A catering service processing method, device and equipment

Abstract

The embodiment of the specification discloses a catering service processing method, device and equipment. Including: receiving the catering order sent by the user through the first server, and obtaining the corresponding catering recipe; send the catering recipe to the second server, determine the object instruction set according to the catering recipe through the second server, the instruction set includes the first object instruction of the robot for the movable and the retrievable article, and the second object instruction of the intelligent cooking machine in the specified cooking area; send the first object instruction to the robot through the second server, instruct the robot to take the corresponding food materials from the specified food material area, and move from the food material area to the cooking area, execute the cooking feeding processing to the cooking container according to the cooking process corresponding to the catering recipe; send the second object instruction to the intelligent cooking machine through the second server, instruct the intelligent cooking machine to execute the cooking processing to the cooking container according to the cooking process.

Description

Technical Field

[0001] This specification relates to the field of robotics, and in particular to a method, apparatus, and equipment for processing catering services. Background Technology

[0002] With the explosive emergence and growth of various applications, more offline businesses have shifted online, reducing costs and bringing more convenience to users.

[0003] For the catering industry, although online food delivery apps offer delivery services, food preparation still needs to be done in physical stores and relies heavily on manual labor. Beverage preparation is relatively lightweight, with low barriers to entry and easy to learn, and manual preparation is still quite efficient. However, hot dish preparation, such as stir-frying and deep-frying, has a higher barrier to entry and is less efficient by hand. Therefore, some restaurants use intelligent cooking equipment, such as smart cooking machines, to assist manual labor in cooking more efficiently.

[0004] However, the actual capabilities of smart cooking devices are relatively limited. They can usually only complete some cooking tasks such as stir-frying and steaming, and still require a lot of manual intervention.

[0005] Therefore, the catering industry needs more efficient business support solutions. Summary of the Invention

[0006] This specification provides one or more embodiments of a catering business processing method, apparatus, and equipment to solve the following technical problem: the catering industry needs more efficient business support solutions.

[0007] To solve the above-mentioned technical problems, one or more embodiments of this specification are implemented as follows:

[0008] This specification provides a catering business processing method according to one or more embodiments, including:

[0009] The system receives restaurant orders from users through a first server and retrieves the corresponding restaurant recipes.

[0010] The catering recipe is sent to a second server, which determines a set of object instructions based on the catering recipe. The set of instructions includes a first object instruction for a robot that can move and pick up objects, and a second object instruction for an intelligent cooking machine located in a designated cooking area.

[0011] The second server sends the first object instruction to the robot, instructing the robot to take the corresponding ingredient from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe;

[0012] The second server sends the second object instruction to the smart cooking machine, instructing the smart cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding food products for delivery to the user.

[0013] This specification provides one or more embodiments of a catering business processing device, comprising:

[0014] The restaurant recipe acquisition module receives restaurant orders sent by users through a first server and retrieves the corresponding restaurant recipes.

[0015] The object instruction determination module sends the catering recipe to the second server, and the second server determines the object instruction set based on the catering recipe. The instruction set includes a first object instruction for a robot that can move and pick up items, and a second object instruction for an intelligent cooking machine located in a designated cooking area.

[0016] The robot processing module sends the first object instruction to the robot through the second server, instructing the robot to take the corresponding ingredients from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe;

[0017] The intelligent cooking machine processing module sends the second object instruction to the intelligent cooking machine through the second server, instructing the intelligent cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding catering products for delivery to the user.

[0018] This specification provides one or more embodiments of a catering business processing device, comprising:

[0019] At least one processor; and,

[0020] A memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform:

[0022] The system receives restaurant orders from users through a first server and retrieves the corresponding restaurant recipes.

[0023] The catering recipe is sent to a second server, which determines a set of object instructions based on the catering recipe. The set of instructions includes a first object instruction for a robot that can move and pick up objects, and a second object instruction for an intelligent cooking machine located in a designated cooking area.

[0024] The second server sends the first object instruction to the robot, instructing the robot to take the corresponding ingredient from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe;

[0025] The second server sends the second object instruction to the smart cooking machine, instructing the smart cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding food products for delivery to the user.

[0026] The above-mentioned at least one technical solution adopted in one or more embodiments of this specification can achieve the following beneficial effects: it can provide catering services to users more conveniently and efficiently. Based on the first server, it supports users to place catering orders and can prepare catering recipes accordingly for a specially deployed second server. Based on the global scheduling of the second server, it determines (which can be directly generated by it) and issues targeted object instructions, instructing the robot and the intelligent cooking machine to work together in a complementary and cooperative manner. Based on the user's catering order, the second server automatically generates and matches control and coordination instructions for both, so that the robot cooperates with the cooking process and focuses on performing tasks that the intelligent cooking machine is unable to perform, such as moving, picking up and putting in ingredients, and strengthening cooking actions. It also enables the intelligent cooking machine to perform cooking and preparation processes with the assistance of the robot according to the cooking process, which more fully liberates human labor, creates more flexible and changeable cooking and preparation capabilities, helps to implement the solution at a lower cost, and effectively improves the efficiency of catering services. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the drawings used in the description of the embodiments or prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 A flowchart illustrating a catering business processing method provided for one or more embodiments of this specification;

[0029] Figure 2 Provided for one or more embodiments of this specification Figure 1 A schematic diagram illustrating the principle of a specific implementation scheme of the method;

[0030] Figure 3 A flowchart illustrating a robot assistance scheme provided for one or more embodiments of this specification;

[0031] Figure 4 A schematic diagram illustrating a robot-based cooking adjustment scheme provided for one or more embodiments of this specification;

[0032] Figure 5 A schematic diagram of the structure of a catering business processing device provided for one or more embodiments of this specification;

[0033] Figure 6 This is a structural schematic diagram of a catering business processing device provided for one or more embodiments of this specification. Detailed Implementation

[0034] This specification provides a method, apparatus, equipment, and storage medium for processing catering business.

[0035] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this application.

[0036] Based on the above overall approach, the solution proposed in this application will be further explained below.

[0037] Figure 1 This document illustrates a flowchart of a catering business processing method provided in one or more embodiments of this specification. This method can be applied to the catering business processing system constructed in this application. The system includes at least a robot, an intelligent cooking machine, and multiple control devices. The control devices include at least a first server and a second server, which can be provided by the same platform or by different platforms. In addition, control devices can also be located locally at the merchant's location. This application primarily focuses on the first and second servers, especially the second server, regarding the control devices. It should be emphasized that the first server, the second server, and the remaining control devices can be implemented using physical servers located locally at the merchant's location, or they can be implemented based on cloud servers provided by one or more platforms.

