Central rotating robotic automatic portioning system and method for multi-person table
The central rotating robot automatic meal distribution system solves the problem of cross-infection in multi-person dining scenarios, realizes automatic and accurate distribution of dishes and dynamic adjustment of the order of meal distribution, and improves the dining experience and efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- HEGANG CHANGLIDAN TRADING CO LTD
- Filing Date
- 2026-04-30
- Publication Date
- 2026-06-05
Smart Images
Figure CN122143050A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of catering service equipment technology, and in particular to a central rotating robot automatic food dispensing system and method for multi-person dining tables. Background Technology
[0002] In restaurants, wedding banquets, family gatherings, canteens, and other multi-person dining settings, the traditional way of dining involves all diners taking food from the same communal plate. While this method fosters interaction and atmosphere, it also presents significant hygiene and safety risks—diners' saliva can contaminate food through shared utensils or contact during the food-taking process, potentially leading to the cross-transmission of pathogens such as Helicobacter pylori and hepatitis A virus. To address this issue, some restaurants use serving chopsticks and spoons or have staff manually portion the food. The former relies on diners' self-discipline and cannot completely avoid indirect contact, while the latter suffers from low efficiency, uneven portion sizes, and high labor costs. In recent years, with the development of service robot technology, products such as food delivery robots and automatic rotating serving tables have emerged on the market. However, these devices can only transport or rotate food; they cannot proactively separate food from communal plates to individual utensils.
[0003] The existing technology lacks a system that can automatically, accurately, and hygienically distribute food from a shared dining table to each diner's personal utensils in a multi-person dining scenario. This makes it impossible to effectively solve the risk of cross-infection during shared meals, and manual food distribution methods are difficult to balance efficiency, hygiene, and cost. Summary of the Invention
[0004] To overcome the above deficiencies, the present invention provides a central rotating robot automatic food distribution system and method for multi-person dining tables, aiming to improve the problem of the lack of a food distribution system in the prior art that can automatically, accurately and hygienically distribute dishes to each diner's personal tableware.
[0005] In a first aspect, the present invention provides the following technical solution: a central rotating robot automatic food distribution system for multi-person dining tables, comprising the following modules: The initialization module is used to acquire and record table configuration information, which includes the position of the main body of the serving robot, the position of each diner, and the fixed correspondence between the grids of the multi-compartment plate corresponding to each diner and the dishes. The recognition module is used to identify the types of dishes in the public serving trays and match the corresponding picking parameters; The sensing module is used to detect the state of the diners and the safety status around the main body of the food dispensing robot; The food serving module is used to control the main body of the food serving robot to pick up the target dish from the public plate according to the picking parameters, and after the picking amount reaches the preset condition, to put the target dish into the grid corresponding to the target diner according to the fixed correspondence. The control module is used to dynamically adjust the order of meal distribution by the meal distribution execution module based on the diner's status detected by the sensing module.
[0006] Preferably, in the initialization module, the step of acquiring and recording the table configuration information specifically includes: Obtain table layout information, including the working position of the main body of the food-serving robot in the central area of the table; Obtain the grid layout information of the multi-compartment plate set at each dining seat, wherein the grid layout information includes the relative position of each compartment in the multi-compartment plate; Obtain the binding information between dishes and grids, wherein the binding information is used to establish a fixed correspondence between each dish and a grid on a dining seat; The table layout information, the grid layout information, and the binding information are associated and stored as the table configuration information.
[0007] Preferably, in the recognition module, the step of recognizing the type of food on the public plate and matching the corresponding picking parameters specifically includes: Collect images of food items from public dining trays; Image recognition is performed on the food images to identify the type of each dish in the public serving dish; Based on the identified dish type, the corresponding clamping parameters are matched from the preset clamping strategy library; The matched gripping parameters are output to the food serving execution module, which then controls the main body of the food serving robot to perform gripping operations.
[0008] Preferably, the step of matching the corresponding clamping parameters from a preset clamping strategy library based on the identified dish type specifically includes: Obtain the identified dish type and use the dish type as the query key value; Based on the query key value, perform a matching query in the preset pinch strategy library; When a match is successful, extract the clamping parameters corresponding to the dish type; When a match fails, the default clamping parameters are loaded, and a prompt message is generated to request the user to confirm or supplement the clamping parameters corresponding to the dish type.
[0009] Preferably, in the sensing module, the steps of detecting the diner's state and the safety status around the main body of the food dispensing robot specifically include: Collect images of the status of the multi-compartment plates for each diner; Image analysis is performed on the plate status image to detect the emptying status of each compartment and generate diner status information; Collect environmental perception data around the main body of the food dispensing robot; Based on the environmental perception data, the system detects whether any personnel have entered the preset danger zone around the main body of the food dispensing robot and generates safety status information. The system outputs the diner's status information to the control module and the safety status information to the meal distribution execution module, so as to control the meal distribution execution module to suspend the meal distribution operation when a person enters a preset danger area.
[0010] Preferably, in the meal distribution execution module, the step of placing the target dish into the grid corresponding to the target diner according to the fixed correspondence specifically includes: Obtain the clamping parameters matched by the recognition module; The gripper of the food dispensing robot is controlled to move to the target dish on the public plate according to the gripping parameters, and the gripping operation is performed. After the gripping operation is completed, the gripping weight is measured; Determine whether the clamping weight has reached the preset condition. If not, repeat the clamping operation until the clamping weight reaches the preset condition. When the gripping weight reaches the preset condition, the main body of the food dispensing robot is controlled to rotate to the target diner's position according to the position of each diner; Based on the fixed correspondence between grids and dishes, determine the target grid corresponding to the target dish; The gripper of the food dispensing robot is controlled to place the target dish into the corresponding target compartment of the multi-compartment plate of the target diner.
[0011] Preferably, in the control module, the step of dynamically adjusting the meal distribution order of the meal distribution execution module specifically includes: Obtain the diner's status information detected by the sensing module; Based on the diners' status information, determine the priority of meal distribution for each diner; Generate a target diner sequence according to the order of meal distribution priority from high to low; The target diners sequence is output to the meal distribution execution module to control the meal distribution execution module to perform the meal distribution operation sequentially according to the target diners sequence.
[0012] Preferably, the step of determining the meal allocation priority for each diner based on the diner's status information specifically includes: Get the empty status of the compartments corresponding to the dishes to be served in the multi-compartment plates for each diner; Diners whose grids corresponding to the dishes to be served have been cleared are designated as first priority; Diners whose grid corresponding to the currently unserved dishes are not cleared are designated as the second priority; Set the priority level of the first priority to be higher than that of the second priority.
