may further provide a robot task decision method, and an implementation process of determining the relevance in the above method is described as follows with reference to the accompanying drawings. Fig. 2 is a schematic flowchart of a robot task decision method according to another embodiment of the present disclosure, and as shown in fig. 2, S101 may include:
s103: and determining at least one second subtask according to the belonging domain mark of the first subtask.
Each subtask in the task stack can be pre-labeled with a corresponding belonging domain mark to indicate the task to which the subtask belongs. The belonging domain flag of the first subtask may be used to indicate a target task to which the first subtask belongs, and for subtasks under the same task, the same belonging domain flag may be provided, that is, at least one second subtask and the first subtask having the same belonging domain flag are both used to indicate the target task.
And determining a target task to which the first subtask belongs based on the belonging domain mark of the first subtask, and then determining other tasks after the first subtask as the at least one second subtask from the target task.
Each subtask under the same target task has the same belonging domain mark, and the belonging domain mark can be, for example, a corresponding timestamp mark when the robot receives each target task, or unique identification information of each target task, and the like, and only needs to uniquely indicate each target task.
Because the relevance between the subtasks is used for indicating the relevance between the subtasks in the same target task, the mode of determining at least one second subtask corresponding to the first subtask according to the domain mark to which the subtask belongs can ensure that the first subtask and the second subtask belong to the same target task, so that the subsequent judgment of whether the subtasks have the relevance is meaningful, and the problems of judgment confusion, misjudgment, missing judgment and the like caused by the fact that the target tasks to which the second subtask and the first subtask belong are different are avoided.
S104: and respectively determining the relevance of the first subtask and the at least one second subtask according to the relevance mark between the first subtask and the at least one second subtask.
In the task stack, for each subtask in each task, an association flag between corresponding subtasks may be pre-labeled. Then, for the target task, the task stack may have an association flag between the first subtask and each second subtask to indicate an execution association between the first subtask and each second subtask, respectively.
For example, in some possible embodiments, the association flag between the subtasks may be association indication information, that is, whether the first subtask and the at least one second subtask have an association may be determined according to the association indication information between the first subtask and the at least one second subtask, respectively. The indication information is, for example, in the form of "yes", or "no". Correspondingly, whether the first subtask and the at least one second subtask have relevance or not can be respectively determined in a semantic recognition mode or a comparison mode with preset indication information according to the relevance indication information between the first subtask and the at least one second subtask.
In another possible embodiment, the labeling manner may be that, in a plurality of subtasks, only the subtasks having the relevance are respectively labeled, or the relevance between each subtask and each other subtask is labeled on each subtask; for example, the following steps are carried out: for example, when each subtask of the target task is split, the relevance between each other subtask and the subtask may be labeled on each subtask directly, for example, the relevance mark between subtasks may be a relevance parameter, for example, any numerical value such as 0.2, 0.5, and the larger the numerical value is, the stronger the relevance between subtasks is; the association flag between the subtasks may be represented by, for example, label information 0 or 1, where, for example, 0 represents no association and 1 represents association; the relevance between the subtask and other subtasks can also be labeled directly by "having relevance" or "having no relevance". The content and the labeling form of the specific association indication information can be flexibly adjusted according to the user requirement, and are not limited to the embodiments described above.
Correspondingly, whether the first subtask and the at least one second subtask have relevance or not can be respectively determined according to the value of the relevance parameter between the first subtask and the at least one second subtask; for example, whether the first subtask and the at least one second subtask have relevance may be determined according to a value of an association parameter between the first subtask and the at least one second subtask, in combination with a preset parameter threshold. For example, when an association parameter between a first subtask and a second subtask is greater than or equal to a preset parameter threshold, it may be determined that the first subtask and the second subtask have an association, that is, if the first subtask is cancelled, the second subtask also needs to be cancelled; on the contrary, if the correlation parameter between the first subtask and the second subtask is smaller than the preset parameter threshold, it may be determined that there is no correlation between the first subtask and the second subtask, i.e., even if the first subtask is cancelled, the second subtask may still be executed.
In the method provided by the embodiment, the relevance between the first subtask and the at least one second subtask can be respectively determined through the relevance mark between the first subtask and the at least one second subtask, so that the judgment on the relevance between the subtasks can be more accurate, and the target task cancellation decision can be accurately executed effectively based on the relevance.