[0038] The first server is, for example, the ordering server of a food ordering platform. In addition to supporting users to place food orders, the ordering server can also obtain food recipes from its local or external devices to support subsequent instruction processing.

[0039] It is important to emphasize that this application specifically includes a second server for processing restaurant recipes into instructions, which are then used to direct the machines to complete the cooking process. The restaurant recipes can also be obtained by the second server itself. In this case, the modifications to the first server will be minimal, and the first server will primarily only need to confirm the restaurant orders placed by users for the second server, without needing to concern itself with the restaurant recipes.

[0040] As mentioned earlier, the second server and the first server can be provided by different platforms. In this case, the second server may be provided by a professional robot operation platform, which can then serve different ordering platforms simultaneously.

[0041] A robot is a mobile device capable of carrying objects, and its form may be humanoid. An intelligent cooking machine is an intelligent machine with a certain degree of automated cooking capabilities, such as a stir-fry machine or a food processor. It should be noted that the intelligent cooking machine in this application may have undergone additional software modifications to facilitate interaction with the robot.

[0042] The control equipment can be used to issue commands to instruct robots and smart cooking machines to work, and it can also be used to interact with users. Therefore, the main executor of this process can include the control equipment, especially the secondary server. This process also demonstrates the minimum tasks that the robots and smart cooking machines need to perform under instruction.

[0043] It should be noted that robots and smart cooking machines can also make a certain degree of autonomous decision-making based on their intelligence, thereby doing more work on their own, without necessarily needing to be specifically instructed by the controlled equipment to perform these tasks.

[0044] Figure 1 The process includes the following steps:

[0045] S102: Receive the catering order sent by the user through the first server and obtain the corresponding catering recipe.

[0046] In restaurant settings, users can place orders via a mobile app or by ordering directly from staff at the restaurant. At home, users can place orders via a mobile app or by ordering from a robot or other control device in their home.

[0047] As the primary server for order processing, upon receiving a food order, it retrieves the corresponding recipe from the food recipe database, or provides the order to another device (e.g., a data query device) to retrieve the recipe. To improve efficiency, the food recipe database can be stored on the primary server. To enhance accuracy, food merchants can upload and maintain their own food recipes through the primary server.

[0048] A food order specifies the food item to be cooked, while the corresponding recipe specifies the ingredients, seasonings, and other raw materials needed to cook that item. It also outlines the cooking process. For example, when to add which seasonings and ingredients, how to add them in stages, the heat level and cooking time, whether to reduce the heat at a certain point, and when to remove from the heat. The cooking process consists of multiple sequential, staged cooking actions.

[0049] For restaurant recipes, you can directly use those that are described in natural language and are understood through common sense (such as recipes on the internet or in books).

[0050] Of course, in order to improve the efficiency of subsequent instruction processing, the catering recipes understood in common sense can also be preprocessed in advance, such as data cleaning (e.g., reorganizing non-standard or inconsistent descriptions, simplifying actions that the machine cannot perform, etc.) and data structuring (e.g., identifying information such as seasonings, raw materials, actions, the timing and duration of the actions, and then assigning them to the corresponding defined fields), to obtain catering recipes that are more suitable for efficient use by the second server.

[0051] Food products can include dishes, staple foods, beverages, desserts, etc. This application is particularly concerned with dishes, which are highly common food products, and some of the following embodiments are also mainly illustrated by this example.

[0052] S104: The catering recipe is sent to the second server, and the second server determines an object instruction set based on the catering recipe. The instruction set includes a first object instruction for a robot that can move and pick up items, and a second object instruction for an intelligent cooking machine located in a designated cooking area.

[0053] In one or more embodiments of this specification, the cooking process is not performed by a chef, but by a second server automatically determining (e.g., generating or retrieving pre-generated) corresponding instructions based on the restaurant recipe to instruct the robot and the intelligent cooking machine to work together to produce the food products corresponding to the recipe. The first object instruction is directed to the robot, and the second object instruction is directed to the intelligent cooking machine.

[0054] The second server generates multiple sequential instructions (some of which may be weakly constrained and optional) for each cooking action specified in the recipe, forming an object instruction set. These instructions are understandable and executable by the issuing machine. During instruction generation, the intelligent cooking machine and the robot can be matched with instructions corresponding to actions that their respective capabilities are sufficient to perform. Since the intelligent cooking machine's capabilities are relatively more deterministic and its execution cost is relatively lower, it is preferable to prioritize using the intelligent cooking machine's capabilities, while allowing the robot to provide supplementary or enhanced assistance.

[0055] Enhanced assistance may enable smart cooking machines, with the help of robots, to produce food products with more sophisticated cooking methods (that exceed the cooking capabilities of smart cooking machines themselves), which will help improve the taste of food products and meet more complex and personalized needs.

[0056] These instructions can be broken down and issued in stages at a more granular and timely manner. Furthermore, subsequent instructions can be adjusted according to changes in the situation, which helps to improve the accuracy and reliability of control.

[0057] In addition, as mentioned earlier, restaurant recipes can be preprocessed. During preprocessing, the restaurant recipes can be partially or completely converted into instructions. In the case of complete instruction conversion, the restaurant recipe itself may directly constitute a set of object instructions. In this case, the restaurant recipe itself is the set of object instructions generated by the second server, which can be directly obtained by the second server. Alternatively, the second server can distinguish the instructions contained in the restaurant recipe and determine the objects to be issued.

[0058] S106: The second server sends the first object instruction to the robot, instructing the robot to take the corresponding ingredients from the designated ingredient area and move from the ingredient area (in the case of a humanoid robot, it can be more accurately described as movement or walking to better represent the anthropomorphic scene here) to the cooking area, and perform cooking and feeding (i.e., feeding raw materials) processing on the cooking container according to the cooking process corresponding to the catering recipe.

[0059] A typical workplace includes at least a cooking area and a food preparation area. The smart cooking machine can be relatively permanently located in the cooking area, primarily responsible for the actual cooking process. The food preparation area is used to store ingredients, where various pre-processed (e.g., washed, chopped) ingredients (such as pre-cleaned vegetables) can be placed for later use.