[0013] Preferably, the main body of the food dispensing robot is equipped with a motion mechanism, which includes: A rotating mechanism is used to drive the main body of the food dispensing robot to rotate around its own axis; A moving mechanism is used to drive the main body of the food-dispensing robot to move in the central area of the dining table; The moving mechanism and the rotating mechanism work together to enable the main body of the food-dispensing robot to perform a rotating food-dispensing operation at the moved position.
[0014] Secondly, the present invention provides the following technical solution: a method for automatic food distribution by a central rotating robot at a multi-person dining table, the method comprising: Acquire and record table configuration information, which includes the position of the main body of the serving robot, the position of each diner, and the fixed correspondence between the grids of the multi-compartment plate corresponding to each diner and the dishes. Identify the types of dishes in the public serving trays and match the corresponding picking parameters; Detect the status of diners and the safety status around the main body of the food dispensing robot; The main body of the food dispensing robot is controlled to pick up the target dish from the public plate according to the picking parameters, and after the picking amount reaches the preset condition, the target dish is placed into the grid corresponding to the target diner according to the fixed correspondence. The meal distribution order of the meal distribution execution module is dynamically adjusted based on the diner's status detected by the sensing module.
[0015] The present invention has the following beneficial effects: 1. In this invention, by setting up a central rotating food distribution robot, the food in the public plate is automatically picked up and placed into the multi-compartment plate for each diner. During the entire food distribution process, the diner does not need to touch the public tableware or public plate, which physically isolates the risk of saliva transmission and cross-infection.
[0016] 2. In this invention, by integrating a weighing sensor at the end of the gripper, the weight being gripped is detected in real time during the gripping process. Feedback control ensures that the amount gripped each time reaches the preset amount. When the amount gripped is insufficient, additional gripping is automatically performed. When the amount gripped exceeds the limit, fine-tuning and release can be achieved, thereby realizing precise control of the portion size for each diner. At the same time, through a preset gripping strategy library, different gripping forces, speeds, and number of times are matched for different types of dishes, ensuring the standardization and consistency of the portioning of various solid dishes and solving the problem of uneven portioning by manual serving.
[0017] 3. In this invention, the sensing module detects the emptying status of each compartment in the multi-compartment plate of each diner in real time, and the control module dynamically determines the food distribution priority based on the emptying status, giving priority to diners whose compartments have been emptied, thus avoiding food from piling up on the plate and getting cold or diners waiting too long; at the same time, when it is detected that a diner leaves the table, the food distribution for that diner is automatically paused and resumed when the diner returns, thus realizing intelligent adaptation of the food distribution rhythm to the dining progress and improving the dining experience. Attached Figure Description
[0018] Figure 1 This is a schematic diagram of the architecture of the central rotating robot automatic food distribution system for multi-person dining tables proposed in this invention. Figure 2 This is a schematic diagram of the process for the automatic food distribution method using a central rotating robot for multi-person dining tables proposed in this invention. Detailed Implementation
[0019] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0020] Example 1: In a first embodiment of the invention, the invention provides a centrally rotating robotic automatic food dispensing system for multi-person dining tables, such as... Figure 1 As shown, it includes the following modules: The initialization module is used to acquire and record the table configuration information, which includes the position of the main body of the serving robot, the position of each diner, and the fixed correspondence between the grid of the multi-compartment plate for each diner and the dishes.
[0021] Furthermore, in the initialization module, the steps for obtaining and recording the dining table configuration information specifically include: Obtain table layout information, including the working position of the main body of the food-serving robot in the central area of the table; Obtain the grid layout information of the multi-compartment plates set at each dining seat, including the relative position of each compartment in the multi-compartment plate; Obtain the binding information between dishes and grids, wherein the binding information is used to establish a fixed correspondence between each dish and a grid on a dining seat; The table layout information, grid layout information, and binding information are stored together as table configuration information.
[0022] Specifically, the system first acquires the table layout information. The main body of the serving robot is pre-fixed in the center of the table, and the system obtains its position coordinates by reading preset installation parameters. The position information of each dining seat distributed around the robot body is obtained in the following ways: the system controls the robot body to rotate one full circle, using a lidar or vision sensor installed on it to scan the environment around the table, identify the position of the positioning slot corresponding to each dining seat, and record the polar coordinates (including radial distance and angular offset) of each dining seat relative to the center point of the robot body; or, the system receives the number of dining seats and distribution parameters input by the user through an interactive interface, and automatically generates the polar coordinates of each dining seat. The positioning slot corresponding to each dining seat is pre-fixed on the table to accommodate and fix multiple plates.
[0023] At each dining seat, a multi-compartment plate is detachably installed on the table via positioning slots. The positioning slots are recessed structures whose shape matches the bottom of the multi-compartment plate. The plate is secured in the slots using snaps or magnets, ensuring it doesn't shift during serving. The plate can be removed for cleaning. The system obtains the compartment layout information of the multi-compartment plate at each dining seat: either by acquiring images of the multi-compartment plate through a visual recognition module, identifying the relative position of each compartment, and recording its number and coordinates; or by reading a preset plate configuration file.
[0024] The system obtains the binding information between dishes and grids. This binding information is used to establish a fixed correspondence between each dish and a grid on a dining table. Specific methods of obtaining this information include: displaying a list of dishes and a grid layout diagram through an interactive interface, receiving the target dining table and target grid specified by the user for each dish; or automatically assigning dishes according to preset rules, such as assigning them sequentially to the first available grid on each dining table according to the order in which they are served, or assigning them to grids of the corresponding type according to the dish type.
[0025] The system associates and stores the acquired table layout information, grid layout information, and binding information as table configuration information. It establishes a data structure that includes a robot main body position field, a seat list field, a positioning slot position field corresponding to each seat, a grid layout field, and a dish-grid mapping field. This data is stored in non-volatile memory for subsequent meal distribution operations.
[0026] Through the above steps, the initialization module completes the configuration of the physical layout and allocation rules of the dining tables, providing a complete location benchmark and allocation basis for subsequent meal distribution operations.
[0027] The identification module is used to identify the types of dishes in the public serving dishes and match the corresponding picking parameters.
[0028] Furthermore, in the recognition module, the steps of identifying the types of dishes on the public serving trays and matching the corresponding gripping parameters specifically include: Collect images of food items from public dining trays; Image recognition is performed on the food images to identify the type of each dish in the communal serving dish; Based on the identified dish type, the corresponding clamping parameters are matched from the preset clamping strategy library; The matched gripping parameters are output to the food serving execution module, which then controls the main body of the food serving robot to perform gripping operations.
