CN113243768A - Operation task execution method, kitchen robot, equipment and system - Google Patents

Abstract

The embodiment of the application provides a job task execution method, a kitchen robot, equipment and a system. In the embodiment of the application, corresponding services can be provided for a user based on the basic structured data, and under the condition that the basic structured data does not meet the actual requirements of the user, the basic structured data can be adjusted in the target adjustment dimension according to reference data provided by the user in the target adjustment dimension and by combining the basic usage of each data object in the basic structured data and the usage dependency relationship required by the kitchen robot to execute the job task, so that the target structured data meeting the actual requirements of the user can be obtained, and the kitchen robot is instructed to execute the job task according to the target structured data. In this embodiment, the kitchen robot can obtain a task execution effect expected by the user based on the task executed by the adjusted target structured data, so that the kitchen robot meets the actual requirements of the user, and is helpful for improving the user experience.

Description

Operation task execution method, kitchen robot, equipment and system

Technical Field

The application relates to the technical field of artificial intelligence, in particular to a method for executing a job task, a kitchen robot, equipment and a system.

Background

Along with the rapid development of artificial intelligence, more and more intelligent machines are applied to the life of people, for example, an intelligent cooking machine, and a user can finish the automatic cooking process by using the intelligent cooking machine in few participation steps, so that great convenience is brought to cooking of food.

In the prior art, the intelligent cooker can automatically execute cooking tasks according to the electronic menu, but the existing electronic menu may not meet the user requirements, so that the intelligent cooker cannot cook gourmet food meeting the user requirements.

Disclosure of Invention

Aspects of the application provide a job task execution method, a kitchen robot, equipment and a system, which are used for adjusting basic structured data according to adjustment dimensionality specified by a user to obtain target structured data meeting actual requirements of the user, so that the kitchen robot executes a job task according to the target structured data, and satisfactory service is provided for the user.

The embodiment of the application provides a job task execution method, which comprises the following steps: acquiring basic structured data, wherein the basic structured data at least comprise a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user on the target adjustment dimension; according to the reference data, the usage of at least part of the data objects is adjusted by combining the usage dependency relationship to obtain target structured data; and controlling the kitchen robot to execute the work task according to the target structured data, wherein the target structured data at least comprises target usage of each data object.

The embodiment of this application still provides a kitchen robot, kitchen robot still includes: the pot comprises a pot body, a heating base and a base for bearing the heating base; the heating base is used for heating the pot body in the process that the kitchen robot executes an operation task; the base is also provided with a weighing device; the kitchen robot is used for acquiring basic structural data, wherein the basic structural data at least comprises a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension in combination with the usage dependency relationship to obtain target structured data, wherein the target structured data at least comprises target usage of each data object; controlling the weighing equipment to weigh each data object according to the target usage amount of each data object, and executing the operation task aiming at each data object weighed by the weighing equipment; and the weighing device is used for weighing each data object according to the target consumption of each data object under the control of the kitchen robot so as to provide the corresponding consumption of the data objects for the kitchen robot.

An embodiment of the present application further provides a weighing apparatus, including: a weighing component, a processor and a memory storing a computer program; the processor to execute the computer program to: acquiring basic structured data, wherein the basic structured data at least comprise a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension and by combining the usage dependency relationship to obtain target structured data; controlling the kitchen robot to execute the operation task according to the target structured data, wherein the target structured data at least comprises target usage of each data object; and the weighing component is used for weighing the data objects according to the target usage of each data object so as to provide the corresponding usage data objects for the kitchen robot.

The embodiment of the present application further provides a kitchen robot operating system, including: the kitchen robot and the weighing equipment are in communication connection with the kitchen robot; the kitchen robot is used for acquiring basic structural data, wherein the basic structural data at least comprises a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension in combination with the usage dependency relationship to obtain target structured data, wherein the target structured data at least comprises target usage of each data object; controlling the weighing equipment to weigh each data object according to the target usage amount of each data object, and executing the operation task aiming at each data object weighed by the weighing equipment; and the weighing device is used for weighing each data object according to the target consumption of each data object under the control of the kitchen robot so as to provide the corresponding consumption of the data objects for the kitchen robot.

The embodiment of the present application further provides a kitchen robot operating system, including: the kitchen robot and the weighing equipment are in communication connection with the kitchen robot; the kitchen robot is used for acquiring basic structural data, wherein the basic structural data at least comprises a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; sending the infrastructure data to the weighing device; and executing the job task for each data object weighed by the weighing device; the weighing device is used for acquiring reference data provided by a user on a target adjustment dimension, and the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension in combination with the usage dependency relationship to obtain target structured data, wherein the target structured data at least comprises target usage of each data object; and weighing each data object according to the target consumption of each data object so as to provide the corresponding consumption data object for the kitchen robot.

In the embodiment of the application, corresponding services can be provided for a user based on the basic structured data, and under the condition that the basic structured data does not meet the actual requirements of the user, the basic structured data can be adjusted in the target adjustment dimension according to reference data provided by the user in the target adjustment dimension and by combining the basic usage of each data object in the basic structured data and the usage dependency relationship required by the kitchen robot to execute the job task, so that the target structured data meeting the actual requirements of the user can be obtained, and the kitchen robot is instructed to execute the job task according to the target structured data. In this embodiment, the kitchen robot can obtain a task execution effect expected by the user based on the task executed by the adjusted target structured data, so that the kitchen robot meets the actual requirements of the user, and is helpful for improving the user experience.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 is a flowchart of a job task execution method according to an embodiment of the present application;

fig. 2a is a schematic structural diagram of a kitchen robot operating system according to an embodiment of the present disclosure;

fig. 2b is a schematic structural diagram of another kitchen robot operating system according to an embodiment of the present disclosure;

fig. 3a is a schematic structural diagram of a kitchen robot according to an embodiment of the present disclosure;

fig. 3b is a schematic structural diagram of a weighing apparatus according to an embodiment of the present disclosure.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

With the rapid development of artificial intelligence, more and more intelligent devices are applied to daily life of people, for example, kitchen robots such as intelligent cooking machines, range hoods, dish washers, baking machines and the like are used to provide more convenient service for kitchen work, users can complete the kitchen work with little action participation, and the application of the kitchen robot is particularly important for young people who live at a fast pace and users who have insufficient experience in the kitchen work. Use intelligent cooking machine as an example, the user only needs to prepare material according to the suggestion of intelligent cooking machine, carries out operations such as simple selection and can accomplish culinary art food, and is simple convenient, labour saving and time saving.

The kitchen robot can rely on the structured data in the process of executing the job task, the structured data at least comprises the contents such as job steps corresponding to the job task, the execution sequence of the job steps, job conditions and the like, and the kitchen robot can execute corresponding actions according to the information in the structured data. Before executing the job task, the kitchen robot may preset structured data corresponding to the job task, or the kitchen robot may obtain the structured data corresponding to the job task from a terminal device or a server communicatively connected thereto, and a specific manner is not limited.

However, the content in the structured data may not meet the user's requirements, so that the kitchen robot cannot achieve the task effect expected by the user in the process of executing the task according to the structured data. In this case, in the embodiment of the present application, the basic structured data may be generated in advance, and the basic structured data may be standardized structured data on which the kitchen robot depends to execute the job task, and the basic structured data may include at least contents such as each data object required for the kitchen robot to execute the job task, a basic usage of each data object, and a usage dependency required for executing the job task. And if the basic structured data do not meet the requirements of the user, the basic structured data can be adjusted by combining the task execution effect expected by the user to obtain target structured data meeting the requirements of the user, and the kitchen robot is instructed to execute the corresponding operation task according to the target structured data.

Further, in the embodiment of the application, the task execution effect desired by the user is associated with the adjustment dimension supported by the infrastructure data, and the user is allowed to set the reference data on the adjustment dimension to embody the desired task execution effect, so that the datamation of the task execution effect is realized, the realization is simplified, and the performability of the scheme is improved. The adjustment dimensions supported by the infrastructure data have a corresponding relationship with the task execution effect, and the number of the adjustment dimensions can be one or more.

Based on the above, an embodiment of the present application provides a job task execution method, as shown in fig. 1, the method includes:

s1a, acquiring basic structured data, wherein the basic structured data at least comprises usage dependency relations required by the kitchen robot to execute the work task and basic usage of each data object.

And S2a, acquiring reference data provided by the user in the target adjustment dimension, wherein the reference data reflects the task execution effect expected by the user in the target adjustment dimension.

And S3a, adjusting the usage of at least part of the data objects according to the reference data and the usage dependency relationship to obtain the target structured data.

And S4a, controlling the kitchen robot to execute the task according to the target structured data, wherein the target structured data at least comprises the target usage of each data object.

The main body of the method according to the embodiment may be a kitchen robot, or may be a weighing device in communication connection with the kitchen robot, or the kitchen robot and the weighing device may be cooperatively executed. In addition, in this embodiment of the application, the weighing device may be a separate device or may be a part of the kitchen robot, and when the weighing device is implemented as a part of the kitchen robot, the weighing device may be separated from the kitchen robot or integrated with the kitchen robot, which is not limited thereto. In the embodiment of the present application, the method execution subject is not limited to the embodiment of obtaining the infrastructure data, and the following is an exemplary description of the embodiment of obtaining the infrastructure data:

mode 1: obtaining user configured infrastructure data

In this example, a display screen is provided on the kitchen robot or weighing device as the main body of the method execution, so as to provide a human-computer interaction interface including an infrastructure data generation function for a user, and the user can configure infrastructure data for the kitchen robot or weighing device through the human-computer interaction interface, and the kitchen robot or weighing device obtains the infrastructure data configured by the user in response to a configuration operation on the display screen. Specifically, the user can input information such as identification information of data objects required for executing the job task and basic usage of each data object through the human-computer interaction interface. Based on the information input by the user, the kitchen robot, or weighing device, may generate the infrastructure data required by the kitchen robot to perform the job task. The usage dependency relationship in the infrastructure data can be determined by a user and input to a kitchen robot or weighing device through a human-computer interaction interface; alternatively, the kitchen robot or the weighing device may combine some auxiliary information, such as attribute information of the data objects, an association relationship between the data objects, and/or a mutual constraint relationship between the usage of the data objects and the task execution effect, and calculate the usage dependency relationship required by the kitchen robot to execute the task based on information such as the basic usage of each data object input by the user.