[0060] While intelligent cooking machines lack autonomous mobility and can produce tasty dishes through intelligent temperature control and digital recipes, the overall operation still relies on manual addition of ingredients and seasonings and cannot automatically serve or serve food. A significant portion of the work remains manual. Therefore, this application introduces a robot with autonomous mobility to assist in the process. This robot is used to retrieve ingredients from the ingredient area and return to the cooking area to place the retrieved ingredients into the cooking container according to the cooking process. This action serves as a supplementary aid to the aforementioned functionality.

[0061] In one or more embodiments of this specification, the robot employs at least one of the following locomotion configurations: bipedal, wheeled, or wheel-legged; the robot has a multi-degree-of-freedom robotic arm and a dexterous hand to support object-grabbing capabilities. In this configuration, triggered by a first object command, the robot can use its robotic arm and dexterous hand to retrieve one or more corresponding ingredients (i.e., ingredients required to prepare the food products specified in the current catering order) from a designated ingredient area, and then, carrying the retrieved ingredients, move them to a designated cooking area using its locomotion configuration. Of course, if the robot is not initially in the ingredient area, it needs to move there first to retrieve the ingredients.

[0062] Furthermore, in addition to ingredients, seasonings can also be retrieved by robots from the cooking or ingredient areas and then dispensed into the cooking containers in a timely manner according to the cooking process. Of course, compared to ingredients, the demand for seasonings is often much smaller and the types are more fixed. Therefore, it is also possible to deploy automated dispensing devices in the cooking area to be specifically responsible for dispensing seasonings, without relying on robots. In this case, it is also necessary to generate corresponding instructions based on the catering recipe to direct the automated dispensing devices.

[0063] In one or more embodiments of this specification, the robot performs image recognition on selectable ingredients in a designated food area to identify and retrieve the corresponding ingredients; or, based on a pre-set mapping relationship between ingredients and their positions in the designated food area, it locates and retrieves the corresponding ingredients; thereby helping to retrieve the correct ingredients more efficiently and accurately. Furthermore, the first object instruction also indicates the amount of ingredients to be retrieved (e.g., weight or volume). When the robot retrieves ingredients, it also uses its own sensors or surrounding sensors to ensure the accuracy of the retrieved amount. Of course, the robot can also retrieve more than the specified amount, but will release the exact amount when dispensing.

[0064] S108: The second object instruction is sent to the intelligent cooking machine via the second server, instructing the intelligent cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding food products for delivery to the user.

[0065] According to the cooking process, when the step requiring ingredient addition is reached, the robot (optionally, it may also have an additional automatic seasoning dispensing device) performs the corresponding ingredient or seasoning dispensing action. The intelligent cooking machine can then continue the cooking process, processing the added ingredients. Of course, multiple ingredient addition steps may be interspersed throughout the cooking process, and the robot will execute the currently reached ingredient addition step accordingly. In this way, the robot and the intelligent cooking machine cooperate to complete the cooking process, potentially without human intervention.

[0066] To achieve precise and reliable cooperation, the robot and the smart cooking machine can directly exchange commands in one-way or two-way (without necessarily requiring additional intervention from control equipment) to confirm whether the other's real-time status is normal, or can actively trigger the other to start executing the next step, or can automatically adjust the steps it is currently executing to give the other more buffer time, especially when it detects delays or other abnormalities in the other's execution.

[0067] In addition, similarly, besides smart cooking machines, robots can also work in conjunction with other food-related equipment in the workplace (such as putting cups in water dispensers or putting food to be heated into microwave ovens) to replace or even optimize tasks that were originally performed manually.

[0068] After the cooking and preparation process is completed and the corresponding food product is obtained, a notification is sent to the user to pick up the food. The user is notified via a mobile application that the food product has been prepared and is ready for pickup. Further automation can be implemented to facilitate food pickup for the user.

[0069] For example, after the cooking and preparation process is completed and the corresponding food products are obtained, a food delivery instruction is sent; in response to the food delivery instruction, the food products are moved and placed in the food collection area by a robot, or by a conveyor belt; after the user or the user's agent (e.g., a food delivery rider) is authenticated (e.g., by scanning a QR code with a mobile phone), authorization data (e.g., an unlock instruction) is issued to the user to pick up the food products in the food collection area.

[0070] pass Figure 1 This method provides users with more convenient and efficient catering services. A first server supports user ordering and prepares recipes for a specially deployed second server. Based on the second server's global scheduling, it determines (or can directly generate) and issues targeted instructions to the robot and intelligent cooking machine, directing them to work collaboratively. Based on the user's order, the second server automatically generates and matches control instructions for both, allowing the robot to focus on tasks difficult for the intelligent cooking machine, such as moving, picking up ingredients, and enhancing cooking movements. The intelligent cooking machine, with the robot's assistance, performs cooking according to the process, significantly reducing human intervention and creating more flexible and adaptable cooking capabilities. This facilitates lower-cost implementation and effectively improves catering service efficiency.

[0071] based on Figure 1 In addition to the method described herein, this specification also provides some specific implementation schemes and extension schemes of this method, which will be further explained below.

[0072] In one or more embodiments of this specification, in addition to supplementary assistance, enhanced assistance is further considered, allowing the intelligent cooking machine to summon the robot as needed to provide enhanced assistance for direct cooking actions, thereby directly affecting the taste of the food products, rather than just assisting with preparatory work. Based on this, the second server endows the intelligent cooking machine with such summoning capability when generating instructions.

[0073] Specifically, the second object instruction issued by the second server to the intelligent cooking machine may include a self-executing instruction, and optionally may also include an auxiliary summoning instruction. This application particularly proposes an auxiliary summoning instruction and builds a cooking action enhancement scheme based on machine cooperation around it.

[0074] The second server instructs the smart cooking machine to perform cooking processes on the cooking container based on its own cooking capabilities by executing self-executing instructions.

[0075] When the second object instruction includes an auxiliary summoning instruction, during the cooking process, the intelligent cooking machine summons a robot to intervene in the cooking process for the cooking container according to the auxiliary summoning instruction. After the robot intervenes, the intelligent cooking machine executes the first cooking action, and the robot executes the second cooking action under the instruction of the auxiliary summoning instruction (this mainly refers to cooking actions directly targeting the ingredients, such as frying, stir-frying, braising, boiling, etc., rather than the action of adding ingredients), so that the first cooking action and the second cooking action constitute a cooking enhancement action.