[0029] Furthermore, the step of matching the corresponding clamping parameters from the preset clamping strategy library based on the identified dish type specifically includes: Obtain the identified dish type and use the dish type as the query key value; Based on the query key value, perform a matching query in the preset pinch strategy library; When a match is successful, extract the clamping parameters corresponding to the dish type; When a match fails, the default gripping parameters are loaded and a prompt message is generated to request the user to confirm or supplement the gripping parameters corresponding to the dish type.
[0030] Specifically, the system uses a color camera mounted on the main body of the food-distributing robot to capture images of the food on the shared serving tray. Image acquisition is triggered when the robot rotates to the location of the shared serving tray, obtaining an RGB image of the area containing the food.
[0031] The system employs a pre-trained convolutional neural network model to identify the type of each dish from the collected images. The model uses either ResNet50 or MobileNetV2 architecture. During training, it utilizes an image dataset labeled with dish categories, containing at least 200 common solid dishes, with at least 1000 images of each dish taken from different angles and under varying lighting conditions. During recognition, the image size is normalized to 224×224 pixels before being input into the model for forward propagation. The model's output layer uses a Softmax activation function to output the probability distribution for each dish category. The system selects the category with the highest probability as the recognition result and records the confidence score. If the confidence score falls below a preset threshold, the system generates a prompt requesting manual confirmation from the user.
[0032] The system matches corresponding clamping parameters from a pre-defined clamping strategy library based on the identified dish type. The clamping strategy library is stored in non-volatile memory using a key-value pair data structure, where the key is the dish type identifier and the value is the corresponding set of clamping parameters. During matching, the system uses the identified dish type as the query key to perform a matching query: if a match is found, the corresponding clamping parameters are extracted; if no match is found, default clamping parameters are loaded, and the user is prompted through an interactive interface to confirm or supplement the parameters. The supplemented parameters are then stored in association to achieve dynamic updates to the strategy library.
[0033] The clamping parameters include clamping force (2N to 15N, determined according to the hardness of the dish), clamping speed (50mm / s to 200mm / s, determined according to the fragility of the dish), number of clamping operations (positive integer, used for dishes requiring multiple clamping operations), and target weight for a single clamping operation (20g to 100g, determined according to the portion size requirements of the dish). Different types of dishes correspond to different parameter combinations. For example, for block-shaped dishes, the corresponding clamping force is 8N, clamping speed is 150mm / s, number of clamping operations is 1, and target weight for a single clamping operation is 50g; for fragile dishes, the corresponding clamping force is 3N, clamping speed is 60mm / s, number of clamping operations is 1, and target weight for a single clamping operation is 30g.
[0034] The system transmits the matched gripping parameters to the food dispensing module through the internal communication interface, so that the module can control the robot to perform the gripping operation.
[0035] Through the above process, the recognition module completes the entire processing chain from image acquisition to parameter output, providing precise control parameters for subsequent meal distribution.
[0036] The perception module is used to detect the diners' status and the safety status around the main body of the food dispensing robot.
[0037] Furthermore, in the perception module, the steps for detecting the diner's state and the safety status around the food-dispensing robot specifically include: Collect images of the status of the multi-compartment plates for each diner; Image analysis is performed on the plate status image to detect the emptying status of each compartment and generate diner status information; Collect environmental perception data around the main body of the food dispensing robot; Based on environmental perception data, the robot detects whether anyone has entered a pre-set danger zone around its main body and generates safety status information. The system outputs the diner's status information to the control module and the safety status information to the meal distribution execution module, so that the meal distribution execution module can be controlled to suspend the meal distribution operation when someone enters the preset danger area.
[0038] Specifically, the system uses a color camera mounted on the main body of the serving robot to capture images of the status of the multi-compartment plates corresponding to each diner. When the robot rotates to the front of each dining position, it triggers a vision sensor to capture images of the multi-compartment plates at that position. The image resolution is no less than 1280×720 pixels, covering the entire multi-compartment plate area.
[0039] The system employs a deep learning-based image segmentation model to analyze plate status images, detecting the empty status of each grid cell and generating diner status information. The model uses either Mask R-CNN or U-Net architecture, and during training, it utilizes image datasets labeled with grid boundaries and empty status tags. During recognition, the plate status image is input into the model, which outputs a pixel-level segmentation mask for each grid cell and its empty status classification result, generating a list of empty grid cells for each diner. To improve detection reliability, the system simultaneously uses color analysis and contour detection as auxiliary judgment methods: the image is converted to the HSV color space, and the color histogram features of each grid region are extracted. When the dominant color tone of a grid region matches the preset plate background color and there is no obvious food texture inside, it is determined to be in an empty state. The system weightedly fuses the deep learning model results and the auxiliary judgment results; in case of inconsistency, the deep learning model result prevails, and abnormal events are recorded.
[0040] The system collects environmental data by installing environmental sensing sensors around the base of the food-dispensing robot. These sensors include infrared grating sensors, millimeter-wave radar sensors, ultrasonic sensors, or lidar sensors, covering a 360-degree range. The detection distance is adjustable from 0.5 meters to 1.5 meters, and data is continuously collected at a frequency of no less than 10 Hz. The system outputs a signal indicating the presence of obstacles or people within the detection range.
[0041] The system detects whether personnel have entered a preset danger zone based on environmental perception data and generates safety status information. The preset danger zone is a ring-shaped area with a radius of 0.3 to 0.5 meters around the robot's main body (set according to the maximum extension distance of the robotic arm). When a sensor in any direction detects an object within the preset danger radius, it determines that personnel have entered the danger zone and generates a danger status indicator; otherwise, it is determined to be a safe state. The system also records the intrusion direction information.
[0042] The system outputs diners' status information to the control module and safety status information to the meal distribution execution module. Diner status information includes diners' identifiers, grid numbers, clear status, and timestamps; safety status information is transmitted as a Boolean value of "safe" or "dangerous." When the meal distribution execution module receives a danger status indicator, it immediately pauses the meal distribution operation and issues an audio warning; after the safety status is restored, it resumes the unfinished meal distribution operation upon receiving a resumption command.
[0043] Through the above process, the perception module realizes real-time monitoring of the diner's plate status and continuous perception of the safety environment around the robot, providing data support for the dynamic scheduling of the control module and the safety control of the meal distribution module.
[0044] The food serving module controls the main body of the food serving robot to pick up the target dishes from the public plate according to the picking parameters, and after the picking amount reaches the preset condition, it puts the target dishes into the grid corresponding to the target diners according to a fixed correspondence.
