High-flexibility unmanned coffee robot system based on visual positioning

Abstract

The invention discloses a high-flexibility unmanned coffee robot system based on visual localization, and relates to the technical field of mechanical automation, and the high-flexibility unmanned coffee robot system comprises a user interaction unit, a visual localization unit and a mechanical arm unit. The system can accurately capture environment images under various illumination conditions, and data preprocessing is performed through the image acquisition module, so that the image quality is improved. The feature extraction module extracts useful features from the preprocessed image, and the positioning analysis module calculates the positions and postures of the cameras at different time points through an SLAM algorithm by using multi-view image data captured by the plurality of cameras, and constructs a three-dimensional map of the environment; the combination of the multi-modal sensing and advanced image processing technology significantly improves the positioning precision and adaptability of the unmanned coffee robot in a complex environment.

Description

Technical Field

[0001] The present invention belongs to the technical field of mechanical automation, and in particular relates to a highly flexible unmanned coffee robot system based on visual positioning. Background Art

[0002] With the development of science and technology, unmanned coffee robots are gradually becoming a reality. This highly flexible unmanned coffee robot system based on visual positioning realizes the automated coffee making process through the collaborative work of the user interaction unit, the visual positioning unit and the robotic arm unit. However, in practical applications, traditional unmanned coffee robots often have the following problems: the existing system has limited positioning and recognition capabilities in complex environments, especially in the case of light changes or occlusions, and it is difficult to maintain stable and efficient operation. In addition, the device fails to effectively integrate the visual system and cannot autonomously identify and locate coffee cups or other accessories, which limits the independent operation capability of the device and affects the flexibility and accuracy of production. Therefore, we propose a highly flexible unmanned coffee robot system based on visual positioning. Summary of the invention

[0003] The purpose of the present invention is to provide a highly flexible unmanned coffee robot system based on visual positioning. By combining a high-definition camera and an infrared camera, the system can accurately capture environmental images under various lighting conditions, and perform data preprocessing through an image acquisition module to improve image quality. The feature extraction module extracts useful features from the preprocessed image, and the positioning analysis module uses the multi-view image data captured by multiple cameras to calculate the position and posture of the camera at different time points through the SLAM algorithm to construct a three-dimensional map of the environment. This combination of multimodal sensing and advanced image processing technology significantly improves the positioning accuracy and adaptability of the unmanned coffee robot in complex environments, and solves the problem that the existing system has limited positioning and recognition capabilities in complex environments, especially in the case of light changes or occlusions, and it is difficult to maintain stable and efficient operation. In addition, the device fails to effectively integrate the visual system and cannot autonomously identify and locate coffee cups or other accessories, which limits the independent operation capability of the device and affects the flexibility and accuracy of production.

[0004] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0005] The present invention is a highly flexible unmanned coffee robot system based on visual positioning, comprising a user interaction unit, a visual positioning unit and a mechanical arm unit;

[0006] The visual positioning unit includes a camera array, an image acquisition module, a feature extraction module, a positioning analysis module and a communication module. The camera array includes a high-definition camera and an infrared camera; the camera array is unidirectionally connected to the image acquisition module; the image acquisition module is unidirectionally connected to the feature extraction module; the feature extraction module is unidirectionally connected to the positioning analysis module; the positioning analysis module is unidirectionally connected to the communication module; the high-definition camera is responsible for acquiring high-resolution images of the environment, providing clear visual information, and capturing detailed features; the infrared camera is responsible for working in low-light environments and identifying target positions by detecting infrared radiation; it can make up for the shortcomings of high-definition cameras in dark environments and ensure that the unmanned coffee robot can be accurately positioned under various lighting conditions; the image acquisition module is responsible for capturing image information of objects in real time through a combination of high-definition cameras and infrared cameras, and performing data preprocessing, such as filtering, denoising, and image enhancement operations to improve image quality. The image quality is improved and the complexity of subsequent processing is reduced. These image information is the basis for subsequent feature extraction and position calculation processing; the feature extraction module is responsible for extracting features useful for object recognition and positioning from the preprocessed image. These features may include contour features, color features, and shape features, which can reflect the essential attributes and spatial position information of the object. After feature extraction, feature selection and optimization can be used to retain the most useful features for recognition and positioning, while removing redundant and noise features, thereby improving the accuracy and efficiency of the system; the positioning analysis module is responsible for using multiple cameras to capture multi-view image data in the working environment. By analyzing the feature matching relationship between multi-view images, the SLAM algorithm can calculate the position and posture of the camera at different time points, and gradually build a three-dimensional map of the environment. Once the three-dimensional map and the image data of the current frame are obtained, the PnP problem solving method can be used to calculate the position and direction of the camera relative to the known landmarks;

[0007] Its nonlinear optimization method:

[0008] Construct a least squares problem and solve it iteratively, namely Bundle Adjustment (BA). This method regards both the camera pose and the spatial point position as optimization variables and optimizes them together. The reprojection error formula solved by BA is expressed as:

[0009]

[0010] Among them, P i is the pixel coordinate of the i-th feature point, P iis the corresponding three-dimensional world point coordinate, K is the camera intrinsic parameter matrix, and [R|t] is the camera extrinsic parameter matrix; by minimizing the reprojection error, the optimal camera pose and spatial point position can be iteratively solved; the communication module is responsible for sending corresponding instructions to the controller to control the operating status of the device or adjust the working parameters of the device according to the requirements of the controller and system design.