[0076] That is, the self-execution command is used to utilize the intelligent cooking machine's own cooking capabilities, while the auxiliary summoning command is used to summon the robot to directly intervene in the main work of cooking.

[0077] With the assistance of the summoning command, the intelligent cooking machine acts as the first chef, and the robot as the second chef, with both chefs working together to prepare the dish (i.e., the food product). The resulting dish, compared to one prepared solely by the first chef, exhibits an improved flavor in certain aspects or more. Therefore, this assistance effectively enhances the cooking capabilities originally provided solely by the intelligent cooking machine.

[0078] The first cooking action and the second cooking action can both be performed directly on the ingredients in the cooking container, thus enabling complex cooking actions that are difficult to achieve by intelligent cooking machines or by humans alone.

[0079] The auxiliary summoning command instructs the robot on what second cooking action to perform, and how this action should coordinate with the intelligent cooking machine's first cooking action, so as not to interfere with the first cooking action, but rather to combine them to form a new set of enhanced cooking actions. This is not only difficult for the intelligent cooking machine itself to perform, but even for humans to execute precisely, and may even disrupt the operation of the intelligent cooking machine. This application achieves enhanced cooking actions through the instruction of the auxiliary summoning command and the robot's execution capabilities.

[0080] For example, assuming the smart cooking machine is a stir-fry machine and the cooking container is a wok, the stir-fry machine typically uses a combination spatula with a rotating shaft (e.g., three spatulas spaced 120 degrees apart) to automatically stir-fry the food in the wok, and the frequency of stirring can be adjusted. In this case, the smart cooking machine performs the first cooking action of stir-frying. However, triggered by an auxiliary summoning command, the robot performs a second cooking action, such as applying a set heat setting to the stir-fried food in the wok once or multiple times from above using a blowtorch. This creates a set of enhanced cooking actions—stir-frying while intermittently applying heat to the wok—resulting in food that is not only evenly heated but also drier and slightly crispier on the surface—an effect that the smart cooking machine itself cannot easily achieve.

[0081] For example, robots can also perform a second cooking action: during a break from stir-frying, they can grab and knead some of the ingredients being cooked in the pan, shaping them before quickly returning them to the pan and continuing to stir-fry. This creates a set of enhanced cooking actions that involve simultaneously stir-frying and kneading, resulting in a dish that is already shaped or semi-shaped, rather than the loose state typical of stir-fried dishes. At the same time, the entire dish retains a stir-fried flavor, and even the shaped parts have a certain degree of stir-fried flavor inside. This is an effect that is difficult to achieve by shaping first and then processing.

[0082] Based on the above idea, similarly, the auxiliary summoning command can also be issued directly to the robot by the second server in a timely manner, so that the second server can accurately control the intelligent cooking machine and the robot to cooperate in performing enhanced cooking actions.

[0083] Strengthening the cooking process helps to give the final food products additional special flavors or forms, helps to provide positive differentiated services, helps to improve the user experience, and enhances the competitiveness of catering merchants.

[0084] More reliably, especially by taking into account the user's needs or potential needs, it can determine whether or specifically what kind of auxiliary summoning command is needed.

[0085] Specifically, the system obtains the user's corresponding dining preference information; based on the dining preference information, it determines whether the user's dining preference exceeds the smart cooking machine's own cooking capabilities; if so, it generates corresponding auxiliary summoning commands based on the gap between its own cooking capabilities and dining preferences, so as to strengthen the action through corresponding cooking preparation, make up for the gap, or even take it a step further; if not, it can rely on the smart cooking machine's own cooking capabilities to cater to the user's dining preferences and use an appropriate working mode to trigger the smart cooking machine to work.

[0086] If a user notes additional requests in their current food order (e.g., wanting the food to be crispier or softer), these additional requests can be used as food preference information. Alternatively, user food preferences can be inferred from their historical food order data. In particular, by analyzing the user's food preferences in more detail based on the cooking enhancement actions that can be performed, it is possible to bring surprises to the user.

[0087] In addition to its use in enhancing cooking to improve the quality of food products, as mentioned above, the auxiliary summoning command can also be used to dynamically adjust the overall cooking efficiency, which is especially useful in scenarios such as restaurants handling multiple orders in parallel.

[0088] In this scenario, the second server or intelligent cooking machine has an instruction buffer for receiving self-executing instructions corresponding to multiple catering orders. During the cooking process, the second server or intelligent cooking machine determines, based on changes in the data in the instruction buffer, whether the global (representing the overall situation of multiple orders) delay risk threshold has been reached; if so, it summons a robot to intervene in the cooking process using an auxiliary summoning command.

[0089] If there are too many self-executing instructions in the instruction buffer, or too much workload corresponding to the instructions, it indicates that the pressure to complete parallel orders is high, and one or more orders may be delayed. In order to reduce the risk of delay, a second server or smart cooking machine can dynamically decide which auxiliary summoning instructions to use and how many auxiliary summoning instructions to use to alleviate the pressure.

[0090] In this scenario, the second cooking action triggered by the auxiliary summoning command can primarily help the intelligent cooking machine improve its cooking efficiency. For example, the robot can use a self-heating stirrer (e.g., made into a robotic arm accessory) in conjunction with the intelligent cooking machine's own spatula to provide additional stirring and heating to the stir-fried food in the wok. Consequently, the intelligent cooking machine reduces its own cooking time so that the food can be served earlier.

[0091] Through the above scheme, based on the scheduling of the second server or the active summoning of the intelligent cooking machine, the robot can dynamically adjust its work to assist the intelligent cooking machine with enhanced cooking methods and directly provide positive intervention to the dishes.

[0092] In one or more embodiments of this specification, to facilitate more efficient carrying of the retrieved ingredients, the robot itself may be equipped with an ingredient container. If the amount of ingredients to be retrieved is small, the robot can directly use its dexterous hand to hold the ingredients and place them at the cooking container; however, if the amount of ingredients to be retrieved is large, the retrieved ingredients can be temporarily stored in the ingredient container, and then taken out of the ingredient container and placed at the cooking container.

[0093] Furthermore, the food container can include multiple separated sub-regions. In this case, it can be determined whether the cooking process involves multiple food feeding steps. If so, the robot, based on the order of at least some of the steps in the multiple food feeding steps, temporarily stores the corresponding ingredients for each step into the corresponding ordered sub-regions. For example, assuming the food container has three consecutive adjacent compartments (1, 2, and 3), and it is determined that the cooking process requires three separate food feedings at different times, the ingredients needed for the first feeding can be temporarily stored in compartment 1, the ingredients needed for the second feeding in compartment 2, and the ingredients needed for the third feeding in compartment 3. This facilitates accurate positioning and sequential feeding, resulting in greater efficiency.