[0045] Furthermore, in the meal distribution module, the specific steps of placing the target dish into the corresponding grid of the target diner according to a fixed correspondence include: Obtain the clamping parameters matched by the recognition module; The gripper of the food dispensing robot is controlled to move to the target dish on the public plate according to the gripping parameters and perform the gripping operation. After the gripping operation is completed, the gripping weight is measured; Determine whether the gripping weight has reached the preset condition. If not, repeat the gripping operation until the gripping weight reaches the preset condition. When the weight being gripped reaches the preset condition, the main body of the food dispensing robot is controlled to rotate to the target diner's position according to the position of each diner. Based on the fixed correspondence between grids and dishes, determine the target grid corresponding to the target dish; The gripper of the food-dispensing robot is controlled to place the target dish into the corresponding compartment of the multi-compartment plate of the target diner.
[0046] Specifically, the food serving module controls the food serving robot to pick up target dishes from the public tray according to the picking parameters, and after the picked-up quantity reaches the preset condition, it places the target dishes into the corresponding compartment of the target diner according to a fixed correspondence. The specific implementation process of this module is as follows.
[0047] The meal serving module obtains the gripping parameters matched by the recognition module through the system's internal communication interface. These gripping parameters are transmitted in the form of a parameter structure, which includes fields for gripping force, gripping speed, number of grips, and target weight for a single grip. The gripping force is in Newtons, the gripping speed is in millimeters per second, the number of grips is a positive integer, and the target weight for a single grip is in grams.
[0048] The food dispensing module controls the gripper of the food dispensing robot to move to the target dish on the communal plate according to the gripping parameters, and then performs the gripping operation. Specifically, the system first obtains the three-dimensional spatial coordinates of the target dish on the communal plate through the vision recognition module, and uses a hand-eye calibration method to convert the image coordinates into spatial coordinates in the coordinate system of the robot arm base. The motion trajectory of the gripper is calculated by an inverse kinematics algorithm, and the motion trajectory is planned using a fifth-order polynomial interpolation method to ensure smooth motion. After the gripper reaches the target position, it controls the gripper to close according to the gripping force parameters. The gripping force is realized through the current closed-loop control of the servo motor, and the actual gripping force is... Clamping force with target The deviation is adjusted by a PID controller: ; in, To control the output, = - This is the deviation amount. , , These are the proportional, integral, and differential coefficients, which were determined through experimental calibration.
[0049] After the gripping operation is completed, the meal dispensing module detects the gripped weight using a load cell integrated into the gripper. The load cell is a resistance strain gauge sensor, and its output signal is converted from analog to digital to obtain the weight value W_actual. The system remains stationary for 0.5 seconds after the gripper closes, and reads the weight value after the sensor signal stabilizes. The average of three consecutive readings is taken as the actual gripped weight.
[0050] The food serving module determines whether the weight to be picked up meets a preset condition. Let the target weight for a single pick-up be... The allowable error range is The preset conditions are: ; The allowable error range ΔW is set according to the type of dish: 5 to 10 grams for chunky dishes and 3 to 5 grams for fragile dishes.
[0051] when < - If the system determines that the gripping weight is insufficient, it will perform a compensating gripping operation. The compensating gripping uses an incremental control strategy; let the actual gripping weight be... Then compensate for the target weight = - The system repeats steps two and three until the cumulative gripped weight meets the preset condition. To prevent infinite looping, a maximum number of grips is set. If the preset conditions cannot be met even after the number of pinches reaches N_max, the current cumulative weight is used as the final result and the abnormal event is recorded.
[0052] when > + If the system determines that the weight being gripped exceeds the limit, it will perform a release compensation operation. The grippers will slightly open, releasing the food in steps. After each release, the weight will be re-checked until W_actual falls below the preset range. The release step size is set according to the type of food: 5 to 10 grams for chunky foods and 2 to 5 grams for fragile foods. Once the gripping weight reaches the preset threshold, the food dispensing module, based on the position of each diner recorded by the initialization module, controls the main body of the food dispensing robot to rotate to the target diner's location. The main body of the food dispensing robot is equipped with a rotating base, and precise angle control is achieved through a servo motor drive. Let the current position angle of the main body of the food dispensing robot be θ. The target diners' position angle is Then the rotation angle The system uses closed-loop control to rotate the base. The angle and rotation speed are set to 30 to 60 degrees per second to ensure smooth operation.
[0053] The serving module determines the target grid corresponding to the target dish based on the fixed correspondence between grids and dishes recorded by the initialization module. Specifically, the system queries the binding information stored in the initialization module to obtain the diner's identifier and grid number corresponding to the current dish identifier, and generates the target grid position coordinates. The target grid position coordinates are local coordinates relative to the center of the multi-grid plate, which are converted into spatial coordinates in the robotic arm base coordinate system through a pre-calibrated transformation matrix.
[0054] The food dispensing module controls the grippers of the food dispensing robot to place the target dish into the corresponding compartment of the diner's multi-compartment plate. During dispensing, the system controls the robotic arm to move directly above the target compartment, at a height of 5 to 10 centimeters from the bottom of the compartment. The grippers then perform a release operation in the reverse order of the gripping motion, with the release speed set to 50% to 70% of the gripping speed to prevent food from splashing. After release, the grippers remain open for 0.5 seconds, and the robotic arm retracts once the dish has been completely removed.
[0055] The food serving module records the completion status of each food serving operation, including dish identification, diner identification, grid number, actual weight picked up, and completion timestamp, for use by the control module and system log. Once a dish has been served to all diners, the food serving module controls the food serving robot to return to its initial position, awaiting the next dish serving instruction.
[0056] Through the above process, the meal distribution module completes the entire meal distribution process from parameter acquisition, clamping execution, weight detection and compensation, rotation positioning, grid determination to delivery operation, realizing accurate and automated distribution of solid dishes.
[0057] The control module is used to dynamically adjust the order of meal distribution by the meal distribution execution module based on the diner's status detected by the sensing module.
[0058] Furthermore, within the control module, the specific steps for dynamically adjusting the meal distribution order in the meal distribution execution module include: Acquire the diners' status information detected by the sensing module; Based on the diners' status information, determine the priority of meal distribution for each diner; Generate a sequence of target diners according to their priority for serving meals, from highest to lowest. The target diners sequence is output to the meal distribution execution module to control the module to perform the meal distribution operation sequentially according to the target diners sequence.
[0059] Furthermore, the steps for determining the food distribution priority for each diner based on their status information specifically include: Get the empty status of the compartments corresponding to the dishes to be served in the multi-compartment plates for each diner; Diners whose grids for the dishes currently to be served have been cleared are designated as the first priority; Diners whose grids for the dishes currently to be served have not been cleared are designated as the second priority; Set the priority level of the first priority to be higher than that of the second priority.