Or

In this example, the kitchen robot or weighing device serving as the main body of the method execution has an audio module, and can perform voice interaction with the user, so that the user can provide the identification information of the data objects required for executing the job task and information such as the basic usage of each data object to the kitchen robot or weighing device in a voice manner, so that the kitchen robot or weighing device can generate the basic structured data. Accordingly, the usage dependency relationship in the infrastructure data may be provided to the kitchen robot or the weighing device by the user through a voice manner, or the kitchen robot or the weighing device may combine some auxiliary information, such as attribute information of the data objects, an association relationship between the data objects, and/or an interaction relationship between the usage of the data objects and the task execution effect, and calculate the usage dependency relationship required by the kitchen robot to execute the task based on information such as the basic usage of each data object input by the user.

Mode 2: receiving infrastructure data sent by terminal equipment

In this example, the terminal device may communicate with the kitchen robot or the weighing device as the main body of the method execution through wireless communication methods such as wifi, bluetooth and infrared laser, or wired communication methods such as usb data lines or other plug-in type. The terminal device can be a terminal device such as a smart phone or a tablet personal computer with a display screen, an application program corresponding to the kitchen robot can be installed in the terminal device, the application program provides a basic structured data generation function, and a user can input information such as each data object required by executing a job task and basic usage of the data object through the application program. The usage dependency in the infrastructure data may be determined by the user and input to the terminal device via the application; alternatively, the terminal device may calculate the usage dependency relationship required for the kitchen robot to execute the job task based on information such as the basic usage of each data object input by the user, in combination with auxiliary information such as attribute information of the data objects, an association relationship between the data objects, and/or a mutual constraint relationship between the usage of the data objects and the task execution effect. Based on the information input by the user, the terminal device may generate infrastructure data, and further, the terminal device may provide the generated infrastructure data to the kitchen robot or weighing device, or, in case of receiving a request from the kitchen robot or weighing device, provide the generated infrastructure data to the kitchen robot or weighing device.

Mode 3: obtaining infrastructure data from a server

In this example, the server has stored thereon infrastructure data required for various job tasks, and a kitchen robot or a weighing device, which is the subject of method execution, can communicate with the server. When a user wants to execute a certain job task, a job instruction can be sent to a kitchen robot or weighing equipment; the kitchen robot or the weighing device can respond to the received operation instruction and judge whether the basic structured data matched with the operation instruction exists locally; if there is no corresponding infrastructure data locally, the kitchen robot or weighing device may send a request to the server to request the server for the required infrastructure data. Alternatively, the user may request the server for infrastructure data required by the kitchen robot to perform the job task through the terminal device, and the terminal device provides the requested infrastructure data to the kitchen robot or the weighing device.

The basic structured data stored on the server can be preset or uploaded by different users. For example, different users may generate infrastructure data required for performing a job task on a kitchen robot, a weighing device, or a terminal device, and the relevant generation manner may be as described above; in the case that the kitchen robot, the weighing device or the terminal device generates the infrastructure data, the generated infrastructure data may be transmitted to the server for the server to store.

Further optionally, in the case that the method execution subject is a weighing device, the manner in which the weighing device acquires the infrastructure structured data may also be: infrastructure data provided by a kitchen robot in communicative connection with the kitchen robot is received. Specifically, a user sends a work instruction to the kitchen robot, the kitchen robot acquires infrastructure data adapted to the work instruction from a local terminal device or a server side, and sends the infrastructure data to the weighing device, so that the weighing device can weigh a data object with required usage amount for the weighing device.

No matter which way is adopted to obtain the basic structured data, the basic structured data at least comprises the usage dependency relationship required by the kitchen robot to execute the operation task and the basic usage of each data object. The data object is an object which is needed by the kitchen robot to execute the operation task, and the data object is different according to different scenes, and can be various food materials, seasonings and the like needed in the process of cooking food by taking a cooking machine as an example. Accordingly, the basic usage of the data object refers to a standard usage of the data object that needs to be used when the kitchen robot performs the job task according to the basic structured data, and the usage can be measured by volume, weight, quantity, or the like for different types of data objects. For example, if the data object is a liquid object, the basic amount may be 50 ml, 30 ml, etc.; if the data object is a solid object, the basic usage may be 100 grams, 500 grams, etc.; if the data object is a solid object that can be measured in number, its base usage can also be 3, 4, etc. Of course, whether the object is a liquid or solid object, the basic dose of the data object may also be measured by a standard gauge, such as a measuring spoon, which may be, for example, 3 measuring spoons, 4 measuring spoons, etc. The usage dependency in the infrastructure data is used to define usage of at least some of the data objects or usage relations between some of the data objects, which usage dependency may affect the task performance of the kitchen robot to some extent. The usage dependency is a universal dependency and is not only applicable to the infrastructure data, i.e. the usage dependency needs to be considered no matter what kind of structured data the kitchen robot performs the task.

In addition to the above, the basic structured data may further include attribute information of each data object, a work step required by the kitchen robot to execute a work task, a correspondence between the work step and the work object, and a work condition, so that the kitchen robot can successfully and efficiently complete the work task. In different application scenarios, the data objects and attribute information included in the infrastructure data may be different. For example, the attribute information of the data object may be information such as a category and/or a priority of the data object. Wherein the priority or class of the data objects reflects the importance of each data object in the process of executing the task by the kitchen robot. Based on this, the user can selectively adjust the data objects according to their categories and/or priorities. Taking a cooking scene as an example, the infrastructure data may be an electronic menu, the data object may be a food material, optionally, the attribute information corresponding to the data object may be a heat coefficient or information such as a certain nutritional value coefficient, priority, category, retention degree, and the like, and the information reflects the correlation of the quality such as taste, color, and the like of the food material and the gourmet food to a certain extent. For example, if a user wants to cook a piece of gourmet food, and the existing food materials in the family are not all food materials contained in the electronic menu, the user can remove the food materials with lower priorities according to the priorities of the food materials in the electronic menu, so that the cooking can be completed by using the existing food material resources without affecting the overall cooking effect.

In the embodiment of the application, the task execution effect expected by a user is associated with the adjustment dimension supported by the basic structured data, and the user is allowed to set the reference data on the adjustment dimension to embody the expected task execution effect, so that if the basic structured data does not meet the requirement of the user on the task execution effect, the user can provide the reference data capable of reflecting the expected task execution effect on the target adjustment dimension; based on reference data provided by a user in a target adjustment dimension, the basic structured data can be adjusted by combining the usage dependency relationship in the basic structured data. Wherein the target adjustment dimension is a dimension that the user desires to adjust for the data object. For example, taking a cooking scene as an example, if the structured data is an electronic recipe and the data object is a food material, the target adjustment dimension may be a dosage dimension, a heat dimension, or a taste dimension; the consumption dimension refers to the adjustment of the consumption of the food materials appointed by the user; the heat dimension refers to the adjustment of the total heat of each food material in the electronic menu; the taste dimension refers to the adjustment of the taste of the delicious food cooked according to the electronic menu; correspondingly, the reference data provided by the user in the target adjustment dimension may be a caloric value, a usage value, or a taste type of the food material, and indicates that the user expects the kitchen robot to adjust the food material according to the caloric value, the usage value, or the taste type provided by the user, so that the cooked food material achieves an effect expected by the user.

In the embodiment of the application, a certain dependency relationship exists between the usage of partial data objects in the infrastructure data or a certain constraint exists in the usage of some data objects, that is, in the case that the usage of a certain data object changes, the usage of one or more data objects having a dependency relationship with the usage changes. Therefore, in the case of determining a target adjustment dimension desired by a user and reference data on the target adjustment dimension, the usage of at least a part of the data objects can be adjusted according to the reference data and in combination with the usage dependency relationship to obtain target structured data. In this embodiment, the target structured data at least includes a target usage of each data object, and the target usage refers to a usage of each data object obtained after adjustment. Further, in the case of obtaining the target structured data, the kitchen robot may be controlled to perform the job task according to the target structured data.

In the embodiment of the application, corresponding services can be provided for a user based on the basic structured data, and under the condition that the basic structured data does not meet the actual requirements of the user, the basic structured data can be adjusted in the target adjustment dimension according to reference data provided by the user in the target adjustment dimension and by combining the basic usage of each data object in the basic structured data and the usage dependency relationship required by the kitchen robot to execute the job task, so that the target structured data meeting the actual requirements of the user can be obtained, and the kitchen robot is instructed to execute the job task according to the target structured data. In this embodiment, the kitchen robot can obtain a task execution effect expected by a user based on the adjusted job task executed by the target structured data, so that the actual requirements of the user are met, and the user experience is improved.