[0094] After the cooking and preparation of the food products are completed, intelligent cooking machines or robots can automatically remove the products from the cooking containers (e.g., take them out of the pot) and place them in containers ready for delivery to the user, such as plates or lunchboxes. Furthermore, the cooked containers can be moved to designated cleaning equipment via robots or conveyor belts for washing; the cleaning equipment itself can also be automated. In this way, the entire food service process for the user is completed in a more fully closed loop, with smoother automation, and greater efficiency and reliability.

[0095] Based on the foregoing description, and for ease of understanding and greater intuitiveness, one or more embodiments of this specification provide... Figure 1 A schematic diagram illustrating the principle of a specific implementation scheme of the method is shown below. Figure 2 .

[0096] Figure 2The scenario depicted is a restaurant setting. The robots (represented by robot icons) and intelligent cooking machines (represented by multiple pot icons) work in a smart kitchen. The aforementioned control equipment mainly includes: a first server (represented by a desktop computer icon, which can be located at the ordering platform or in the merchant's shop) acting as the ordering server; and a second server (exemplarily called the "scheduling brain" to reflect its responsibility for issuing commands; if implemented on a cloud server, it can be called the "cloud scheduling brain"). In addition, a food storage cabinet (taking a pre-cleaned vegetable cabinet as an example) is shown, which can be placed in the aforementioned food storage area. A serving grid is also shown for placing prepared food products, and washing equipment (represented by a dishwasher icon) is also shown. The robots may employ wheeled mobility configurations, or have 7-DOF dual arms and dexterous hands with more than 6 DDOF.

[0097] Figure 2 The process of the solution may include the following steps:

[0098] Users make reservations through the app or a mini-program within the app, placing orders with the order processing system on the first server. The order processing system retrieves the restaurant recipes based on the orders and triggers the cloud-based scheduling system to analyze and process them through corresponding instructions (referred to as action instructions - dishes in the diagram).

[0099] The cloud-based scheduling system breaks down the menu into action instructions (such as the first object instruction mentioned above) and cooking instructions (such as the second object instruction mentioned above). Based on the current task sequence of the robot and the intelligent cooking machine, it issues the action instructions and cooking instructions accordingly. It should be noted that the names "action instructions" and "cooking instructions" here are exemplary. Since the robot is mainly responsible for actions such as moving and picking up, the corresponding instructions can be collectively referred to as action instructions, while the intelligent cooking machine is mainly responsible for cooking, so the corresponding instructions can be collectively referred to as cooking instructions. Of course, other reasonable names can be used as needed.

[0100] The robot, guided by a cloud-based control system, moves to a pre-cleaned vegetable cabinet, uses its arm and dexterous hand to retrieve the corresponding pre-cleaned vegetables, and then carries them to the cooking area. Following the cooking process, it sequentially adds seasonings and pre-cleaned vegetables to the cooking container (using a pot as an example). Because robots are easier to move and have a larger working radius, they are well-suited for scenarios like catering where complexity is high but precision and strength requirements are not as high. Furthermore, their humanoid hardware design allows for better compatibility with human tools, laying the hardware foundation for future functional generalization.

[0101] The intelligent cooking machine (taking stir-frying as an example) executes the stir-frying action according to the cooking instructions issued by the cloud-based scheduling brain, based on parameters such as temperature, heating time, and stir-frying rate determined by the recipe. After the food is cooked, it notifies the first server or the cloud-based scheduling brain.

[0102] Food serving and pot handling process: The processing system (such as a smart cooking machine or control equipment) issues a food serving instruction, and the food is served from the cooked food pot conveyor belt to the food serving grid, where it waits for the user or their delivery person to pick it up; the processing system issues a pot handling instruction, and after the food is served, the pot is placed in the washing equipment.

[0103] Once prepared, the user or their delivery person scans the code to pick up the meal.

[0104] In addition, robots or staff terminals can be used to notify kitchen staff to replenish the clean vegetable cabinets.

[0105] To further enhance reliability, when malfunctions occur in the kitchen involving robots and / or smart cooking machines, the cloud-based scheduling system can assist operators in manual intervention. This allows for remote control of the robots and / or smart cooking machines to attempt to restore normal operation, ensuring greater operator expertise and reducing the difficulty of handling anomalies. Alternatively, manual intervention by store staff is also possible. Furthermore, during off-peak hours, the cloud-based scheduling system can be used as a training data acquisition device to help iteratively optimize the robot.

[0106] In one or more embodiments of this specification, in a restaurant setting, multiple food orders are often processed in parallel. The robot itself may not be able to carry the necessary ingredients for these orders in a timely manner. Therefore, this application considers using a robot dog to assist the robot. Figure 3 This is a flowchart illustrating a robot-assisted solution provided in one or more embodiments of this specification.

[0107] exist Figure 3 In the scenario, the robot also has: an accompanying robot dog that is instructed by the robot or by the device that instructs the robot, the accompanying robot dog carrying a food container.

[0108] S302: The robot locates the food container carried on the accompanying robot dog and temporarily stores at least a portion of the food it has taken into the food container.

[0109] All the ingredients taken can be temporarily stored in the ingredient container carried by the accompanying robot dog; or, only a portion can be temporarily stored, and the rest can be carried directly by the robot. For example, the ingredients that are first in the delivery order can be carried directly so that they can be prepared for delivery immediately. This will improve the delivery rhythm and avoid wasting time.

[0110] S304: Move together with the accompanying robot dog to the designated cooking area in order to take ingredients from the ingredient container for the cooking feeding process.

[0111] S306: After sending the first object instruction to the mobile and retrieving robot, the robot dynamically determines (since orders are also dynamically increasing, it is necessary to determine in a timely manner based on the current number of orders) whether multiple catering orders cause the short-term demand for the same ingredient (different orders may involve multiple ingredients, and the ingredients involved in different orders may overlap) to exceed the limit.

[0112] "Short-term" can refer to the time range corresponding to these orders, or a short time range following them. "Exceeding the limit" can mean exceeding a set value, or that the quantity is likely to exceed the current quantity in the cooking area. In short, if the short-term demand exceeds the limit, it means that the current quantity of the same ingredient in the cooking area may not be enough.