[0060] Specifically, the control module obtains the diner status information detected by the sensing module through the system's internal communication interface. This diner status information is transmitted in the form of a data structure, which includes a diner identifier field, a grid number field, a clearing status field, and a timestamp field. After receiving this information, the control module stores it in a memory buffer for subsequent priority calculations. Based on the diner status information, the control module determines the food distribution priority for each diner. The food distribution priority represents the urgency of the diner's need for food distribution; the higher the priority, the earlier the food distribution service is received. The specific determination method is as follows: The system first obtains the clearing status of the grid corresponding to the dish currently being distributed in the multi-grid for each diner. Let the dish currently being distributed be... Each diner i corresponds to a grid. The designated grid for this dish is now empty. The possible values are as follows: When grid It has been cleared; =0, when the grid It has not been cleared.
[0061] The system categorizes diners into two priority levels based on their cleared status: First priority: For diners with a priority value of 1, their slots have been cleared, indicating that they have finished the previous dish and are ready to receive the next dish; Second priority: For diners with a score of 0, if their grid is not cleared, it indicates that they have not finished eating the previous dish and are not yet suitable to receive the next dish; the system will set the priority level of the first priority to be higher than that of the second priority.
[0062] When multiple diners exist at the same priority level, the system further calculates sub-priority scores. Used to determine the order of precedence within the same level. Sub-priority score. The calculation formula is: ; in, This is the waiting time for the diner since they last received their meal, expressed in seconds, ranging from 0 to 300. The idle time of the corresponding grid for the diner since the clearing status was detected, in seconds, with a value ranging from 0 to 180; α and β are weighting coefficients, determined through experimental calibration, with α=0.6 and β=0.4 being preferred. and The larger the value, the higher the sub-priority score, indicating that the diner should have a higher priority to receive the meal.
[0063] When a child is detected sitting down, the system immediately sets the child's priority to the highest priority, which is higher than the first priority mentioned above. The child's sitting status is determined by a pressure sensor installed on the seat or by a visual recognition module.
[0064] The control module generates a target diner sequence according to the priority of meal distribution, from highest to lowest. Specifically, the system sorts all diners according to the following rules: First priority: children; Second priority: first-priority diners, ranked by sub-priority scores. First priority diners, ranked from highest to lowest; third priority: second priority diners, ranked according to sub-priority scores. Sort from highest to lowest. After sorting, the system generates an ordered list. ,in Identify the highest priority diners. The lowest priority diners are identified by N, where N is the total number of diners.
[0065] The control module outputs the generated target diner sequence to the meal distribution execution module. The output is achieved by transmitting a list of diner identifiers via an internal system communication interface. Upon receiving the target diner sequence, the meal distribution execution module performs the meal distribution operation for each diner in the order specified in the sequence. After completing the meal distribution for each diner, the meal distribution execution module reports the completion status back to the control module. The control module updates the status information accordingly and can dynamically adjust the subsequent sequence based on the real-time detected diner status.
[0066] During the meal distribution process, the control module continuously receives real-time diners' status information from the sensing module and dynamically adjusts the priority and sequence order of diners who have not yet completed their meal distribution based on the updated status. Specifically, when a diner's cell is cleared, the control module recalculates that diner's priority and updates the order of the remaining diners in the target diners' sequence. The dynamic update uses an incremental algorithm, adjusting only the diners whose status has changed and their adjacent positions to reduce computational overhead.
[0067] The triggering conditions for dynamic updates include: when it is detected that the cell corresponding to the current dish to be served for any diner changes from not cleared to cleared, the diner's priority is dynamically adjusted to the first priority and inserted into the appropriate position in the current sequence; when it is detected that any diner leaves the seat, the diner is removed from the target diner sequence, the serving of food for the diner is paused until the diner is detected to return to the seated state and then re-added to the sequence; when it is detected that the cells corresponding to the current dishes to be served for all diners are not cleared, the priority of all diners is set to the same level, and the sequence is generated according to the order of the diners' positions.
[0068] Once the serving module completes serving a dish to all diners, the control module resets the priority status of all diners to prepare for the next dish's serving order. For dishes that require multiple servings, the control module reassesses the diners' status after each serving to ensure the serving order always matches the diners' actual needs.
[0069] Through the above process, the control module realizes dynamic and intelligent scheduling of the order of serving meals, so that the pace of serving meals is synchronized with the actual eating progress of diners, thereby improving the overall dining experience and the efficiency of serving meals.
[0070] Example 2: In existing scenarios, automated food distribution equipment for multi-person dining at a shared table mainly includes two types: electric rotating food counters and food delivery robots. Electric rotating food counters use a rotating surface in the center of the table to allow dishes to pass in front of each diner sequentially. However, this only achieves passive rotation of the food; diners still need to pick food from the communal trays themselves, failing to solve the problem of cross-infection. Food delivery robots, such as Pudu Technology's "Happy Delivery" series and Keenon Robotics' "T series," can transport food from the kitchen to the table, but their function is limited to placing trays on the table; they lack the ability to actively pick food from the communal trays and distribute it to individual utensils. In addition, some canteens have seen fixed automatic food dispensing machines that can dispense standardized food at a fixed location. However, these devices are installed in the kitchen or at the dispensing window, failing to meet the needs of multiple diners at a single table, and are only suitable for single dishes. None of the aforementioned technologies provide a complete solution for actively picking up food from a communal plate and accurately distributing it to each diner's individual utensils in a multi-person dining setting, thus failing to effectively address the risk of cross-infection during shared meals. To solve this problem, this invention provides a centrally rotating robotic automatic food distribution method for multi-person dining tables, the structure of which is as follows: Figure 2 As shown. The specific implementation process of this method is as follows: Acquire and record table configuration information, including the position of the main body of the serving robot, the position of each diner, and the fixed correspondence between the multi-compartment plate and the dishes for each diner; Identify the types of dishes in the public serving trays and match the corresponding picking parameters; Detects the status of diners and the safety status around the main body of the food dispensing robot; The main body of the food-distributing robot is controlled to pick up the target dishes from the public plate according to the picking parameters, and after the picking amount reaches the preset condition, the target dishes are placed into the corresponding grid of the target diners according to a fixed correspondence. The meal distribution order is dynamically adjusted based on the diners' status detected by the sensing module.