[0011] As a preferred technical solution, the user interaction unit includes a user feedback module, a display screen, an order management module, a personalized customization module, a user payment module and a wireless communication module; the display screen is unidirectionally connected to the user feedback module and the order management module respectively; the order management module is unidirectionally connected to the personalized customization module; the personalized customization module is unidirectionally connected to the user payment module; the user payment module is unidirectionally connected to the wireless communication module.

[0012] As a preferred technical solution, the display screen is responsible for providing customers with a visual interface for interaction between customers and the robot, allowing users to operate through a touch screen or display interface. Users can choose coffee types, customize flavors, and pay on the display screen to realize self-service ordering and checkout functions. The display screen can display information such as coffee making progress and remaining time in real time, allowing users to understand the order status at any time. At the same time, it can also display the working status and fault prompts of the coffee robot, so that maintenance personnel can find and solve problems in time; the order management module is responsible for automating the order processing process, including order entry, confirmation and production, real-time tracking of order status, ensuring the transparency and timeliness of production, and real-time updating of inventory information to ensure the accuracy of remaining materials during order processing and avoid material shortages or surpluses.

[0013] As a preferred technical solution, the personalized customization module is responsible for selecting the parameters of the coffee beans, grinding coarseness, coffee temperature and milk foam ratio that the user likes, and can also select the coffee capacity, latte art pattern and sugar content to meet the diverse needs of different users and improve user satisfaction and loyalty; the user payment module is responsible for allowing users to perform self-service ordering and checkout operations through a touch screen or display interface. Users can select the type of coffee and customize the flavor on the display screen and complete the payment process. This self-service method is convenient and fast, and can be made after charging to prevent customers from escaping the order, and it reduces manual intervention and waiting time, thereby improving overall operational efficiency; the wireless communication module is responsible for inputting instructions according to the type of coffee selected by the customer and the personalized selection, and transmitting instructions according to the different production processes of different coffees and different flavors entered, so as to perform mechanized operations according to the instructions; the user feedback module collects customer feedback at the peak value for continuous improvement and optimization of the system.

[0014] As a preferred technical solution, the robotic arm unit includes a PLC controller, a robotic arm control module, a motor driver, an end effector, a multi-degree-of-freedom robotic arm and a quilt grabber; the communication module is unidirectionally connected to the PLC controller; the wireless communication module is respectively connected to the visual positioning unit and the robotic arm control module WSN network; the PLC controller and the robotic arm control module are respectively unidirectionally connected to the motor driver; the motor driver is respectively unidirectionally connected to the end effector and the multi-degree-of-freedom robotic arm; the end effector is unidirectionally connected to the cup grabber.

[0015] As a preferred technical solution, the PLC controller is responsible for receiving signals from the positioning analysis module, and accurately controlling the movements of the robotic arm based on these signals, including the movement, grabbing and placing of objects by the robotic arm. Through the precise control of the PLC controller, the robotic arm can accurately perform various complex tasks; the robotic arm control module is responsible for receiving signal inputs from the order management module and the personalized customization module, and through a large amount of model training, the robotic arm control module performs different instruction transmissions, thereby performing subsequent robotic arm operations according to the instructions, thereby performing different instruction operations according to different coffee making; the motor driver is responsible for receiving signals from the PLC controller and the robotic arm control module, and inputting electrical signals based on these signals, thereby accurately controlling the movement, grabbing and placing of objects by the robotic arm.

[0016] As a preferred technical solution, the end effector is responsible for adjusting the position and controlling the posture of the object through the control of the robotic arm, which means that no matter where the object is placed, the end effector can accurately adjust its position and angle for subsequent operations; the multi-degree-of-freedom robotic arm is responsible for accurately manipulating the various components of the coffee machine according to the input command signal, and can easily reach different positions, whether high or narrow spaces, to complete operations such as taking cups, adding ingredients, stirring, and making latte art and delivering coffee. It usually has six or more degrees of freedom, allowing it to move and position accurately in three-dimensional space; the cup gripper is usually at the tail end of the end effector, and can accurately grasp and place various objects, such as coffee cups, kettles and other tools. This function enables the unmanned coffee robot to automatically complete the entire process from taking objects to making coffee, improving efficiency and accuracy.