In the above embodiment, the method for acquiring the reference data by the execution main body is not limited, and optionally, the execution main body may be provided with a display screen for displaying a human-computer interaction interface, and the human-computer interaction interface may include a parameter setting item for a user to operate the parameter setting item and set the reference data in the target adjustment dimension. In this embodiment, the manner in which the user operates the parameter setting items is not limited, but in one embodiment, if there is only one adjustment dimension, the adjustment dimension is the target adjustment dimension, and the user can directly operate the parameter setting item corresponding to the adjustment dimension; in another embodiment, if there are multiple adjustment dimensions, the parameter setting item may include a dimension selection item and a numerical value setting item, and the kitchen robot may obtain a target adjustment dimension selected by the user from the adjustment dimensions in response to a selection operation of the user on the dimension selection item, and further obtain reference data in the target adjustment dimension set by the user in response to a setting operation of the user on the numerical value setting item.

In this embodiment, the user may operate the parameter setting item differently according to different implementation forms of the parameter setting item. For example, the parameter setting item is in the form of a selection button or a drop-down list, and the user can determine the reference data through selection operation; the parameter setting item is in a text box form, and a user can determine reference data through editing operation; the parameter setting item is in the form of a scroll bar or a sliding rod, and the user can determine the reference data through up-down or left-right sliding operation, and the specific implementation form can be determined according to the implementation form of the parameter setting item, which is not limited herein. Further, the execution main body can respond to the setting operation of the user on the parameter setting item, obtain reference data on a target adjustment dimension set by the user, and adjust the usage of at least part of the data objects by combining the usage dependency relationship according to the reference data.

Further optionally, an implementation manner of the usage dependency relationship in the embodiment of the present application may include a data object having a usage compensation relationship in each adjustment dimension and a corresponding usage compensation coefficient. For any adjustment dimension, the data object having a usage compensation relationship in the adjustment dimension refers to a data object having a usage limit or constraint in the adjustment dimension; accordingly, a usage compensation factor refers to a compensation factor used to limit or constrain the usage of the data object. For example, taking a cooking scene as an example, the structured data is an electronic recipe, the data objects are food materials, if the target adjustment dimension is a heat dimension, when the heat of the electronic recipe is adjusted, a part of the food materials having an influence on the heat of the electronic recipe is the data objects having a usage compensation relationship, and when the usage of the food materials is adjusted, a limit or constraint relationship among the usage of the food materials is represented by a usage compensation coefficient; if the target adjustment dimension is a consumption dimension, when the consumption of a certain specified food material in the electronic menu is adjusted, if the consumption of other parts of food materials needs to be adjusted, the specified food material and the parts of food materials have a consumption compensation relation, and the adjusted quantity of the consumption of the parts of food materials is represented by a consumption compensation coefficient; if the target adjustment dimension is a mouth feel dimension, the food materials influencing the target mouth feel are data objects having a dosage compensation relation with the target mouth feel, and when the dosage of the data objects is adjusted, the dosage adjustment amount and the restriction or constraint relation of the target mouth feel are represented by dosage compensation coefficients.

Based on this, the implementation manner of the above step S3a includes: and determining a target data object with a usage compensation relation on a target adjustment dimension and a corresponding target usage compensation coefficient from the usage dependency relation, and adjusting the usage of the target data object according to the reference data and the target usage compensation coefficient to obtain target structured data. The target data object refers to a data object with usage limitation or constraint on a target adjustment dimension; the target usage compensation coefficient refers to a compensation coefficient for limiting or constraining usage of the target data object. In this embodiment, the target data objects may be one or more types, and the types of the target data objects may also be different according to different target adjustment dimensions, and further, the types of the reference data provided by the user in different target adjustment dimensions may also be different, which is not limited herein.

For example, if the data object is a food material, and the target adjustment dimension is a heat dimension, the reference data is a target total heat; or, the target adjustment dimension is a usage dimension, and the reference data is a target usage of the specified data object; or the target adjustment dimension is a mouthfeel dimension, and the reference data is a target mouthfeel. Correspondingly, in the dimension of heat and the dimension of consumption, the types of the corresponding target data objects can be various; in the mouth-feel dimension, the kind of the corresponding target data object may be one.

Taking the kitchen robot to execute the task related to the food material as an example, the following processes of adjusting the food material from the dimension of heat, the dimension of dosage and the dimension of mouthfeel by the kitchen robot are respectively exemplified:

1. thermal dimension:

in this embodiment, a user may set a target total heat as reference data in a heat dimension, and before the kitchen robot adjusts the target data object, a data object having a usage compensation relationship among the data objects and a usage compensation coefficient corresponding to the data object may be determined from the usage dependency relationship and respectively used as the target data object and the target usage compensation coefficient. And further calculating a first quantity adjusting coefficient according to the target total heat and the basic quantity of each data object, and adjusting the quantity of the target data object according to the first quantity adjusting coefficient and the target quantity compensation coefficient to obtain target structured data. In this embodiment, the basic total heat of the basic structured data may be calculated according to the basic usage of each data object, and then the first amount adjustment coefficient may be calculated according to the target total heat and the basic total heat; wherein, the first quantity adjusting coefficient refers to a proportionality coefficient of the target total heat quantity and the basic total heat quantity. Optionally, the basic structured data further includes a heat coefficient of each data object, and when calculating the basic total heat, the heat of each data object may be calculated according to the basic usage of each data object and the corresponding heat coefficient, and the heat of each data object is summed to obtain the total heat of the basic structured data.

Further optionally, the infrastructure data further includes a category attribute and/or a priority attribute of each data object, and the kitchen robot may further determine a reference data object and a non-reference data object in the target data object according to the category attribute and/or the priority attribute of the target data object. The reference data object is a data object which plays a decisive role in adjusting heat quantity in data objects having a usage compensation relationship, the non-reference data object is a data object which only plays an auxiliary role in adjusting heat quantity, and the adjustment of the non-reference data object is determined according to the adjustment of the reference data object. In this embodiment, the correspondence relationship between the basic data object and the non-reference data object is not limited, and for example, one type of reference data object may correspond to one type of non-reference data object, or may correspond to a plurality of types of non-reference data objects. Taking food materials as an example, the main food material can be regarded as a reference data object, the complementary food material can be regarded as a non-reference data object, and the main food material in one dish can correspond to one complementary food material and can also be used for multiple complementary food materials. For example, in the hot and sour shredded potatoes, potatoes are used as a main food material, peppers are used as a subsidiary food material, and the main food material and the subsidiary food material are in a one-to-one relationship; for example, in the shredded pork with a fish flavor, meat is a main food material, carrot, agaric and winter bamboo shoot are subsidiary food materials, and the main food material and the subsidiary food materials are in a one-to-many relationship.

In general, if other conditions are not changed, the amount of heat is generally proportional to the amount of heat used, and the amount of heat can be adjusted by adjusting the amount of heat used. According to the above, the first quantity adjustment coefficient reflects a proportional relationship between the target total heat quantity and the basic total heat quantity, and the first quantity adjustment coefficient can also reflect a proportional relationship between the target quantity and the basic quantity of the data object. Therefore, when the kitchen robot adjusts the target data object, the kitchen robot may determine the target usage of the reference data object according to the first usage adjustment coefficient and the basic usage of the reference data object, and then determine the target usage of the non-reference data object according to the target usage of the reference data object, the target usage compensation coefficient, and the basic usage of the non-reference data object. And then, the usage of the reference object and the usage of the non-reference object are respectively adjusted according to the determined target usage, so that the purpose of adjusting the heat quantity is achieved by adjusting the usage of the data object.

For example, taking an example that a user cooks eggs with tomatoes by using an intelligent cooker, assuming that a target total calorie that the user wishes to take is 300 calories, but a basic total calorie calculated according to the usage amount and calorie coefficient of each food material and ingredient in the current recipe is 450 calories, the dishes cooked according to the current recipe cannot meet the dietary requirements of the user. The intelligent cooker may determine that the first quantity adjustment factor is 1/3 according to the target total calorie being 300 calories and the base total calorie being 450 calories, i.e., the target total calorie is reduced 1/3 from the base total calorie. Further, determining a reference food material and a non-reference food material according to the category and the priority of each food material in the eggs fried by the tomatoes, and adjusting the consumption of the non-reference food material according to the consumption of the reference food material.

Alternatively, in the example of stir-frying eggs with tomatoes, tomatoes may be used as the reference food material, and eggs may be used as the non-reference food material, and the ratio of the two usage amounts is the target usage amount compensation coefficient. For example, if the dosage ratio of the tomatoes to the eggs is 1:1, the corresponding target dosage compensation coefficient is 1; if the dosage ratio of the tomatoes to the eggs is 1:1.5, the corresponding target dosage compensation coefficient is 1.5. Further, when the intelligent cooker adjusts the using amounts of tomatoes and eggs, the using amount of the tomatoes can be reduced by 1/3 according to a first amount adjusting coefficient, namely 1/3, and the basic using amount of the eggs is adjusted according to the adjusted using amount of the tomatoes and a target using amount compensating coefficient, so that the ratio of the using amounts of the tomatoes and the eggs after adjustment is still 1:1.5, and the overall taste and color of the dish can be guaranteed not to be affected under the condition that the heat demand of a user is met.