[0071] Specifically, the initialization module first acquires and records the table configuration information, including the installation position of the serving robot in the center of the table, the position information of each dining seat distributed around the serving robot, and the unique and fixed correspondence between each compartment of the detachable multi-compartment plate on each dining seat and each dish. Then, the recognition module collects images of the dishes on the shared plates, identifies the dish types using a deep learning model, and matches the corresponding gripping parameters from a preset gripping strategy library. During the serving process, the perception module, on the one hand, uses visual analysis to detect the emptying status of each compartment in each diner's multi-compartment plate in real time to generate diner status information; on the other hand, it uses environmental perception sensors to continuously monitor whether anyone has entered a preset danger zone around the serving robot to generate safety status information. When someone is detected entering a danger zone, the serving operation is immediately paused and an alarm is issued. The serving execution module... The recognition module controls the gripper to move to the target dish and perform the gripping operation based on the gripping parameters matched by the recognition module. The weight of the gripper is detected by the weighing sensor integrated into the gripper and compared with the preset amount. If the weight is insufficient, the gripping is repeated until the preset conditions are met. Then, the main body of the serving robot is rotated to the target diner's position according to the position of each diner. The target grid is determined according to the fixed correspondence between the grid and the dish, and the target dish is placed into the corresponding grid in the multi-grid plate of the target diner. At the same time, the control module determines the first priority of diners whose grid corresponding to the dish to be served has been cleared and the second priority of diners whose grid has not been cleared according to the perception module. The target diner sequence is generated according to the priority from high to low and output to the serving execution module. The serving execution module performs the serving operation for each diner in sequence according to the sequence, thereby realizing the dynamic adaptation of the serving order to the actual dining progress of the diners.
[0072] Example 3: In this embodiment, in order to reduce the number of compartments required for the multi-compartment plate and improve the user experience, the compartments of the multi-compartment plate are not set according to the number of dishes, but are divided according to the flavor characteristics or cooking methods of the dishes.
[0073] Specifically, the "dish-grid binding information" obtained by the system in the initialization module does not bind each dish to a unique grid. Instead, it associates dishes with the same or similar flavor characteristics with the same grid. Here is an example of a specific configuration: The first grid is configured as a spicy dish receiving area, used to receive spicy dishes such as boiled fish, spicy chicken, Mapo tofu, and spicy blood curd; the second grid is configured as a sweet dish receiving area, used to receive sweet dishes such as sweet and sour pork, candied sweet potato, pineapple sweet and sour pork, and honey-glazed char siu; the third grid is configured as a savory dish receiving area, used to receive savory dishes such as steamed sea bass, boiled shrimp, baby bok choy in broth, and crab roe tofu; the fourth grid is configured as a cold dish or snack receiving area, used to receive various cold dishes, appetizers, and fried snacks. With the above configuration, the original requirement of ten compartments for ten dishes can now be met with only three to four compartments. The plate size remains standard, facilitating cleaning and storage, significantly improving user acceptance. During the serving process, the recognition module identifies the type of dish and then queries its flavor category (this can be achieved through a preset dish-flavor mapping table or by direct image recognition). The serving execution module then controls the grippers to place the dish into the corresponding compartment based on the obtained flavor category. When the same compartment needs to receive multiple different dishes, the system places them sequentially according to the serving order. Because the cross-contamination of flavors between dishes of the same type is minimal (e.g., the mixing of broth from spicy dishes does not produce a noticeable odor), this solution greatly improves the practicality of the plate design and user acceptance while ensuring hygiene during serving.
[0074] Example 4: In this embodiment, diners use ordinary plates (no need for multiple compartments or physical fixation), and the food-distributing robot identifies the position of the plates in real time through visual positioning technology to achieve dynamic food distribution.
[0075] The system controls the main body of the food-dispensing robot to rotate 100 degrees (or move to multiple observation positions), acquiring panoramic images of the dining table through depth cameras mounted on the robot's main body. The system runs a pre-trained plate detection model (e.g., an object detection network based on YOLOv8 or Mask R-CNN) to identify the position of each plate in the image and output the bounding box coordinates of each plate. Combining the depth information provided by the depth cameras, the system converts the two-dimensional image coordinates of each plate into three-dimensional spatial coordinates in the robot's base coordinate system, recording the plate position for each diner. The system also analyzes the location of empty areas on each plate through visual recognition. Specifically, the system performs semantic segmentation on the plate images, distinguishing between "occupied areas" (areas with food) and "empty areas" (areas without food), and records the center coordinates and contour information of the empty areas for subsequent delivery.
[0076] During the food serving process, as diners may move their plates, the system continuously updates the position and available space information of each plate at a predetermined frequency (e.g., every 10 seconds). When the system is ready to serve a particular diner, it first queries the latest position and available space coordinates of that diner's plate, then controls the gripper to move above that available space and execute the food delivery operation. To address positioning deviations caused by plate movement, the system employs visual servo control during gripper movement: a small camera is installed at the end of the gripper, which captures images in real time as it approaches the target area. Visual feedback is used to fine-tune the gripper position, ensuring the food is accurately placed within the available space.
[0077] This embodiment is completely independent of the physical fixation of the plate; diners can use any ordinary plate and can even move the plate at any time, with the system automatically adapting through continuous visual tracking. With the continuous development of computer vision and robot control technologies, the positioning accuracy and real-time performance of this embodiment will continue to improve, possessing scalability for future technological evolution.
[0078] It should be noted that this embodiment is not mutually exclusive with the aforementioned embodiments one to three. In actual products, switching between physical fixing mode and visual positioning mode, or supporting both modes simultaneously, can be achieved according to user needs and application scenarios. All of these fall within the protection scope of this invention.
[0079] The visual positioning technology described in this embodiment can be applied to the above-mentioned system as an alternative implementation method for obtaining the location information of diners in the initialization module.
[0080] Example 5: In this embodiment, for large round tables (diameter greater than 2.5 meters, capable of accommodating 12-20 people) or long dining tables (length greater than 3 meters), the main body of the serving robot is equipped with both a rotating mechanism and a moving mechanism to achieve full table coverage.
[0081] In this embodiment, an AGV (Automated Guided Vehicle) chassis is preferably used as the mobility mechanism. Specifically, the main body of the serving robot is equipped with four omnidirectional wheels, preferably Mecanum wheels. Mecanum wheels are a special wheel system capable of omnidirectional movement. Each wheel has multiple small rollers around its perimeter. By controlling the rotation speed and steering combination of the four wheels, the robot body can achieve translation (forward, backward, left, right, and diagonal) and rotation around its own axis in any direction on a plane, without the need for a turning radius, making its movement extremely flexible. The advantages of this design include: First, it does not require any pre-set guide rails or tracks on the dining table, and is directly applicable to dining tables of various shapes and sizes, including round tables, rectangular tables, and oval tables; Second, the robot can autonomously plan its path, move flexibly on the tabletop, and avoid obstacles such as public plates and tableware; Third, it is simple to install, requiring no modification to existing dining tables, and is ready to use immediately after installation.