Optionally, on the basis of the above embodiment, another embodiment of the present application may further provide a robot task decision method, and an implementation process of the method is described as follows with reference to the accompanying drawings. Fig. 3 is a schematic flowchart of a robot task decision method according to another embodiment of the present application, and as shown in fig. 3, before S103, the method may further include:
s105: and splitting each task in the task stack under the preset task decision dimension to obtain a plurality of subtasks of each task under the preset task decision dimension.
In a specific implementation, each task in the task stack can be split according to the preset task decision dimensions, and if the task stack includes a plurality of task decision dimensions, each task can be split in the plurality of task decision dimensions by using a splitting mode corresponding to each task decision dimension, so as to obtain a plurality of subtasks of each task in each task decision dimension. For example, the preset task decision dimension may include at least one of the following: a temporal order dimension, a spatial dimension, a semantic viscosity dimension.
For example, each task may be split according to a description flag corresponding to a preset task decision dimension in each task, so as to obtain a plurality of subtasks of each task under the preset task decision dimension.
Each task in the task stack may be pre-labeled with a description mark corresponding to a preset task decision dimension, where the description mark may be used to indicate execution information of the task in the task decision dimension, such as an execution time sequence and an execution spatial position, or perform semantic association. Therefore, before splitting the task, whether the task has the corresponding description mark under the preset task decision dimension can be judged, and if the task has the description mark corresponding to the preset task decision dimension, the subtask splitting of the preset task decision dimension can be performed on each task according to the description mark.
For example, taking a time sequence dimension as an example, the description flag corresponding to the task in the time sequence dimension may be a flag having a time concept, for example, the description flag may be a time sequence description flag such as "first" or "last", or may also be a time point flag such as "ten points" or "ten minutes later". Taking the spatial dimension as an example, the description tag corresponding to the task in the spatial dimension may be a tag having a spatial concept, and may be, for example, a spatial description tag such as "room a", "room B", and the like.
Taking the semantic viscosity dimension as an example, the description labels corresponding to the tasks in the semantic viscosity dimension may be labels having a semantic relationship.
The description mark corresponding to each task in the task stack in the preset task decision dimension may be, for example, a description mark operation performed on the task in the preset task decision dimension when receiving a command issued by the task and when identifying the issued task.
Continuing to take the time sequence dimension, the space dimension and the semantic viscosity dimension as examples, in the process of executing task splitting, for example, whether each task in the task stack has the time sequence dimension, the space dimension and a description mark corresponding to the semantic viscosity dimension is respectively judged, and if a description mark corresponding to one dimension exists, the task can be split based on the description mark corresponding to the one dimension in the task; if the description marks corresponding to at least two dimensions exist, the task can be split according to the description marks corresponding to the at least two dimensions respectively.
S106: and performing the marking operation of the affiliated domain on each subtask, and performing the associated marking operation among the subtasks in each task.
In an embodiment of the present application, after performing sub-task splitting on a task in a task stack, a marking operation of a belonging domain may also be performed on each sub-task based on a splitting result of the sub-task to obtain a belonging domain mark of each sub-task, which is used to indicate a main task or a large task to which each sub-task belongs. For multiple subtasks belonging to the same task, the same belonging domain label may be marked. For example, the belonging domain flag may be, for example, a pointer flag of a task corresponding to each subtask in the task stack, so as to indicate an execution order of the task corresponding to each subtask.
In addition, the relevance between the subtasks in the plurality of subtasks obtained by splitting each task can be marked to obtain the relevance mark between the subtasks, such as the relevance indication information or the relevance parameters.
In the subsequent execution process of each subtask after marking, if the first subtask receives a cancellation operation, at least one second subtask belonging to the same task as the first subtask, namely a target task, can be quickly and accurately determined, the relevance between the first subtask and the second subtask can be quickly and accurately determined, and whether the second subtask is cancelled or not can be accurately determined, so that the cancellation decision of the target task is more quickly and accurately ensured. For example, for the subtasks with the same domain and relevance, as the cancelled subtask is cancelled, other subtasks without relevance can be continuously executed, thereby further improving the processing speed.
Optionally, on the basis of the above embodiment, another embodiment of the present application may further provide an implementation method for robot task decision in multiple task decision dimensions, where an implementation process for determining relevance in the above method is described as follows with reference to the accompanying drawings. Fig. 4 is a flowchart illustrating a robot task decision method according to another embodiment of the present application, where as shown in fig. 4, if the preset task decision dimension includes: multiple task decision dimensions, then S101 may include:
s107: an association of the first subtask with at least one second subtask in each task decision dimension is determined.