[0113] S308: If so, a separation action command is sent to the accompanying robot dog to instruct the accompanying robot dog to move alone to the manual preparation area, directly obtain the same kind of ingredient from the manual preparation area, and then rejoin the robot in the ingredient area or the cooking area to continue accompanying the robot.

[0114] The manual preparation area is where kitchen staff prepare ingredients, which would normally be sent to the food preparation area. However, if a potential shortage of ingredients is predicted in advance, the robot proactively instructs its accompanying robot dog to retrieve ingredients directly from the manual preparation area. This avoids the delays caused by kitchen staff replenishing ingredients, ensuring a more reliable and timely supply of sufficient ingredients. Furthermore, because the accompanying robot dog operates independently, it doesn't prevent the robot from simultaneously retrieving ingredients or performing other tasks in the cooking area.

[0115] pass Figure 3 The proposed solution, which involves the robot working in conjunction with a companion robot dog, improves the reliability and predictability of food retrieval. It also indirectly expands the robot's operational range and helps reduce the workload of kitchen staff. Based on a similar idea, when the robot is not in use, the companion robot dog can be instructed to retrieve food, which the robot can then transfer to a designated food storage area for later retrieval when needed.

[0116] In one or more embodiments of this specification, the robot has a more timely ability to observe and analyze the cooking process. Based on this capability, a robot-based cooking adjustment scheme is further provided to accommodate more abnormal situations while ensuring the user's actual experience as much as possible. Figure 4This is a flowchart illustrating the scheme.

[0117] Figure 4 The proposed solution includes the following steps:

[0118] S402: The robot collects real-time status information of the cooking process.

[0119] S404: Based on the real-time status information, predict whether the time when the user receives the corresponding food and beverage products will be delayed (similarly, if there are other abnormal situations, consider whether the following automated compensation scheme can be adopted).

[0120] S406: If so, then based on the predicted delay, make differentiated gain adjustments to the ingredients to be retrieved, and send corresponding cooking adjustment instructions to the intelligent cooking machine.

[0121] If delays are possible, they could negatively impact the user experience. Therefore, consider automatically adjusting for differential gains to proactively compensate users for any shortcomings. Here, "gains" refers to providing users with additional benefits. For any differential gain adjustments made, proactively notify users to seek their understanding and let them know about the compensation measures being implemented. This helps to ease user frustration and ensure a positive user experience.

[0122] In one or more embodiments of this specification, based on the predicted level of delay, one or more suitable ingredients are matched to the ingredients to be retrieved as compensation ingredients. The level of delay is positively correlated with one of the following factors of the suitable ingredients: ingredient value, compensation quantity, and compensation variety. The compensation ingredients are added to the ingredients to be retrieved to achieve a gain adjustment. Whether an ingredient is suitable can be determined through large-scale model learning. Generally speaking, this means that the current order's menu may not actually contain the ingredient, but the ingredient is actually quite compatible with the menu and can enhance the flavor of the corresponding food, potentially leading to a more positive dining experience. This situation can be considered suitable. Of course, the quantity of the original ingredients can also be increased to some extent as compensation, but this compensation method is relatively less noticeable to the user.

[0123] pass Figure 4 The proposed solution, in the event of an anomaly during the food preparation stage that could potentially impact the user experience, can proactively intervene and adjust the cooking process based on the robot's anomaly sensitivity and automatic instruction capabilities. This would automatically provide the user with a suitable compensatory experience closely related to the subsequent meal, potentially enhancing the user's positive impression of the service.

[0124] Based on the same idea, one or more embodiments of this specification also provide apparatus and devices corresponding to the above methods, such as... Figure 5 , Figure 6 As shown. The apparatus and equipment are capable of performing the above methods and related alternatives accordingly.

[0125] Figure 5 This specification provides a schematic diagram of the structure of a catering business processing device according to one or more embodiments, the device comprising:

[0126] The restaurant recipe acquisition module 502 receives restaurant orders sent by users through the first server and obtains the corresponding restaurant recipes.

[0127] The object instruction determination module 504 sends the catering recipe to the second server, and the second server determines the object instruction set according to the catering recipe. The instruction set includes a first object instruction for a robot that can move and pick up items, and a second object instruction for an intelligent cooking machine in a designated cooking area.

[0128] The robot processing module 506 sends the first object instruction to the robot through the second server, instructing the robot to take the corresponding ingredients from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe.

[0129] The intelligent cooking machine processing module 508 sends the second object instruction to the intelligent cooking machine through the second server, instructing the intelligent cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding catering products for delivery to the user.

[0130] Optionally, the second object instruction includes a self-executing instruction;

[0131] The intelligent cooking machine processing module 508, through the self-execution instruction, instructs the intelligent cooking machine to perform cooking processing on the cooking container based on its own cooking capabilities.

[0132] Optionally, the second object instruction includes an auxiliary summoning instruction;

[0133] During the cooking process, the intelligent cooking machine summons the robot to intervene in the cooking process on the cooking container according to the auxiliary summoning command;

[0134] After the robot intervenes, the intelligent cooking machine performs a first cooking action. Under the instruction of the auxiliary summoning command, the robot performs a second cooking action, so that the first cooking action and the second cooking action constitute a cooking enhancement action.

[0135] Optionally, both the first cooking action and the second cooking action are performed directly on the ingredients in the cooking container.

[0136] Optionally, the object instruction determination module 504 obtains the dining preference information corresponding to the user;

[0137] Based on the dining preference information, determine whether the user's dining preferences exceed the cooking capabilities of the smart cooking machine.

[0138] If so, the corresponding auxiliary summoning command is generated based on the gap between the user's cooking ability and the user's dining preference.

[0139] Optionally, the intelligent cooking machine has an instruction buffer for receiving self-executing instructions corresponding to multiple catering orders;

[0140] During the cooking process, the intelligent cooking machine processing module 508 determines whether the global delay risk threshold has been reached based on the data changes in the instruction buffer.

[0141] If so, the robot is summoned to intervene in the cooking process of the cooking container according to the auxiliary summoning command.

[0142] Optionally, after the cooking and preparation process is completed and the corresponding food products are obtained, the robot processing module 506 sends a food delivery instruction and a food pickup notification to the user.

[0143] In response to the food dispensing instruction, the food products are moved and placed in the food collection area by the robot, or by a conveyor belt.

[0144] Upon responding to the food pickup notification, the user or their agent, after verifying their identity, issues authorization data to the user to pick up the food in the designated pickup area.