2. Dosage dimension:

when the target adjustment dimension is the usage dimension, the usage of the target data object may be adjusted according to the data object specified by the user, and based on this, the user may set the usage of the specified data object as the reference data in the usage dimension. In the case that the kitchen robot determines that the usage adjustment of the target data object is required, a data object having a usage compensation relationship with the designated data object may be determined from the usage dependency relationship as the target data object, and a usage compensation coefficient between the designated data object and the target data object may be determined as the target usage compensation coefficient. And then, according to the reference data and the target usage compensation coefficient, adjusting the usage of the target data object to obtain target structured data. Alternatively, a second usage adjustment coefficient may be calculated according to the base usage and the target usage of the designated data object, and then the target usage of the target data object may be determined according to the second usage adjustment coefficient and the target usage compensation coefficient, where the second usage adjustment coefficient is a proportionality coefficient between the target usage of the designated data object and the base usage. And when the target usage of the target data object is determined, adjusting the usage of the target data object by taking the proportion coefficient of the target usage of the target data object and the basic usage as a target and meeting the second usage adjustment coefficient.

For the process of adjusting the usage amount of the target data object according to the usage amount of the designated data object, reference may be made to the above-mentioned exemplary description of adjusting the usage amount of the non-reference data object according to the target usage amount of the reference data object in the thermal dimension, and details are not repeated here.

3. Mouthfeel dimension

In the case that the target adjustment dimension is a taste dimension, the reference data set by the user may be a usage amount of a data object having an influence on the target taste, and the usage amount reflects a taste degree to which the user desires the target taste after adjustment. For example, for salty taste, the user can set different amounts of salt to reflect different adjusted saltiness, optionally, trace amounts indicate slight saltiness, normal amounts indicate normal saltiness, small amounts indicate slight saltiness, large amounts indicate slight saltiness, and the like. In this embodiment, the usage amount of the data object corresponding to each taste in different degrees may be determined according to the individual eating habits, or may be determined according to the influence degree of each taste on the human health, which is not limited herein.

Based on the above, when it is determined that the taste of the target data object needs to be adjusted, the kitchen robot may determine, from the usage dependency relationship, a data object having a usage compensation relationship with the target taste as the target data object, and may use a usage compensation coefficient between the target taste and the target data object as the target usage compensation coefficient. The consumption compensation relation reflects the corresponding relation between the data objects and the mouthfeel, and the consumption of which data object can be adjusted can be determined through the consumption compensation relation so as to realize the adjustment of the target mouthfeel; the dosage compensation coefficient reflects the corresponding relation between the dosage variation of the data object and the mouthfeel degree, and the dosage compensation coefficient can determine how much the dosage of the corresponding target data object should be changed from the current mouthfeel to the target mouthfeel. Furthermore, when the usage of the target data object is adjusted, the target usage of the target data object under the target taste can be determined according to the target usage compensation coefficient and the basic usage of the target data object.

For example, if the taste corresponding to the current recipe is slightly light and the amount of the corresponding refined salt is trace, and the user wants to increase the amount of the salt, the adjusted amount of the refined salt can be determined by setting the reference data of the salty taste. Assuming that the amount of refined salt is 20g for every increase or decrease of different saltiness degrees in the dimension of salty taste, if a user wants to have normal salty taste, the user can set the reference data of salty taste as normal amount, i.e. the amount of refined salt is increased by 20g from weak taste to normal salty taste. The kitchen robot can determine to increase the salt dosage by 20g according to the reference data set by the user so as to adjust the salty taste from slight to normal salinity and meet the taste requirement of the user.

Optionally, in each of the above embodiments, in the process of adjusting the usage amount of the target data object, the kitchen robot may further set a corresponding usage amount adjustment threshold for different data objects, so as to avoid that the adjusted target usage amount is too much or too little to affect the operation effect. Further optionally, if the target data object is adjusted, the requirement of the user still cannot be met, and the usage amount of some data objects or data objects may be increased or deleted according to the type and priority of the data object, so that the target structured data meets the actual requirement of the user. For example, taking the adjustment of the infrastructure data from the heat dimension as an example, if the total heat calculated after the adjustment is still greater than the target total heat, the data objects with lower priorities may be removed according to the priorities of the data objects, so that the total heat is less than or equal to the target total heat without affecting the operation effect.

In an optional embodiment, the basic structured data may further include a corresponding retention degree of the data object in the adjustment dimension, so as to represent a remaining amount of the data object in the target adjustment dimension after the kitchen robot performs the task. For example, in the above embodiment, if the heat or weight of some food materials before and after cooking changes, or there is a problem of volatilization or evaporation of liquid or solid, which may affect the taste, when determining the usage amount of the target data object in the dimensions of heat, usage amount and taste, on the basis of calculating the target usage amount, the corresponding final target usage amount of the target data object after the kitchen robot performs the task may be further determined in combination with the corresponding persistence degree in the target dimension, so as to determine the performing effect of the kitchen robot according to the final target usage amount.

The target adjustment dimension is only an exemplary illustration, and in the case that the data object is a food material, the target adjustment dimension may also be the content of a certain type of component, for example, the content of components such as vitamins, proteins, and cellulose; or the cold and hot attribute values corresponding to the total food materials; but also the degree of maturity of the food material, etc. Of course, under the condition that the data object is not a food material, the corresponding target adjustment dimension may also be other content, and may be specifically determined according to the application scenario and the type of the data object, which is not limited herein.

In the embodiment of the application, the target structured data further comprises a working step and a corresponding relation between the working step and the data object, so that when the kitchen robot is controlled to execute the working task according to the target structured data, the kitchen robot can be controlled to execute the working step in sequence to complete the working task; and weighing the first data object according to the target usage of the first data object under the condition that the currently executed operation step corresponds to the first data object, so that the kitchen robot can execute the currently executed operation step according to the first data object.

Further optionally, in the process of weighing the first data object, if the actual usage of the first data object is matched with the target usage thereof, continuously weighing the other data objects according to the target usage of the other data objects; and if the actual usage of the first data object is not matched with the target usage of the first data object, determining a second data object having a usage compensation relationship with the first data object and a corresponding first usage compensation coefficient according to the usage dependency relationship, and calculating the actual usage of the second data object according to the actual usage of the first data object and the first usage compensation coefficient, so as to weigh the second data object according to the actual usage of the second data object in a subsequent weighing process.

Optionally, when calculating the actual usage of the second data object, a third usage adjustment coefficient may be determined according to the actual usage of the first data object and the target usage, and the actual usage of the second data object may be calculated according to the third usage adjustment coefficient and the first usage compensation coefficient, so that the proportion between the actual usage of the first data object and the actual usage of the second data object still satisfies the first usage compensation coefficient. For the process of calculating the actual usage amount of the second data object according to the actual usage amount of the first data object in the weighing process, reference may be made to the above-mentioned exemplary description of adjusting the usage amount of the non-reference data object according to the target usage amount of the reference data object in the thermal dimension, and details are not repeated here.

It should be noted that the execution subjects of the steps of the methods provided in the above embodiments may be the same device, or different devices may be used as the execution subjects of the methods. For example, the execution subjects of steps S1a to S4a may be device a; for another example, the execution subject of steps S1a to S3a may be device a, and the execution subject of step S4a may be device B; and so on.

In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations occurring in a specific order are included, but it should be clearly understood that the operations may be executed out of the order they appear herein or in parallel, and the sequence numbers of the operations, such as S1a, S2a, etc., are merely used to distinguish between the various operations, and the sequence numbers themselves do not represent any execution order. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor limit the types of "first" and "second" to be different.

In the above embodiments, the description has been given with the emphasis on the case where the kitchen robot or the weighing device is used alone as the main execution body, and the following embodiments of the present application also provide a kitchen robot work system, which explains the flow of the work task execution method from the perspective of the kitchen robot and the weighing device in cooperation with each other. Fig. 2a and 2b are schematic diagrams of a kitchen robot operating system provided in an embodiment of the present application, and as shown in fig. 2a or 2b, the system includes a kitchen robot 10 and a weighing device 20 communicatively connected to the kitchen robot 10. The system can execute the job task by adopting the following two ways:

mode 1: the kitchen robot 10 is responsible for obtaining target structured data based on the infrastructure structured data, and the weighing device 20 is responsible for weighing the respective data object according to the target structured data

In the present embodiment, the kitchen robot 10 is configured to obtain infrastructure data, which at least includes usage dependencies required by the kitchen robot 10 to perform a job task and basic usage of each data object. In this embodiment, a data object adjustment function is further provided, and a user can adjust data objects in the basic structured data from different dimensions. Alternatively, the kitchen robot 10 may acquire reference data provided by the user in the target adjustment dimension, which reflects the task performance effect desired by the user. If the reference data provided by the user is inconsistent with the corresponding data in the basic structured data, the kitchen robot 10 may adjust the usage of at least a portion of the data objects according to the reference data in the target adjustment dimension in combination with the usage dependency relationship to obtain the target structured data; the target structured data at least comprises target usage of each data object. Based on this, as shown in fig. 2a, the kitchen robot 10 can control the weighing device 20 to weigh each data object according to the target usage of each data object; the weighing device 20 may weigh each data object according to a target usage amount of each data object under the control of the kitchen robot 10 to provide the kitchen robot 10 with data objects of corresponding usage amounts; further, the kitchen robot 10 may perform a task for each data object weighed by the weighing device 20.

Mode 2: the kitchen robot 10 is responsible for acquiring infrastructure data, and the weighing device 20 is responsible for obtaining target structured data based on the infrastructure data provided by the kitchen robot 10, and weighing each data object according to the target structured data.