For example, an association of a first subtask with at least one second subtask in a temporal order decision dimension may be determined, and a temporal association of the first subtask and each second subtask in the temporal order dimension may be determined; determining the relevance of the first subtask to at least one second subtask in the spatial dimension, and determining the spatial relevance of the first subtask and each second subtask in the spatial dimension; the relevance of the first sub-task to at least one second sub-task in a semantic viscosity dimension may be determined, and the semantic relevance of the first sub-task and each second sub-task in the semantic viscosity dimension may be determined.
Correspondingly, S102 may include:
s108: and performing cancellation decision on the target task according to the relevance of each task decision dimension.
In implementation, according to the relevance of each task decision dimension, a cancellation decision can be made on a second subtask in the target task, which is associated with the first subtask correspondingly to the each task decision dimension. For example, according to the relevance in the time sequence dimension, namely the time relevance, the second subtask in the target task, which is time-related to the first subtask, can be cancelled, and according to the relevance in the space dimension, namely the space relevance, the second subtask in the target task, which is space-related to the first subtask, can be cancelled; and canceling a second subtask which is semantically related to the first subtask in the target task according to the relevance under the semantic viscosity dimension, namely the semantic relevance.
The second subtask needs to be cancelled when the first subtask is cancelled as long as the second subtask has an association with the first subtask in at least one dimension, only the second subtask having no association with the first subtask in each task decision dimension is determined to be a target subtask, the target subtask is executed independently of the first subtask, and the target subtask continues to be executed even if the first subtask is cancelled.
Optionally, on the basis of the foregoing embodiment, another embodiment of the present application may further provide a robot task decision method, and an implementation process of determining the relevance in the foregoing method is described as follows with reference to the accompanying drawings. Fig. 5 is a schematic flowchart of a robot task decision method according to another embodiment of the present application, and as shown in fig. 5, S101 may include:
s109: and if the task sources of the first subtask and the at least one second subtask are the same, determining the relevance of the first subtask and the at least one second subtask under a preset task decision dimension.
Illustratively, the task source may be used to indicate the object that issued the subtask, i.e., the task publisher, or the spatial location at which the subtask was issued, e.g., the location at which the publication time was. Then, by determining the task source, it may be determined whether the task issuer of the first subtask is the same person as the task issuer of the at least one second subtask, or whether the task issuer of the first subtask is a task issued by the same person at the same location. If the task sources of the subtasks are the same through the positions of the task publishers when the subtasks are published, if so, determining that the task sources corresponding to the subtasks are the same, otherwise, determining that the task sources corresponding to the subtasks with different positions of the task publishers are different; the audio information of each subtask is identified, whether the audio information corresponding to each subtask is the audio information sent by the same person or not is judged, if yes, the task source of each subtask is determined to be the same task source, otherwise, the audio information is determined to be sent by different persons, and the task source corresponding to each subtask is not the same task source.
Correspondingly, if the task source of the first subtask is different from that of the at least one second subtask, the first subtask is cancelled, and a next subtask of the first subtask in the at least one second subtask is executed.
After the task sources of the subtasks are judged by adopting the method, for each subtask of the same task source, the relevance among the subtasks needs to be judged, then the second subtask except the first subtask is determined, and whether the second subtask needs to be cancelled or adjusted after the first subtask is cancelled or not is determined; otherwise, for each subtask that is not the same task source, the relevance between the subtasks of different task sources is low, and the relevance between the subtasks does not need to be judged, and at this time, even if the first subtask is cancelled, the second subtask that is not the same task source as the first subtask can still be continuously executed. According to the method, the task source is judged first, and then the task relevance is judged, so that the task decision efficiency can be effectively improved.
According to the method, when the first subtask is cancelled, the relevance between the corresponding second subtasks is considered, the execution is not simply carried out according to the preset execution sequence of each subtask, but the execution sequence is intelligently adjusted, so that different tasks are intelligently executed after the first subtask is cancelled.
Fig. 6 is a schematic structural diagram of a robot task decision process according to another embodiment of the present application, and as shown in fig. 6, the robot task decision process is as follows:
s110: at least one task in the task stack is decomposed in a plurality of task execution dimensions.
For example, in some embodiments, for each task in the task stack, decomposition is performed in a chronological dimension, a spatial dimension, and a semantic viscosity dimension, respectively, and at least one sub-task corresponding to each task in each task dimension is determined.