[0145] Optionally, the robot adopts at least one of bipedal, wheeled, and wheel-legged locomotion configurations, and the robot has a multi-degree-of-freedom robotic arm and a dexterous hand; the food preparation area is prepared in advance by humans, with various pre-processed food ingredients placed therein.

[0146] The robot processing module 506 instructs the robot to retrieve one or more corresponding ingredients from the designated ingredient area using the robotic arm and the dexterous hand; and...

[0147] The robot is instructed to move the retrieved ingredients to the designated cooking area via the mobile configuration.

[0148] Optionally, the robot further comprises: an accompanying robot dog, which is instructed by the robot or by the device that instructs the robot, the accompanying robot dog carrying a food container;

[0149] The robot processing module 506 uses the robot to temporarily store at least a portion of the food ingredients it has picked up into the food ingredient container.

[0150] The accompanying robot dog moves to the designated cooking area to retrieve ingredients from the ingredient container for the cooking process.

[0151] Optionally, the food container includes multiple separated sub-regions;

[0152] The robot processing module 506 determines whether the cooking process includes multiple ingredient feeding steps.

[0153] If so, the robot will temporarily store the ingredients corresponding to each step into the corresponding ordered sub-regions according to the order of at least some of the steps in the multiple ingredient feeding steps.

[0154] Optionally, multiple of the aforementioned catering orders are processed in parallel.

[0155] The robot processing module 506, after sending the first object instruction to the mobile and item-handling robot, dynamically determines whether multiple catering orders cause the short-term demand for the same ingredient to exceed the limit based on the first object instruction.

[0156] If so, a separation action command is sent to the accompanying robot dog, instructing the accompanying robot dog to move independently to the manual preparation area, directly obtain the same type of ingredient from the manual preparation area, and then rejoin the robot in the ingredient area or the cooking area to continue accompanying the robot.

[0157] Optionally, the intelligent cooking machine processing module 508 is configured by the robot to send at least a portion of the second object instructions to the intelligent cooking machine based on the execution status of the first object instructions.

[0158] Optionally, the robot processing module 506 collects real-time status information of the cooking process through the robot;

[0159] Based on the real-time status information, predict whether the time when the user receives the corresponding food and beverage products will be delayed;

[0160] If so, then based on the predicted delay, the ingredients to be retrieved will be adjusted with differentiated gain, and corresponding cooking adjustment instructions will be sent to the intelligent cooking machine.

[0161] Optionally, the robot processing module 506 matches one or more suitable ingredients to be retrieved as compensation ingredients based on the predicted level of delay. The level of delay is positively correlated with one of the following factors of the suitable ingredients: ingredient value, compensation amount, and compensation variety.

[0162] The compensation ingredients are added to the ingredients to be taken in order to achieve gain adjustment.

[0163] Optionally, the robot processing module 506 uses the robot to perform image recognition on the selectable ingredients in the designated food area, thereby identifying and picking up the corresponding ingredients;

[0164] Alternatively, based on a pre-defined mapping relationship between ingredients and their positions in the designated ingredient area, the corresponding ingredients can be located and retrieved.

[0165] Optionally, the robot processing module 506, according to the cooking process, delivers the ingredients to the cooking container and delivers seasonings taken from the ingredient area or the cooking area.

[0166] Optionally, after the cooking process is completed and the corresponding food products are obtained, the robot processing module 506 moves the cooked container after serving to a predetermined cleaning device via the robot or a conveyor belt for cleaning.

[0167] Optionally, the first object instruction and / or the second object instruction are sent to the corresponding device via the second server;

[0168] The device further includes:

[0169] The remote operation module 510, when an abnormal situation occurs in the kitchen involving the robot and / or the cooking container, can perform remote operation through manual intervention by the second server to attempt to restore normal operation.

[0170] Figure 6 This specification provides a schematic diagram of the structure of a catering business processing device according to one or more embodiments, the device comprising:

[0171] At least one processor; and,

[0172] A memory communicatively connected to the at least one processor; wherein,

[0173] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform:

[0174] The system receives restaurant orders from users through a first server and retrieves the corresponding restaurant recipes.

[0175] The catering recipe is sent to a second server, which determines a set of object instructions based on the catering recipe. The set of instructions includes a first object instruction for a robot that can move and pick up objects, and a second object instruction for an intelligent cooking machine located in a designated cooking area.

[0176] The second server sends the first object instruction to the robot, instructing the robot to take the corresponding ingredient from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe;

[0177] The second server sends the second object instruction to the smart cooking machine, instructing the smart cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding food products for delivery to the user.

[0178] Based on the same idea, one or more embodiments of this specification also provide a non-volatile computer storage medium storing computer-executable instructions configured as follows:

[0179] The system receives restaurant orders from users through a first server and retrieves the corresponding restaurant recipes.

[0180] The catering recipe is sent to a second server, which determines a set of object instructions based on the catering recipe. The set of instructions includes a first object instruction for a robot that can move and pick up objects, and a second object instruction for an intelligent cooking machine located in a designated cooking area.

[0181] The second server sends the first object instruction to the robot, instructing the robot to take the corresponding ingredient from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe;

[0182] The second server sends the second object instruction to the smart cooking machine, instructing the smart cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding food products for delivery to the user.

[0183] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0184] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0185] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0186] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0187] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments of this specification can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0188] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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 a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0189] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0190] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0191] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0192] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0193] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, 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 technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0194] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0195] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0196] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0197] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0198] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for processing catering business, comprising: The system receives restaurant orders from users through a first server and retrieves the corresponding restaurant recipes. The catering recipe is sent to a second server, which determines a set of object instructions based on the catering recipe. The set of instructions includes a first object instruction for a robot that can move and pick up objects, and a second object instruction for an intelligent cooking machine located in a designated cooking area. The second server sends the first object instruction to the robot, instructing the robot to take the corresponding ingredient from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe; The second object instruction is sent to the smart cooking machine through the second server, instructing the smart cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding food products for delivery to the user.

2. The method of claim 1, wherein the second object instruction includes a self-executing instruction; The instruction to the intelligent cooking machine to perform cooking processing on the cooking container according to the cooking process specifically includes: The self-executing instructions instruct the intelligent cooking machine to perform cooking processes on the cooking container based on its own cooking capabilities.