In this embodiment, the kitchen robot 10 is configured to obtain infrastructure data, which includes at least usage dependencies required by the kitchen robot to perform a task and base usage of each data object. Further, as shown in fig. 2b, the kitchen robot 10 may send the infrastructure data to the weighing device 20 for the weighing device 20 to adjust the infrastructure data. The weighing device 20 may obtain reference data provided by the user in the target adjustment dimension, which reflects the task performance effect desired by the user; further, the weighing device 20 may adjust the usage of at least a portion of the data objects according to the reference data in the target adjustment dimension in combination with the usage dependency relationship to obtain target structured data; the target structured data at least comprises target usage of each data object. Based on this, as shown in fig. 2b, the weighing device 20 may weigh each data object according to the target usage amount of each data object, and provide the kitchen robot 10 with the data object of the corresponding usage amount, so that the kitchen robot 10 may perform a task for each data object weighed by the weighing device 20.

In the above embodiment, the manner of acquiring the infrastructure data by the kitchen robot 10 is not limited, as shown in fig. 2a and fig. 2b, the system may further include a server 30 and a terminal device 40, and the kitchen robot 10 may acquire the infrastructure data provided by the user through the kitchen robot 10, may also acquire the infrastructure data from the server 30, or acquire the infrastructure data provided by the user at the terminal device 40, and the specific implementation form may be set according to the actual application requirements.

Further alternatively, in the case that the kitchen robot 10 cooperates with the weighing device 20 to execute a job task, after obtaining the target structured data, the kitchen robot 10 may send a first instruction to the weighing device 20 to instruct the weighing device 20 to provide the first data object thereto, in the case that the executed job step needs to obtain the actual usage amount of the first data object, according to the job step in the target structured data and the corresponding relationship between the job step and the data object. Further, the weighing device 20 may weigh the first data object after receiving the first instruction, and provide the first data object and the actual usage to the kitchen robot 10 after weighing the first data object. After the kitchen robot receives the first data object weighed by the weighing device 20, it can continue to execute the current operation step according to the first data object and the actual usage amount.

Further optionally, after the kitchen robot 10 obtains the actual usage amount of the first data object, if it is determined that the actual usage amount of the first data object does not match the target usage amount, the actual usage amount of the second data object having a usage amount dependency relationship with the first data object may be calculated according to the target usage amount, the actual usage amount, and the usage amount dependency relationship of the first data object; and sending a second instruction to the weighing device 20, instructing the weighing device to weigh the second data object according to the calculated actual usage amount, and providing the second data object and the weighed actual usage amount to the kitchen robot 10, so that the kitchen robot 10 continues to execute the task according to the second data object weighed by the weighing device until the task is cooperatively executed.

In addition to the above embodiments, the weighing device 20 may also automatically weigh the first data object according to the work steps in the target structured data and the corresponding relationship between the work steps and the data objects, and after weighing each data object, wait for the kitchen robot 10 to acquire the weighed data objects according to the sequence of the executed work steps.

In the above embodiments, the specific implementation form of the kitchen robot is not limited, and alternatively, the kitchen robot may be implemented as an intelligent kitchen appliance such as a cooker or a baker. The following takes a cooking scenario as an example to illustrate the implementation of the above method embodiment. The executive main kitchen robot is a cooking machine, the structured data is an electronic menu, the data objects are food materials and seasonings, and the target adjustment dimension is the consumption, heat or taste of the food materials or the seasonings.

1: target tuning dimension is heat dimension

In this example, the user wants to cook eggs fried with tomatoes by using the cooking machine, and the corresponding basic electronic recipe includes a food material list, where the food material list includes a plurality of food materials and attribute information of the food materials as shown in table 1a, and the attribute information of the food materials includes: weight of food material, caloric coefficient, category, priority and degree of retention. The remaining degree is the amount of each food remaining after cooking relative to the amount of each food remaining before cooking. The cooking machine can calculate the basic total heat of the eggs fried by the tomatoes cooked according to the basic electronic menu according to the information in the basic electronic menu, and optionally, the basic total heat can be calculated by: the basic total heat was calculated in the form of "type of food material 1, weight, heat coefficient, storage … + type of food material n, weight, heat coefficient, storage". In this example, the base total calories of tomato-fried eggs cooked according to the base electronic recipe calculated from the information in Table 1a was about 429 calories.

Before instructing the cooker to execute a cooking task according to a basic electronic menu, a user can set a target total heat of the eggs fried by tomatoes expected to be cooked according to the eating habits of the user, taking 300 calories as an example. If the target total calorie set by the user is 300 calories, the calorie regulation factor is determined to be 1/3 in combination with the basic total calorie, i.e., the basic total calorie needs to be reduced by about 1/3 to meet the calorie requirement requested by the user. Further, the cooker can adjust the consumption of each food material according to the heat adjustment coefficient 1/3 to obtain a target electronic menu with a final total heat equal to or close to 300 calories.

Table 1b is partial information of the dose dependency relationship table provided in this embodiment, which includes information of the reference food material, the non-reference food material, the dose compensation coefficient, the dose compensation threshold, and the like. Alternatively, when the consumption of each food material is adjusted, a target food material may be determined according to table 1b, and taking egg liquid and peanut oil as examples, the target food material is divided into a reference food material (i.e., egg liquid) and a non-reference food material (i.e., peanut oil), wherein the consumption compensation coefficient represents a corresponding relationship between the consumption change ratio of the non-reference food material and the consumption change ratio of the reference food material. Further, under the condition that the reference food material and the non-reference food material are determined, the target consumption of the reference food material can be determined according to the basic consumption and the heat adjustment coefficient of the reference food material; further, the target consumption of the non-reference food material can be determined according to the target consumption of the reference food material and the consumption compensation coefficient.

Taking the egg liquid and the peanut oil as examples, as can be seen from table 1a that the dosage of the egg liquid is 150g, the dosage of the egg liquid can be synchronously reduced 1/3 to reduce the total heat quantity 1/3, wherein the retention degree of the egg liquid is 1, namely the residual quantity after cooking is unchanged, and the target dosage of the egg liquid is determined to be 100 g. Further, according to the amount compensation factor of +1 in table 1b, it can be determined that the amount of peanut oil and egg liquid is the same, i.e. the amount of peanut oil needs to be reduced by 1/3. In combination with a peanut oil weight of 32g and a corresponding retention of 0.5 in table 1a, the target amount of peanut oil, i.e. 21g, can be calculated by 32 x (1- (150-100)/150 x 1).

Optionally, when the usage amount of each food material in the basic electronic menu is adjusted, the usage amount can be selectively adjusted according to the category and the priority of the food material. For example, selecting and adjusting the food material category which has a main influence on the cooking effect of the current dish; or adjusting the food materials with higher priority. For example, in the implementation, the amount of the egg liquid, the tomato and the peanut oil which are used as food materials with higher priority is selected to be adjusted, and the amount of other seasonings with lower priority is not adjusted. The adjusted food material list is shown in table 1c, and the corresponding target total calorie is 293.431, which meets the actual demand of the user.

TABLE 1a

Food material	Weight (D)	Coefficient of heat/(100 g)	Categories	Priority level	Degree of retention
						Egg liquid	150g	139	Staple food	Height of	1
Tomato fruit	350g	15	Auxiliary materials	Height of	0.9
						Chopped green onion	6g	27	Small material	In	1
Peanut oil	32g	899	Seasoning	In	0.5
						Water purification	26g	0	Seasoning	In	0.3
Refined salt	3.2g	0	Seasoning	Height of	0.8
						Soft white sugar	7g	396	Seasoning	In	0.8
Corn starch	1.5	346	Seasoning	Is low in	1

TABLE 1b

Reference food material	Non-reference food material	Minimum/maximum value	Coefficient of dose compensation
				Egg liquid	Peanut oil	5/max	+1
Water purification	Refined salt	0/max	+1

TABLE 1c

Food material	Weight (D)	Coefficient of heat/(100 g)	Categories	Priority level	Residual amount of
						Egg liquid	100g	139	Staple food	Height of	1
Tomato fruit	230g	15	Auxiliary materials	Height of	0.9
						Chopped green onion	6g	27	Small material	In	1
Peanut oil	21g	899	Seasoning	In	0.5
						Water purification	26g	0	Seasoning	In	0.3
Refined salt	3.2g	0	Seasoning	Height of	0.8
						Soft white sugar	7g	396	Seasoning	In	0.8
Corn starch	1.5	346	Seasoning	Is low in	1

2: the target adjustment dimension is a taste dimension

Table 1d is partial information of another usage dependency relationship table provided in this embodiment, including information of food materials, mouth feel, usage compensation coefficients, usage compensation thresholds, and the like; the consumption compensation coefficient reflects the corresponding relation between the consumption variation of the food material and the taste. In this embodiment, in addition to adjusting the total heat of the basic electronic recipe, the user may also adjust the taste of the recipe, and in the case of the basic electronic recipe, if the user wants to adjust the salinity or sweetness of eggs fried with tomatoes, the user may set the consumption of the food material corresponding to the target salinity or the target sweetness. Further, the cooking machine may determine the target consumption of the food material corresponding to the target taste according to the consumption of the food material set by the user and the consumption compensation coefficient corresponding to the target taste in table 1 d. Optionally, the target consumption of the food material corresponding to the target taste may be determined by the basic consumption x quantity compensation factor. For example, if the user wants to eat salty dishes, the target taste can be set to be salty, and if the dosage compensation coefficient corresponding to salty taste is 1.2, and the base dosage of refined salt is 3.2g according to table 1a, the corresponding target dosage is 3.2 × 1.2 — 3.84 g; if the user wants to eat some sweet dishes, the target taste can be set to be slightly sweet, if the dosage compensation coefficient corresponding to the slightly salty taste is 1.2, and the basic dosage of soft sugar is 7g according to the table 1a, the corresponding target dosage is 7 x 1.2-8.4 g. Further optionally, under the condition that the user has adjusted the taste, if the total heat of the electronic menu exceeds the target total heat set by the user, the usage amount of each food material can be further adjusted from the heat dimension, so as to meet the requirement of the user on heat.