S111: and sequentially executing each task according to the arrangement sequence of each task in the task stack, determining the currently executed task as a target task, and sequentially executing at least one subtask in the target task.
S112: it is determined whether there is a cancel command for the first subtask.
If the currently executed target task includes subtask 1, subtask 2, subtask 3, and subtask N, during the execution process, the subtask 1 receives a cancel command, and at this time, the subtask 1 is the first subtask, and the subtask 2, subtask 3, and subtask N are the second subtask.
If the determination result is yes, S113 is executed.
S113: and circularly judging the relevance between the first subtask and at least one second subtask in the target task corresponding to the first subtask.
For example, if a cancel operation on the subtask 1 is currently received, it needs to be determined whether the subtask 1 and the subtask 2 have a correlation, whether the subtask 1 and the subtask 3 have a correlation, and whether the subtask 1 and the subtask N have a correlation.
S114 is then executed.
S114: it is determined whether at least one second subtask has an association relationship with the first subtask.
If yes, go to step S115.
S115: the target task is cancelled and the next task is indexed from the task stack and executed.
And if the judgment result indicates that the subtask 2, the subtask 3 and the subtask N both have relevance with the subtask 1, namely that all the second subtasks have relevance with the first subtask which is cancelled currently, cancelling the current target task, and indexing and executing the next task from the task stack.
If the execution result of S113 is that there is a second subtask not associated with the first subtask in the second subtask, S116 is executed.
S116: and executing a second subtask which has no relation with the first subtask.
That is, if the execution result of S113 is that there is a second subtask that is not related to the first subtask in the second subtask, it indicates that at least one subtask that is not related to the subtask 1 exists in the subtask 2, and at this time, it is only necessary to cancel the subtask that is related to the first subtask and execute the second subtask that is not related to the first subtask.
The following describes a device, an apparatus, a storage medium, and the like for executing the robot task decision method provided by the present application, and specific implementation processes and technical effects thereof are referred to above, and will not be described again below.
Fig. 7 is a schematic diagram of a robot task decision device according to an embodiment of the present disclosure, and as shown in fig. 7, the robot task decision device 200 may include: a determination module 201 and a decision module 202, wherein:
the determining module 201 is configured to determine, if a cancel command of a first subtask is received, a relevance between the first subtask and at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension, where the at least one second subtask is another subtask after the first subtask in the target task in the preset task decision dimension.
And the decision module 202 is configured to make a cancellation decision for the target task according to the relevance.
Optionally, the decision module 202 is specifically configured to cancel the target task and execute a next task of the target task in the task stack if the at least one second subtask has relevance to the first subtask.
Optionally, the decision module 202 is specifically configured to, if a target subtask that is not associated with the first subtask exists in the at least one second subtask, cancel the first subtask, and execute the target subtask.
Optionally, the determining module 201 is specifically configured to determine at least one second subtask according to the belonging domain flag of the first subtask, where the at least one second subtask and the first subtask have the same belonging domain flag, and the belonging domain flag is used to indicate the target task; and respectively determining the relevance of the first subtask and the at least one second subtask according to the relevance mark between the first subtask and the at least one second subtask.
Optionally, the determining module 201 is specifically configured to determine whether the first subtask and the at least one second subtask have relevance according to association indication information between the first subtask and the at least one second subtask.
Fig. 8 is a schematic diagram of a robot task decision device according to an embodiment of the present application, and as shown in fig. 8, the device further includes: a splitting module 203 and a marking module 204, wherein:
the splitting module 203 is configured to split each task in the task stack in a preset task decision dimension to obtain multiple subtasks of each task in the preset task decision dimension.
And the marking module 204 is used for performing a marking operation of the domain of each subtask and an associated marking operation between subtasks in each task.
Optionally, the splitting module 203 is specifically configured to split each task according to the description flag corresponding to the preset task decision dimension in each task, so as to obtain a plurality of subtasks of each task in the preset task decision dimension.
Optionally, the determining module 201 is specifically configured to determine relevance of the first subtask to at least one second subtask in each task decision dimension;
the decision module 202 is specifically configured to make a cancellation decision for the target task according to the relevance of each task decision dimension.
Optionally, the determining module 201 is specifically configured to determine, if the task source of the first subtask is the same as that of the at least one second subtask, an association between the first subtask and the at least one second subtask in a preset task decision dimension.
Optionally, the decision module 202 is specifically configured to cancel the first subtask and execute a next subtask of the first subtask in the at least one second subtask if the task source of the first subtask is different from the task source of the at least one second subtask.