[0082] In practical applications, multi-person dining tables often come with a large rotating turntable (glass or wooden) for placing communal dishes. In this embodiment, the main body of the food-distributing robot moves independently; its base is not fixed to the turntable but is placed directly on the table or the turntable surface. The robot moves autonomously using omnidirectional wheels, completely decoupled from the movement of the turntable. Specifically: when the turntable is stationary, the robot can move freely on the turntable surface or the table to perform food distribution; when the turntable rotates automatically, the robot can perceive its own position changes in real time through a visual positioning system, autonomously adjust its movement path, or choose to pause its movement while the turntable is rotating and resume operation after the turntable stops; the robot uses a bottom-facing camera to read artificial markings (QR codes or reflective marks) set on the table or the edge of the turntable for positioning and navigation, and its movement path can actively avoid obstacles such as communal plates and utensils on the turntable. Since the robot in this embodiment moves independently and its base is not fixed to the turntable, there are no interference issues such as "the robot passively rotating with the turntable" or "the robot's movement causing the turntable to rotate." The robot's movement and the turntable's movement are independent of each other, each performing its own function without affecting the other.
[0083] To achieve precise movement and food distribution, the robot employs visual positioning and navigation technology. Specifically, multiple artificial markers, such as QR codes, April Tags, or reflective markings, are placed along the edges of the table or turntable. A downward-facing camera is mounted on the robot's bottom, which reads these markers in real time during movement. By calculating the position and orientation of the markers in the image, the robot's precise position and orientation within the table's coordinate system are determined. Simultaneously, a depth camera or LiDAR is mounted on the robot's main body to perceive the surrounding environment and identify the positions of shared plates, utensils, obstacles, and diners' plates. By fusing data from multiple sensors, the robot can construct a local map of the table in real time, plan the optimal movement path, and dynamically avoid obstacles during movement.
[0084] The robot's moving and rotating mechanisms work in tandem, forming a "movement-rotation-movement-rotation" step-by-step working pattern: First, the robot moves to a working position near the first set of dining seats via the moving mechanism; second, the robot rotates around its own axis via the rotating mechanism, aligning its grippers with the diners' plates within a certain angle range around the working position to perform the food dispensing operation; third, after completing the food dispensing in that area, the robot moves to a working position near the next set of dining seats via the moving mechanism; fourth, steps two and three are repeated until all dining seats are covered. This step-by-step working pattern allows for full coverage of large dining tables without increasing the length of the robotic arm.
[0085] The movement function in this embodiment is optional and can be flexibly configured according to the actual table size. Specifically: on small tables for 4-6 people or round tables with a small diameter, the robot can omit the movement mechanism or disable the movement function, and rely solely on the rotation mechanism to complete the food distribution for the entire table, thereby reducing costs and simplifying control; on large tables for 10-20 people or long tables, the movement function is enabled, and the robot completes the food distribution area by area through "stepping movement + rotation"; for tables with a built-in turntable, the robot can choose to move directly on the surface of the turntable or move on the tabletop, and neither method will interfere with the turntable.
[0086] This embodiment utilizes an omnidirectional wheeled AGV chassis as its mobility mechanism, enabling the robot to move flexibly in any direction on the dining table without the need for pre-set guide rails, making it suitable for dining tables of various shapes and sizes. Furthermore, because the robot moves independently, its base is not fixed to the turntable, avoiding motion interference with the existing turntable. The robot autonomously plans its path and dynamically avoids obstacles using visual positioning and navigation technology, achieving full-scene coverage from small to large dining tables, and from tables without turntables to tables with turntables.
[0087] Those skilled in the art will understand that the specific implementation of the mobile mechanism is not limited to Mecanum wheels. Any wheel system structure (such as omnidirectional wheels, caster wheels, steering wheels, etc.) or tracked structure capable of omnidirectional movement falls within the protection scope of this invention. Similarly, the positioning and navigation methods are not limited to QR code identification. Any technology capable of enabling autonomous robot positioning (such as laser SLAM, visual SLAM, UWB positioning, etc.) can be applied to this embodiment.
[0088] Example 6: In some practical applications, the central area of a multi-person dining table may be occupied by a large turntable, large communal plates, decorations, or other items, making it impossible to accommodate a base-mounted food-dispensing robot. To solve this problem, this embodiment provides a ceiling-mounted track installation method.
[0089] The main body of the serving robot is suspended from the ceiling directly above the dining table via a suspension mechanism. Specifically, a circular or linear track is fixedly installed on the ceiling, the shape of which matches the shape of the dining table (e.g., a circular track for a round table, and a linear or rectangular track for a long table). A sliding mechanism (such as a slider, roller, or rack and pinion mechanism) is located on the top of the robot body and works in conjunction with the track, driven by a servo motor or stepper motor, enabling the robot body to move along the track.
[0090] The motion mechanism of the ceiling-mounted serving robot includes: a moving mechanism: moving along a track to adjust the robot's position over a wide range above the dining table. The moving mechanism can be driven by a synchronous belt, lead screw, or rack and pinion. A lifting mechanism: connected to the moving mechanism and the robot body, used to drive the robot to move vertically up and down to approach or move away from the plates on the table surface. The lifting mechanism can be an electric push rod, lead screw lift, or scissor lift structure. A rotating mechanism: located on the robot body, used to drive the gripper to rotate around its own axis to achieve coverage in all circumferential directions. An optional telescopic mechanism: located between the rotating mechanism and the gripper, used to extend or retract horizontally to expand the gripper's coverage area.
[0091] The food distribution process of the ceiling-mounted track-type serving robot is as follows: Initialization phase: The system scans the dining table using visual sensors to identify the location of each seat, the location of each diner's plate, and the location of the communal plate, establishing a table coordinate system. Movement phase: Based on the location of the target diner, the system controls the movement mechanism to drive the robot body along the track to the area directly above the diner. Lifting and positioning phase: The system controls the lifting mechanism to lower the robot body to a suitable height, while simultaneously using visual sensors to accurately locate the empty area of the target plate. Grabbing and placing phase: The robot body adjusts the gripper posture through a rotation and extension mechanism, grabs the target dish from the communal plate, and then moves it above the target diner's plate to place the dish into the empty area. Reset phase: After completing the food distribution, the lifting mechanism raises the robot body to a safe height, and the movement mechanism moves it to the standby position or the next target position.
[0092] The ceiling-mounted, track-mounted food-dispensing robot is also equipped with safety features. The robot is equipped with lidar or ultrasonic sensors to detect people or obstacles below. When a person is detected entering a danger zone, the system immediately pauses movement and food dispensing operations and issues a voice warning. The lifting mechanism is equipped with an anti-fall device to ensure the robot will not fall in the event of a power outage or malfunction.