TABLE 1d

3: target adjustment dimension is a usage dimension

In this embodiment, a user may set a target consumption of a certain food material and specify that the basic electronic menu is adjusted according to the target consumption of the food material. When the basic electronic recipe is specified to be adjusted according to the target consumption of a certain food material, the food material having the consumption compensation relation with the specified food material can be determined according to the table 1b to serve as the target food material, and the target consumption of the target food material is determined according to the basic consumption and the target consumption of the specified food material and the consumption compensation coefficient of the target food material and the specified food material. For example, if the user specifies to increase the amount of purified water, and the food material having the amount compensation relation with the purified water is refined salt according to table 1b, the amount of refined salt needs to be adjusted so as not to affect the taste of the dish. For the process of adjusting the amount of the refined salt according to the target amount of the purified water, reference may be made to the example description of adjusting the amount of the peanut oil according to the target amount of the egg liquid in terms of heat dimension, and repeated description is omitted here.

It should be noted that, in this embodiment, tables 1a and 1c are only part of the contents in the electronic recipe, and besides, the electronic recipe may further include information such as operation steps required by the cooker to execute a cooking task, ingredients corresponding to the operation steps, and execution power and duration required to execute each operation step. Further, under the condition that the target electronic menu is obtained, the cooking machine can execute the operation steps according to the target electronic menu, and under the condition that the first food material is needed in the current operation execution step, the cooking machine can determine whether the usage amount of each food material in the target electronic menu needs to be continuously adjusted according to the target usage amount and the actual usage amount of the first food material. If the actual consumption of the first food material is consistent with the target consumption, continuing to execute the subsequent operation steps according to the target electronic menu; if not, determining a second food material and a dosage compensation coefficient which have a dosage compensation relation with the first food material according to the table 1b, and determining the actual dosage of the second food material by combining the target dosage and the actual dosage of the first food material. And further, weighing the second food material according to the determined actual consumption, and continuously executing the cooking task according to the weighed second food material until the cooking task is completed.

In the embodiment of the application, under the condition that the data object in the basic structured data does not meet the actual requirement of the user, the data object usage in the basic structured data can be adjusted from the target adjustment dimension specified by the user according to the actual requirement of the user, so that the adjusted target structured data meets the requirement of the user on the target adjustment dimension; in addition, in the process that the kitchen robot executes the operation task according to the target structured data, the usage of each data object can be continuously adjusted under the condition that the actual usage of the data object is not matched with the target usage, the whole adjusting process is more flexible, and the user experience is favorably improved.

Based on the above, an embodiment of the present application further provides a kitchen robot, fig. 3a is a schematic structural diagram of the kitchen robot 10 provided in the embodiment of the present application, and as shown in fig. 3a, the kitchen robot 10 includes: the pot comprises a pot body 11 and a heating base 12, wherein a processor 13 and a memory 14 storing a computer program are arranged on the heating base 12; wherein, the pan body 11 is used for accommodating data objects; the heating base 12 is used for heating the pot body 11 in the process that the kitchen robot 10 executes the operation task; in this embodiment, the processor 13 and the memory 14 may be one or more.

The memory 14 is mainly used for storing computer programs, which can be executed by the processor 13, so that the processor 13 controls the kitchen robot 10 to realize corresponding functions and complete corresponding actions or tasks. In addition to storing computer programs, the memory 14 may also be configured to store other various data to support operations on the kitchen robot 10. Examples of such data include instructions for any application or method operating on the kitchen robot 10.

In the embodiment of the present application, the implementation form of the processor 13 is not limited, and may be, for example, but not limited to, a CPU, a GPU, an MCU, or the like. The processor 13 may be seen as a control system of the kitchen robot 10, operable to execute a computer program stored in the memory 14 to control the kitchen robot 10 to perform a corresponding function, to perform a corresponding action or task. It should be noted that, depending on the implementation form and the scene of the kitchen robot 10, the functions, actions or tasks to be implemented may be different; accordingly, the computer programs stored in the memory 14 may be different, and the processor 13 executing different computer programs may control the kitchen robot 10 to perform different functions, perform different actions or tasks.

In some optional embodiments, the kitchen robot 10 may further include a display screen for displaying or for user selection of the structured data; the device comprises an audio component used for outputting prompt information to a user and a communication component used for establishing communication connection with other equipment. In the present embodiment, these components are only part of the components shown schematically, and it is not meant that the kitchen robot 10 includes only these components, and the kitchen robot 10 may further include other components according to different application requirements, depending on the product form of the kitchen robot 10.

In the embodiment of the present application, when the processor 13 executes the computer program in the memory 14, it is configured to: acquiring basic structured data, wherein the basic structured data at least comprises basic usage and usage dependency relationship of data objects required by the kitchen robot 10 to execute the operation task; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension and by combining the usage dependence of the data objects to obtain target structured data; the kitchen robot 10 is controlled to perform the job task according to the target structured data, which includes the target usage of each data object.

In an alternative embodiment, the processor 13, when obtaining the reference data provided by the user in the target adjustment dimension, is configured to: displaying a human-computer interaction interface, wherein the human-computer interaction interface comprises parameter setting items; and responding to the setting operation of the user on the parameter setting item, and acquiring the reference data on the target adjustment dimension set by the user.

In an optional embodiment, the parameter setting items include a dimension selection item and a value setting item, and the processor 13, when acquiring the reference data in the target adjustment dimension set by the user in response to the setting operation of the parameter setting item by the user, is configured to: responding to the selection operation of the user on the dimension selection item, and acquiring a target adjustment dimension selected by the user from all adjustment dimensions; and responding to the setting operation of the user on the numerical value setting item, and acquiring the reference data on the target adjustment dimension set by the user.

In an alternative embodiment, the usage dependencies include: a data object having a usage compensation relationship in at least one adjustment dimension and a corresponding usage compensation coefficient; the processor 13, when adjusting the usage of at least part of the data objects in combination with the usage dependency according to the reference data to obtain the target structured data, is configured to: determining a target data object with a usage compensation relation on a target adjustment dimension and a corresponding target usage compensation coefficient from the usage dependency relation; and adjusting the usage of the target data object according to the reference data and the target usage compensation coefficient to obtain the target structured data.

In an optional embodiment, if the data object is a food material, the target adjustment dimension is a heat dimension, and the reference data is a target total heat; or, the target adjustment dimension is a usage dimension, and the reference data is a target usage of the specified data object; or the target adjustment dimension is a mouthfeel dimension, and the reference data is a target mouthfeel.

In an optional embodiment, in the case that the target adjustment dimension is a thermal dimension, when determining, from the usage dependency, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation coefficient, the processor 13 is configured to: and determining the data objects with the usage compensation relationship in each data object and the corresponding usage compensation coefficients thereof as target data objects and target usage compensation coefficients respectively from the usage dependency relationship.

In an alternative embodiment, the processor 13, when adjusting the dose of the target data object according to the reference data and the target dose compensation coefficient to obtain the target structured data, is configured to: calculating a first quantity adjustment coefficient according to the target total heat quantity and the basic quantity of each data object; and adjusting the usage of the target data object according to the first usage adjustment coefficient and the target usage compensation coefficient to obtain the target structured data.

In an alternative embodiment, the infrastructure data further comprises: thermal coefficients for each data object; the processor 13, when calculating the first quantity adjustment factor based on the target total heat quantity and the base quantity of each data object, is configured to: calculating the basic total heat according to the basic usage and the heat coefficient of each data object; and calculating a first quantity adjustment coefficient according to the target total heat quantity and the basic total heat quantity.

In an alternative embodiment, the infrastructure data further comprises: a category attribute and/or a priority attribute of each data object; the processor 13, when adjusting the usage of the target data object according to the first usage adjustment coefficient and the target usage compensation coefficient to obtain the target structured data, is configured to: determining a reference data object and a non-reference data object in the target data object according to the category attribute and/or the priority attribute of the target data object; determining a target usage amount of the reference data object according to the first amount adjustment coefficient and the basic usage amount of the reference data object; and determining the target consumption of the non-reference data object according to the target consumption of the reference data object, the target consumption compensation coefficient and the basic consumption of the non-reference data object.

In an optional embodiment, in a case that the target adjustment dimension is a usage dimension, when determining, from the usage dependency relationship, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation coefficient, the processor 13 is configured to: and determining a data object having a usage compensation relation with the specified data object as a target data object from the usage dependency relation, and taking a usage compensation coefficient between the specified data object and the target data object as a target usage compensation coefficient.

In an alternative embodiment, the processor 13, when adjusting the dose of the target data object according to the reference data and the target dose compensation coefficient to obtain the target structured data, is configured to: calculating a second use amount adjustment coefficient according to the basic use amount and the target use amount of the specified data object; and determining the target usage of the target data object according to the second usage adjusting coefficient and the target usage compensation coefficient.

In an optional embodiment, in a case that the target adjustment dimension is a mouth feel dimension, when determining, from the usage dependency relationship, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation coefficient, the processor 13 is configured to: and determining a data object having a dosage compensation relation with the target mouthfeel as a target data object from the dosage dependence relation, and taking a dosage compensation coefficient between the target mouthfeel and the target data object as a target dosage compensation coefficient.

In an alternative embodiment, the processor 13, when adjusting the dose of the target data object according to the reference data and the target dose compensation coefficient to obtain the target structured data, is configured to: and determining the target consumption of the target data object under the target taste according to the target consumption compensation coefficient and the basic consumption of the target data object.