The above-mentioned apparatus is used for executing the method provided by the foregoing embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
The above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when one of the above modules is implemented in the form of a Processing element scheduler code, the Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. As another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).
Fig. 9 is a schematic diagram of another robot task decision device provided in an embodiment of the present application, which may be integrated in a robot controller inside a robot or an external controller communicatively connected to the robot.
The robot task decision device comprises: memory 601, processor 602. The memory 601 and the processor 602 are connected by a bus.
The memory 601 is used for storing programs, and the processor 602 calls the programs stored in the memory 601 to execute the above method embodiments. The specific implementation and technical effects are similar, and are not described herein again.
Optionally, the invention also provides a program product, for example a computer-readable storage medium, comprising a program which, when being executed by a processor, is adapted to carry out the above-mentioned method embodiments.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. 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.
The 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 invention 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, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer-readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think of the changes or substitutions within the technical scope of the present application, and shall cover the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (13)
1. A method for robot task decision-making, comprising:
if a cancel command of a first subtask is received, determining the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs under a preset task decision dimension, wherein the at least one second subtask is other subtasks behind the first subtask in the target task under the preset task decision dimension;
and according to the relevance, making a cancellation decision on the target task.
2. The method of claim 1, wherein the making a cancellation decision for the target task based on the relevance comprises:
and if the at least one second subtask and the first subtask have relevance, canceling the target task and executing a next task of the target task in a task stack.
3. The method of claim 1, wherein the making a cancellation decision for the target task based on the relevance further comprises:
and if a target subtask which is not related to the first subtask exists in the at least one second subtask, canceling the first subtask and executing the target subtask.
4. The method according to claim 1, wherein the determining of the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension comprises:
determining the at least one second subtask according to the belonging domain mark of the first subtask, wherein the at least one second subtask and the first subtask have the same belonging domain mark, and the belonging domain mark is used for indicating the target task;
and respectively determining the relevance of the first subtask and the at least one second subtask according to the relevance mark between the first subtask and the at least one second subtask.
5. The method of claim 4, wherein before determining the at least one second subtask according to the domain flag of the first subtask, the method further comprises:
splitting each task in the task stack under the preset task decision dimension to obtain a plurality of subtasks of each task under the preset task decision dimension;
and performing the marking operation of the domain of each subtask, and performing the associated marking operation among the subtasks in each task.
6. The method according to claim 5, wherein the splitting each task in the task stack in the preset task decision dimension to obtain a plurality of subtasks of each task in the preset task decision dimension comprises:
splitting each task according to the description mark corresponding to the preset task decision dimension in each task to obtain a plurality of subtasks of each task under the preset task decision dimension.
7. The method of claim 1, wherein if the predetermined task decision dimension comprises: if a plurality of task decision dimensions are provided, the determining of the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension includes:
determining an association of the first subtask with the at least one second subtask in each task decision dimension;
the making a cancellation decision for the target task according to the relevance comprises:
and performing a cancellation decision on the target task according to the relevance of each task decision dimension.
8. The method according to claim 1, wherein the determining of the relevance of the first subtask to at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension comprises:
and if the task sources of the first subtask and the at least one second subtask are the same, determining the relevance of the first subtask and the at least one second subtask under the preset task decision dimension.
9. The method of claim 8, further comprising:
and if the task sources of the first subtask and the at least one second subtask are different, canceling the first subtask and executing a next subtask of the first subtask in the at least one second subtask.
10. The method according to any one of claims 1-9, wherein the preset task decision dimension comprises at least one of the following dimensions: a temporal order dimension, a spatial dimension, a semantic viscosity dimension.
11. A robotic task decision-making apparatus, the apparatus comprising: a determination module and a decision module, wherein:
the determining module is configured to determine, if a cancel command of a first subtask is received, a relevance between the first subtask and at least one second subtask included in a target task to which the first subtask belongs in a preset task decision dimension, where the at least one second subtask is another subtask after the first subtask in the target task in the preset task decision dimension;
and the decision module is used for making a cancellation decision for the target task according to the relevance.
12. A robotic task decision device, comprising: a memory storing a computer program executable by the processor, and a processor implementing the robot task decision method of any of the preceding claims 1-10 when executing the computer program.
13. A storage medium having stored thereon a computer program which, when read and executed, implements a robot task decision method as claimed in any one of claims 1 to 10.
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