3. The method of claim 1, wherein the second object instruction includes an auxiliary summoning instruction; The instruction to the intelligent cooking machine to perform cooking processing on the cooking container according to the cooking process specifically includes: During the cooking process, the intelligent cooking machine summons the robot to intervene in the cooking process on the cooking container according to the auxiliary summoning command; After the robot intervenes, the intelligent cooking machine performs a first cooking action, and the robot performs a second cooking action under the instruction of the auxiliary summoning command, so that the first cooking action and the second cooking action constitute a cooking enhancement action.

4. The method as described in claim 3, wherein both the first cooking action and the second cooking action are performed directly on the ingredients in the cooking container.

5. The method as described in claim 3, wherein determining the object instruction set based on the catering recipe specifically includes: Obtain the dining preference information corresponding to the user; Based on the dining preference information, determine whether the user's dining preferences exceed the cooking capabilities of the smart cooking machine. If so, the corresponding auxiliary summoning command is generated based on the gap between the user's cooking ability and the user's dining preference.

6. The method as described in claim 3, wherein the intelligent cooking machine has an instruction buffer for receiving self-executing instructions corresponding to multiple catering orders; During the cooking process, the intelligent cooking machine, according to the auxiliary summoning command, summons the robot to intervene in the cooking process targeting the cooking container, specifically including: During the cooking process, the intelligent cooking machine determines whether the global delay risk threshold has been reached based on the data changes in the instruction buffer. If so, the robot is summoned to intervene in the cooking process of the cooking container according to the auxiliary summoning command.

7. The method of claim 1, further comprising: After the cooking and preparation process is completed and the corresponding food products are obtained, a food delivery instruction is sent, and a food pickup notification is sent to the user. In response to the food dispensing instruction, the food products are moved and placed in the food collection area by the robot, or by a conveyor belt. Upon responding to the food pickup notification, the user or their agent, after verifying their identity, issues authorization data to the user to pick up the food in the designated pickup area.

8. The method of claim 1, wherein the robot further comprises: an accompanying robot dog, which is instructed by the robot or by the device instructing the robot, the accompanying robot dog carrying a food container; The movement from the food ingredient area to the designated cooking area specifically includes: The robot temporarily stores at least a portion of the food it has taken into the food container; The accompanying robot dog moves to the designated cooking area to retrieve ingredients from the ingredient container for the cooking process.

9. The method of claim 8, wherein the food container comprises a plurality of separated sub-regions; The step of temporarily storing at least a portion of the taken ingredients in the ingredient container specifically includes: Determine whether the cooking process includes multiple steps of adding ingredients; If so, the robot will temporarily store the ingredients corresponding to each step into the corresponding ordered sub-regions according to the order of at least some of the steps in the multiple ingredient feeding steps.

10. The method of claim 8, wherein multiple catering orders are being processed in parallel; After the first object instruction is sent to the robot via the second server, the method further includes: The robot dynamically determines, based on the instructions from the first object, whether multiple catering orders result in an excessive short-term demand for the same ingredient. If so, a separation action command is sent to the accompanying robot dog, instructing the accompanying robot dog to move independently to the manual preparation area, directly obtain the same type of ingredient from the manual preparation area, and then rejoin the robot in the ingredient area or the cooking area to continue accompanying the robot.

11. The method of claim 1, further comprising: The robot collects real-time status information of the cooking and preparation process. Based on the real-time status information, predict whether the time when the user receives the corresponding food and beverage products will be delayed; If so, then based on the predicted delay, the ingredients to be retrieved will be adjusted with differentiated gain, and corresponding cooking adjustment instructions will be sent to the intelligent cooking machine.

12. The method as described in claim 11, wherein adjusting the differential gain of the ingredients to be retrieved based on the predicted delay specifically includes: Based on the predicted level of delay, one or more suitable ingredients are matched with the ingredients to be obtained as compensation ingredients. The level of delay is positively correlated with one of the following factors of the suitable ingredients: ingredient value, compensation amount, and compensation variety. The compensation ingredients are added to the ingredients to be taken in order to achieve gain adjustment.

13. The method of claim 1, further comprising: After the cooking process is completed and the corresponding food products are obtained, the cooked containers are moved to a predetermined cleaning device by the robot or by conveyor belt for cleaning.

14. The method of claim 1, further comprising: When an abnormal situation occurs in the kitchen involving the robot and / or the smart cooking machine, the operator can remotely intervene through the assistance of the second server to attempt to restore normal operation.

15. A catering service processing device, comprising: The restaurant recipe acquisition module receives restaurant orders sent by users through a first server and retrieves the corresponding restaurant recipes. The object instruction determination module sends the catering recipe to the second server, and the second server determines the object instruction set based on the catering recipe. The instruction set includes a first object instruction for a robot that can move and pick up items, and a second object instruction for an intelligent cooking machine located in a designated cooking area. The robot processing module sends the first object instruction to the robot through the second server, instructing the robot to take the corresponding ingredients from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe; The intelligent cooking machine processing module sends the second object instruction to the intelligent cooking machine through the second server, instructing the intelligent cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding catering products for delivery to the user.

16. The apparatus of claim 15, wherein the second object instruction includes an auxiliary summoning instruction; The intelligent cooking machine processing module, during the cooking process, summons the robot to intervene in the cooking process of the cooking container according to the auxiliary summoning command. After the robot intervenes, the intelligent cooking machine performs a first cooking action, and the robot performs a second cooking action under the instruction of the auxiliary summoning command, so that the first cooking action and the second cooking action constitute a cooking enhancement action.

17. The apparatus of claim 15, further comprising: The remote operation module allows for remote operation by the operator, assisted by the second server, to attempt to restore normal operation when an abnormal situation occurs in the kitchen, involving the robot and / or the smart cooking machine.

18. A catering service processing device, comprising: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform: The system receives restaurant orders from users through a first server and retrieves the corresponding restaurant recipes. The catering recipe is sent to a second server, which determines a set of object instructions based on the catering recipe. The set of instructions includes a first object instruction for a robot that can move and pick up objects, and a second object instruction for an intelligent cooking machine located in a designated cooking area. The second server sends the first object instruction to the robot, instructing the robot to take the corresponding ingredient from the designated ingredient area and move from the ingredient area to the cooking area, and perform cooking and feeding processing on the cooking container according to the cooking process corresponding to the catering recipe; The second object instruction is sent to the smart cooking machine through the second server, instructing the smart cooking machine to perform cooking processing on the cooking container according to the cooking process, so as to obtain the corresponding food products for delivery to the user.

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