In an alternative embodiment, the target structured data further comprises: the corresponding relation between the operation step and the data object; the processor 13, when controlling the kitchen robot 10 to perform the job task according to the target structured data, is configured to: controlling the kitchen robot 10 to perform the work steps in sequence to complete the work task; and weighing the first data object according to the target usage of the first data object when the currently executed work step corresponds to the first data object, so that the kitchen robot 10 can execute the currently executed work step according to the first data object.

In an alternative embodiment, the processor 13 is further configured to: in the process of weighing the first data object, if the actual usage of the first data object is not matched with the target usage of the first data object, determining a second data object having a usage compensation relation with the first data object and a corresponding first usage compensation coefficient according to the usage dependency relation; and calculating the actual consumption of the second data object according to the actual consumption of the first data object and the first quantity compensation coefficient, so as to weigh the second data object according to the actual consumption of the second data object in the subsequent weighing process.

In an alternative embodiment, the processor 13, when weighing the first data object according to its target usage, is configured to: sending the target usage amount of the first data object to the weighing device, so that the weighing device can weigh the first data object according to the target usage amount of the first data object; and receiving the first data object weighed by the weighing device.

In an alternative embodiment, the processor 13, when obtaining the underlying structured data, is configured to: receiving basic structured data sent by terminal equipment; or responding to configuration operation on a display screen, and acquiring basic structured data configured by a user; or in response to the received job instruction, obtaining infrastructure data adapted to the job instruction from a server.

In an alternative embodiment, the weighing device may be implemented independently as a separate device, but is not limited thereto. In another alternative embodiment, the weighing device may be implemented as part of the kitchen robot 10, which may be integrated on the kitchen robot 10, or may be implemented separately. When implemented integrally with kitchen robot 10, a weighing device may be provided on the base for weighing the data objects according to their target usage to provide a corresponding amount of data objects to pot 11.

Accordingly, the present application also provides a computer readable storage medium storing a computer program, which when executed can implement the steps that can be performed by the kitchen robot in the above method embodiments.

An embodiment of the present application further provides a weighing apparatus, fig. 3b is a schematic structural diagram of the weighing apparatus 20 provided in the embodiment of the present application, and as shown in fig. 3b, the weighing apparatus 20 includes: a weighing unit 21, a processor 22, and a memory 23 in which a computer program is stored; the weighing component 21 is used for weighing the data objects according to the target usage of each data object; in this embodiment, the processor 22 and the memory 23 may be one or more.

The memory 23 is mainly used for storing computer programs, which can be executed by the processor 22, so that the processor 22 controls the weighing device 20 to realize corresponding functions and complete corresponding actions or tasks. In addition to storing computer programs, the memory 23 may also be configured to store other various data to support operations on the weighing apparatus 20. Examples of such data include instructions for any application or method operating on the weighing device 20.

In the embodiment of the present application, the implementation form of the processor 22 is not limited, and may be, for example, but not limited to, a CPU, a GPU, an MCU, or the like. The processor 22 may be considered a control system for the weighing apparatus 20 and may be configured to execute a computer program stored in the memory 23 to control the weighing apparatus 20 to perform a corresponding function, perform a corresponding action, or task. It should be noted that, depending on the implementation form and the scene in which the weighing device 20 is located, the functions, actions or tasks required to be implemented may be different; accordingly, the computer programs stored in the memory 23 may vary, and execution of different computer programs by the processor 22 may control the weighing apparatus 20 to perform different functions, perform different actions or tasks.

In some alternative embodiments, the weighing apparatus 20 may also include a display screen for displaying or providing user selection of the structured data; the device comprises an audio component used for outputting prompt information to a user and a communication component used for establishing communication connection with other equipment. In the present embodiment, these components are only a part of the components shown schematically, and it is not meant that the weighing device 20 includes only these components, and the weighing device 20 may include other components according to different application requirements, depending on the product form of the weighing device 20.

In the embodiment of the present application, when the processor 22 executes the computer program in the memory 23, it is configured to: acquiring basic structured data, wherein the basic structured data at least comprises basic usage and usage dependency relationship of data objects required by the kitchen robot to execute a job task; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension and by combining the usage dependence of the data objects to obtain target structured data; and controlling the kitchen robot to execute the work task according to the target structured data, wherein the target structured data comprises the target usage of each data object.

In an alternative embodiment, the processor 22, when obtaining the reference data provided by the user in the target adjustment dimension, is configured to: displaying a human-computer interaction interface, wherein the human-computer interaction interface comprises parameter setting items; and responding to the setting operation of the user on the parameter setting item, and acquiring the reference data on the target adjustment dimension set by the user.

In an alternative embodiment, the parameter setting items include a dimension selection item and a value setting item, and the processor 22, when acquiring the reference data in the target adjustment dimension set by the user in response to the setting operation of the parameter setting item by the user, is configured to: responding to the selection operation of the user on the dimension selection item, and acquiring a target adjustment dimension selected by the user from all adjustment dimensions; and responding to the setting operation of the user on the numerical value setting item, and acquiring the reference data on the target adjustment dimension set by the user.

In an alternative embodiment, the usage dependencies include: a data object having a usage compensation relationship in at least one adjustment dimension and a corresponding usage compensation coefficient; the processor 22, when adjusting the usage of at least part of the data objects in combination with the usage dependency based on the reference data to obtain the target structured data, is configured to: determining a target data object with a usage compensation relation on a target adjustment dimension and a corresponding target usage compensation coefficient from the usage dependency relation; and adjusting the usage of the target data object according to the reference data and the target usage compensation coefficient to obtain the target structured data.

In an optional embodiment, if the data object is a food material, the target adjustment dimension is a heat dimension, and the reference data is a target total heat; or, the target adjustment dimension is a usage dimension, and the reference data is a target usage of the specified data object; or the target adjustment dimension is a mouthfeel dimension, and the reference data is a target mouthfeel.

In an alternative embodiment, in the case that the target adjustment dimension is a thermal dimension, the processor 22, when determining from the usage dependency, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation coefficient, is configured to: and determining the data objects with the usage compensation relationship in each data object and the corresponding usage compensation coefficients thereof as target data objects and target usage compensation coefficients respectively from the usage dependency relationship.

In an alternative embodiment, the processor 22, when adjusting the dose of the target data object according to the reference data and the target dose compensation factor to obtain the target structured data, is configured to: calculating a first quantity adjustment coefficient according to the target total heat quantity and the basic quantity of each data object; and adjusting the usage of the target data object according to the first usage adjustment coefficient and the target usage compensation coefficient to obtain the target structured data.

In an alternative embodiment, the infrastructure data further comprises: thermal coefficients for each data object; the processor 22, when calculating the first quantity adjustment factor based on the target total heat quantity and the base quantity for each data object, is configured to: calculating the basic total heat according to the basic usage and the heat coefficient of each data object; and calculating a first quantity adjustment coefficient according to the target total heat quantity and the basic total heat quantity.

In an alternative embodiment, the infrastructure data further comprises: a category attribute and/or a priority attribute of each data object; the processor 22, when adjusting the usage of the target data object according to the first usage adjustment coefficient and the target usage compensation coefficient to obtain the target structured data, is configured to: determining a reference data object and a non-reference data object in the target data object according to the category attribute and/or the priority attribute of the target data object; determining a target usage amount of the reference data object according to the first amount adjustment coefficient and the basic usage amount of the reference data object; and determining the target consumption of the non-reference data object according to the target consumption of the reference data object, the target consumption compensation coefficient and the basic consumption of the non-reference data object.

In an alternative embodiment, in the case that the target adjustment dimension is a usage dimension, when determining, from the usage dependency, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation coefficient, the processor 22 is configured to: and determining a data object having a usage compensation relation with the specified data object as a target data object from the usage dependency relation, and taking a usage compensation coefficient between the specified data object and the target data object as a target usage compensation coefficient.

In an alternative embodiment, the processor 22, when adjusting the dose of the target data object according to the reference data and the target dose compensation factor to obtain the target structured data, is configured to: calculating a second use amount adjustment coefficient according to the basic use amount and the target use amount of the specified data object; and determining the target usage of the target data object according to the second usage adjusting coefficient and the target usage compensation coefficient.

In an optional embodiment, in a case that the target adjustment dimension is a mouth feel dimension, when determining, from the usage dependency relationship, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation coefficient, the processor 22 is configured to: and determining a data object having a dosage compensation relation with the target mouthfeel as a target data object from the dosage dependence relation, and taking a dosage compensation coefficient between the target mouthfeel and the target data object as a target dosage compensation coefficient.

In an alternative embodiment, the processor 22, when adjusting the dose of the target data object according to the reference data and the target dose compensation factor to obtain the target structured data, is configured to: and determining the target consumption of the target data object under the target taste according to the target consumption compensation coefficient and the basic consumption of the target data object.

In an alternative embodiment, the target structured data further comprises: the corresponding relation between the operation step and the data object; the processor 22, when controlling the kitchen robot to perform the job task in dependence of the target structured data, is configured to: controlling the kitchen robot to execute the operation steps in sequence to complete the operation task; and weighing the first data object according to the target usage of the first data object under the condition that the currently executed operation step corresponds to the first data object, so that the kitchen robot can execute the currently executed operation step according to the first data object.

In an alternative embodiment, processor 22 is further configured to: in the process of weighing the first data object, if the actual usage of the first data object is not matched with the target usage of the first data object, determining a second data object having a usage compensation relation with the first data object and a corresponding first usage compensation coefficient according to the usage dependency relation; and calculating the actual consumption of the second data object according to the actual consumption of the first data object and the first quantity compensation coefficient, so as to weigh the second data object according to the actual consumption of the second data object in the subsequent weighing process.