[0093] This embodiment solves the problem of insufficient installation space in the center of the dining table by mounting the main body of the serving robot on a track above the table. The robot can cover the entire dining area through multi-degree-of-freedom movements such as moving, lifting, rotating, and extending. Simultaneously, since the robot is suspended from the ceiling, it does not occupy any tabletop space, does not affect diners' normal eating, and does not interfere with items such as the turntable or communal serving dishes on the table. This embodiment complements the aforementioned Embodiment Five (AGV omnidirectional wheel type): when there is space in the center of the table and the user does not wish to modify the ceiling, the tabletop moving solution of Embodiment Five can be selected; when there is no space in the center of the table or the user wishes to completely avoid occupying tabletop space, the ceiling-mounted track solution of this embodiment can be selected. Both solutions can be flexibly selected according to the actual application scenario.
[0094] Those skilled in the art will understand that the specific shape of the track, the specific driving method of the moving mechanism, and the specific implementation method of the lifting mechanism are not limited to the above examples. Any technical means that can enable the main body of the serving robot to move and lift above the dining table falls within the protection scope of this invention.
[0095] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A centrally rotating robotic automatic food dispensing system for multi-person dining tables, characterized in that, Includes the following modules: The initialization module is used to acquire and record table configuration information, which includes the position of the main body of the serving robot, the position of each diner, and the fixed correspondence between the grids of the multi-compartment plate corresponding to each diner and the dishes. The recognition module is used to identify the types of dishes in the public serving trays and match the corresponding picking parameters; The sensing module is used to detect the state of the diners and the safety status around the main body of the food dispensing robot; The food serving module is used to control the main body of the food serving robot to pick up the target dish from the public plate according to the picking parameters, and after the picking amount reaches the preset condition, to put the target dish into the grid corresponding to the target diner according to the fixed correspondence. The control module is used to dynamically adjust the order of meal distribution by the meal distribution execution module based on the diner's status detected by the sensing module.
2. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 1, characterized in that, In the initialization module, the steps for obtaining and recording table configuration information specifically include: Obtain table layout information, including the working position of the main body of the food-serving robot in the central area of the table; Obtain the grid layout information of the multi-compartment plate set at each dining seat, wherein the grid layout information includes the relative position of each compartment in the multi-compartment plate; Obtain the binding information between dishes and grids, wherein the binding information is used to establish a fixed correspondence between each dish and a grid on a dining seat; The table layout information, the grid layout information, and the binding information are associated and stored as the table configuration information.
3. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 1, characterized in that, In the recognition module, the steps of identifying the types of dishes on the public serving tray and matching the corresponding picking parameters specifically include: Collect images of food items from public dining trays; Image recognition is performed on the food images to identify the type of each dish in the public serving dish; Based on the identified dish type, the corresponding clamping parameters are matched from the preset clamping strategy library; The matched gripping parameters are output to the food serving execution module, which then controls the main body of the food serving robot to perform gripping operations.
4. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 3, characterized in that, The step of matching the corresponding clamping parameters from the preset clamping strategy library based on the identified dish type specifically includes: Obtain the identified dish type and use the dish type as the query key value; Based on the query key value, perform a matching query in the preset pinch strategy library; When a match is successful, extract the clamping parameters corresponding to the dish type; When a match fails, the default clamping parameters are loaded, and a prompt message is generated to request the user to confirm or supplement the clamping parameters corresponding to the dish type.
5. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 1, characterized in that, In the perception module, the steps of detecting the diner's state and the safety status around the main body of the food dispensing robot specifically include: Collect images of the status of the multi-compartment plates for each diner; Image analysis is performed on the plate status image to detect the emptying status of each compartment and generate diner status information; Collect environmental perception data around the main body of the food dispensing robot; Based on the environmental perception data, the system detects whether any personnel have entered the preset danger zone around the main body of the food dispensing robot and generates safety status information. The system outputs the diner's status information to the control module and the safety status information to the meal distribution execution module, so as to control the meal distribution execution module to suspend the meal distribution operation when a person enters a preset danger area.
6. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 1, characterized in that, In the meal distribution module, the step of placing the target dish into the grid corresponding to the target diner according to the fixed correspondence specifically includes: Obtain the clamping parameters matched by the recognition module; The gripper of the food dispensing robot is controlled to move to the target dish on the public plate according to the gripping parameters, and the gripping operation is performed. After the gripping operation is completed, check the gripping weight; Determine whether the clamping weight has reached the preset condition. If not, repeat the clamping operation until the clamping weight reaches the preset condition. When the gripping weight reaches the preset condition, the main body of the food dispensing robot is controlled to rotate to the target diner's position according to the position of each diner; Based on the fixed correspondence between grids and dishes, determine the target grid corresponding to the target dish; The gripper of the food dispensing robot is controlled to place the target dish into the corresponding target compartment of the multi-compartment plate of the target diner.
7. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 1, characterized in that, In the control module, the step of dynamically adjusting the meal distribution order of the meal distribution execution module specifically includes: Obtain the diner's status information detected by the sensing module; Based on the diners' status information, determine the priority of meal distribution for each diner; Generate a target diner sequence according to the order of meal distribution priority from high to low; The target diners sequence is output to the meal distribution execution module to control the meal distribution execution module to perform the meal distribution operation sequentially according to the target diners sequence.
8. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 1, characterized in that, The step of determining the meal distribution priority for each diner based on the diner's status information specifically includes: Get the empty status of the compartments corresponding to the dishes to be served in the multi-compartment plates for each diner; Diners whose grids corresponding to the dishes to be served have been cleared are designated as first priority; Diners whose grid corresponding to the currently unserved dishes are not cleared are designated as the second priority; Set the priority level of the first priority to be higher than that of the second priority.
9. The central rotating robotic automatic food dispensing system for multi-person dining tables according to claim 1, characterized in that, The main body of the food dispensing robot is equipped with a motion mechanism, which includes: A rotating mechanism is used to drive the main body of the food dispensing robot to rotate around its own axis; A moving mechanism is used to drive the main body of the food-dispensing robot to move in the central area of the dining table; The moving mechanism and the rotating mechanism work together to enable the main body of the food-dispensing robot to perform a rotating food-dispensing operation at the moved position.
10. A method for automatic food distribution using a central rotating robot at a multi-person dining table, characterized in that: The method for the central rotating robotic automatic food distribution system for multi-person dining tables according to any one of claims 1-9 comprises: Acquire and record table configuration information, which includes the position of the main body of the serving robot, the position of each diner, and the fixed correspondence between the grids of the multi-compartment plate corresponding to each diner and the dishes. Identify the types of dishes in the public serving trays and match the corresponding pick-up parameters; Detect the status of diners and the safety status around the main body of the food dispensing robot; The main body of the food dispensing robot is controlled to pick up the target dish from the public plate according to the picking parameters, and after the picking amount reaches the preset condition, the target dish is placed into the grid corresponding to the target diner according to the fixed correspondence. The meal distribution order of the meal distribution execution module is dynamically adjusted based on the diner's status detected by the sensing module.