In an alternative embodiment, processor 22 is further configured to: after the first data object has been weighed, the first data object is provided to the kitchen robot for the kitchen robot to carry out the currently executed work step on the basis of the first data object.

In an alternative embodiment, processor 22, in acquiring the underlying structured data, is configured to: and receiving the basic structured data sent by the kitchen robot so as to provide the kitchen robot with a data object of the consumption required when the kitchen robot executes the task.

In an alternative embodiment, processor 22, in acquiring the underlying structured data, is configured to: receiving basic structured data sent by terminal equipment; or responding to configuration operation on a display screen, and acquiring basic structured data configured by a user; or in response to the received job instruction, obtaining infrastructure data adapted to the job instruction from a server.

Accordingly, embodiments of the present application also provide a computer-readable storage medium storing a computer program, where the computer program can implement the steps that can be performed by the weighing device in the above method embodiments when executed.

The communication component in the above embodiments is configured to facilitate communication between the device in which the communication component is located and other devices in a wired or wireless manner. The device where the communication component is located can access a wireless network based on a communication standard, such as a WiFi, a 2G, 3G, 4G/LTE, 5G and other mobile communication networks, or a combination thereof. In an exemplary embodiment, the communication component receives a broadcast signal or broadcast related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component further includes a Near Field Communication (NFC) module to facilitate short-range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, Ultra Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

The display in the above embodiments includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.

The power supply assembly of the above embodiments provides power to various components of the device in which the power supply assembly is located. The power components may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the device in which the power component is located.

The audio component in the above embodiments may be configured to output and/or input an audio signal. For example, the audio component includes a Microphone (MIC) configured to receive an external audio signal when the device in which the audio component is located is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal may further be stored in a memory or transmitted via a communication component. In some embodiments, the audio assembly further comprises a speaker for outputting audio signals.

As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (16)

1. A job task execution method, comprising:

acquiring basic structured data, wherein the basic structured data at least comprise a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object;

acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user on the target adjustment dimension;

according to the reference data, the usage of at least part of the data objects is adjusted by combining the usage dependency relationship to obtain target structured data;

and controlling the kitchen robot to execute the work task according to the target structured data, wherein the target structured data at least comprises target usage of each data object.

2. The method of claim 1, wherein obtaining reference data provided by a user in a target adjustment dimension comprises:

displaying a human-computer interaction interface, wherein the human-computer interaction interface comprises parameter setting items;

and responding to the setting operation of the user on the parameter setting item, and acquiring the reference data on the target adjustment dimension set by the user.

3. The method of claim 1, wherein the usage dependency comprises: a data object having a usage compensation relationship in at least one adjustment dimension and a corresponding usage compensation coefficient;

adjusting the usage of at least part of the data objects according to the reference data and in combination with the usage dependency relationship to obtain target structured data, including:

determining a target data object with a usage compensation relation on the target adjustment dimension and a corresponding target usage compensation coefficient from the usage dependency relation;

and adjusting the usage of the target data object according to the reference data and the target usage compensation coefficient to obtain the target structured data.

4. The method of claim 3, wherein if the data object is a food material, the target adjustment dimension is a heat dimension, and the reference data is a target total heat;

or, the target adjustment dimension is a usage dimension, and the reference data is a target usage of the specified data object;

or the target adjustment dimension is a mouthfeel dimension, and the reference data is a target mouthfeel.

5. The method of claim 4, wherein determining, from the usage dependencies, a target data object for which a usage compensation relationship exists in the target adjustment dimension and corresponding target usage compensation coefficients, if the target adjustment dimension is a thermal dimension, comprises:

and determining the data objects with the usage compensation relationship in each data object and the corresponding usage compensation coefficients thereof from the usage dependency relationship as target data objects and target usage compensation coefficients respectively.

6. The method of claim 5, wherein adjusting the usage of the target data object based on the reference data and the target usage compensation factor to obtain the target structured data comprises:

calculating a first quantity adjustment coefficient according to the target total heat quantity and the basic quantity of each data object;

and adjusting the usage of the target data object according to the first usage adjustment coefficient and the target usage compensation coefficient to obtain the target structured data.

7. The method of claim 6, wherein the infrastructure data further comprises: thermal coefficients for each data object;

calculating a first quantity adjustment coefficient according to the target total heat quantity and the basic quantity of each data object, wherein the first quantity adjustment coefficient comprises the following steps:

calculating the basic total heat according to the basic usage and the heat coefficient of each data object;

and calculating a first quantity adjustment coefficient according to the target total heat quantity and the basic total heat quantity.

8. The method of claim 6, wherein the infrastructure data further comprises: a category attribute and/or a priority attribute of each data object;

adjusting the usage of the target data object according to the first usage adjustment coefficient and the target usage compensation coefficient to obtain the target structured data, including:

determining a reference data object and a non-reference data object in the target data object according to the category attribute and/or the priority attribute of the target data object;

determining a target usage amount of the reference data object according to the first amount adjustment coefficient and a basic usage amount of the reference data object;

and determining the target usage of the non-reference data object according to the target usage of the reference data object, the target usage compensation coefficient and the basic usage of the non-reference data object.

9. The method of claim 4, wherein determining, from the usage dependency, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation factor if the target adjustment dimension is a usage dimension comprises:

and determining a data object having a usage compensation relationship with the specified data object from the usage dependency relationship as a target data object, and using a usage compensation coefficient between the specified data object and the target data object as a target usage compensation coefficient.

10. The method of claim 4, wherein determining, from the usage dependency, a target data object having a usage compensation relationship in the target adjustment dimension and a corresponding target usage compensation factor if the target adjustment dimension is a mouth feel dimension comprises:

and determining a data object having a dosage compensation relation with the target mouthfeel as a target data object from the dosage dependency relation, and taking a dosage compensation coefficient between the target mouthfeel and the target data object as a target dosage compensation coefficient.

11. The method of any one of claims 1-10, wherein the target structured data further comprises: the corresponding relation between the operation step and the data object;

controlling the kitchen robot to execute the work task according to the target structured data, comprising:

controlling the kitchen robot to sequentially execute the work steps to complete the work task; and

and under the condition that the currently executed operation step corresponds to a first data object, weighing the first data object according to the target usage of the first data object, so that the kitchen robot can execute the currently executed operation step according to the first data object.

12. The method of claim 11, further comprising:

in the process of weighing the first data object, if the actual usage of the first data object is not matched with the target usage of the first data object, determining a second data object having a usage compensation relation with the first data object and a corresponding first usage compensation coefficient according to the usage dependency relation;

and calculating the actual using amount of the second data object according to the actual using amount of the first data object and the first amount compensation coefficient so as to weigh the second data object according to the actual using amount of the second data object in the subsequent weighing process.

13. A kitchen robot, characterized in that the kitchen robot further comprises: the pot comprises a pot body, a heating base and a base for bearing the heating base; the heating base is used for heating the pot body in the process that the kitchen robot executes an operation task; the base is also provided with a weighing device;

the kitchen robot is used for acquiring basic structural data, wherein the basic structural data at least comprises a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension in combination with the usage dependency relationship to obtain target structured data, wherein the target structured data at least comprises target usage of each data object; controlling the weighing equipment to weigh each data object according to the target usage amount of each data object, and executing the operation task aiming at each data object weighed by the weighing equipment;

and the weighing device is used for weighing each data object according to the target consumption of each data object under the control of the kitchen robot so as to provide the corresponding consumption of the data objects for the kitchen robot.

14. A weighing apparatus, comprising: a weighing component, a processor and a memory storing a computer program;

the processor to execute the computer program to:

acquiring basic structured data, wherein the basic structured data at least comprise a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object;

acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user;

adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension and by combining the usage dependency relationship to obtain target structured data;

controlling the kitchen robot to execute the operation task according to the target structured data, wherein the target structured data at least comprises target usage of each data object;

and the weighing component is used for weighing the data objects according to the target usage of each data object so as to provide the corresponding usage data objects for the kitchen robot.

15. A kitchen robotic work system, comprising: the kitchen robot and the weighing equipment are in communication connection with the kitchen robot;

the kitchen robot is used for acquiring basic structural data, wherein the basic structural data at least comprises a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; acquiring reference data provided by a user on a target adjustment dimension, wherein the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension in combination with the usage dependency relationship to obtain target structured data, wherein the target structured data at least comprises target usage of each data object; controlling the weighing equipment to weigh each data object according to the target usage amount of each data object, and executing the operation task aiming at each data object weighed by the weighing equipment;

and the weighing device is used for weighing each data object according to the target consumption of each data object under the control of the kitchen robot so as to provide the corresponding consumption of the data objects for the kitchen robot.

16. A kitchen robotic work system, comprising: the kitchen robot and the weighing equipment are in communication connection with the kitchen robot;

the kitchen robot is used for acquiring basic structural data, wherein the basic structural data at least comprises a usage dependency relationship required by the kitchen robot to execute a job task and basic usage of each data object; sending the infrastructure data to the weighing device; and executing the job task for each data object weighed by the weighing device;

the weighing device is used for acquiring reference data provided by a user on a target adjustment dimension, and the reference data reflects a task execution effect expected by the user; adjusting the usage of at least part of the data objects according to the reference data on the target adjustment dimension in combination with the usage dependency relationship to obtain target structured data, wherein the target structured data at least comprises target usage of each data object; and weighing each data object according to the target consumption of each data object so as to provide the corresponding consumption data object for the kitchen robot.

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