[0017] The present invention has the following beneficial effects:

[0018] By combining a high-definition camera and an infrared camera, the system can accurately capture environmental images under various lighting conditions, and perform data preprocessing through an image acquisition module to improve image quality. The feature extraction module extracts useful features from the preprocessed image, while the positioning analysis module uses multi-view image data captured by multiple cameras to calculate the position and posture of the camera at different time points through the SLAM algorithm to construct a three-dimensional map of the environment. This combination of multimodal sensing and advanced image processing technology significantly improves the positioning accuracy and adaptability of the unmanned coffee robot in complex environments.

[0019] The present invention allows customers to directly interact with the robot through a touch screen or display interface through the design of a user interaction unit, select coffee types, customize flavors and complete payment, thereby realizing self-service ordering and checkout functions. The display screen displays the coffee making progress and remaining time in real time, allowing users to understand the order status at any time. In addition, the personalized customization module allows users to adjust the coffee bean type, grinding coarseness, and coffee temperature parameters according to their preferences, providing a more personalized service experience. These functions not only improve user convenience and satisfaction, but also enhance the human-computer interaction experience.

[0020] The high flexibility and precise control capability of the robotic arm unit of the present invention enable the unmanned coffee robot to efficiently complete the entire process from picking up objects to making coffee. The PLC controller accurately controls the movements of the robotic arm according to the signal of the positioning analysis module, including moving, grabbing and placing objects. The multi-degree-of-freedom robotic arm can easily reach different positions, whether high up or in narrow spaces, to complete complex coffee-making tasks. The design of the end effector and cup gripper ensures accurate grabbing and placement of objects, reduces human errors and operation time. Overall, the application of these technologies has significantly improved the operating efficiency and automation level of the unmanned coffee robot, reduced labor costs and improved productivity.

[0021] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0023] Figure 1 This is a flow chart of a highly flexible unmanned coffee robot system based on visual positioning according to the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1 As shown, the present invention is a highly flexible unmanned coffee robot system based on visual positioning, including a user interaction unit, a visual positioning unit and a mechanical arm unit;

[0026] The visual positioning unit includes a camera array, an image acquisition module, a feature extraction module, a positioning analysis module and a communication module. The camera array includes a high-definition camera and an infrared camera; the camera array is unidirectionally connected to the image acquisition module; the image acquisition module is unidirectionally connected to the feature extraction module; the feature extraction module is unidirectionally connected to the positioning analysis module; the positioning analysis module is unidirectionally connected to the communication module; the high-definition camera is responsible for acquiring high-resolution images of the environment, providing clear visual information, and capturing detailed features; the infrared camera is responsible for working in low-light environments and identifying the target position by detecting infrared radiation; it can make up for the shortcomings of high-definition cameras in dark environments and ensure that the unmanned coffee robot can be accurately positioned under various lighting conditions; the image acquisition module is responsible for capturing the image information of objects in real time through a combination of high-definition cameras and infrared cameras, and performing data preprocessing, such as filtering, denoising, and image enhancement operations, to improve image quality and reduce post-processing. The complexity of subsequent processing, these image information is the basis for subsequent feature extraction and position calculation processing; the feature extraction module is responsible for extracting features useful for object recognition and positioning from the preprocessed image, these features may include contour features, color features, shape features, they can reflect the essential attributes and spatial position information of the object, after feature extraction, through feature selection and optimization, the most useful features for recognition and positioning can be retained, while removing redundant and noise features, thereby improving the accuracy and efficiency of the system; the positioning analysis module is responsible for using multiple cameras to capture multi-view image data in the working environment, by analyzing the feature matching relationship between multi-view images, the SLAM algorithm can calculate the position and posture of the camera at different time points, and gradually build a three-dimensional map of the environment, once the three-dimensional map and the image data of the current frame are available, the PnP problem solving method can be used to calculate the position and direction of the camera relative to the known landmarks;

[0027] Its nonlinear optimization method: construct a least squares problem and solve it iteratively, namely Bundle Adjustment (BA). This method regards both the camera pose and the spatial point position as optimization variables and optimizes them together; the reprojection error formula solved by BA is expressed as:

[0028]

[0029] Among them, P i is the pixel coordinate of the i-th feature point, P i is the corresponding three-dimensional world point coordinate, K is the camera intrinsic parameter matrix, and [R|t] is the camera extrinsic parameter matrix; by minimizing the reprojection error, the optimal camera pose and spatial point position can be iteratively solved; the communication module is responsible for sending corresponding instructions to the controller to control the operating status of the device or adjust the working parameters of the device according to the requirements of the controller and system design.

[0030] The user interaction unit includes a user feedback module, a display screen, an order management module, a personalized customization module, a user payment module and a wireless communication module; the display screen is connected to the user feedback module and the order management module in one direction; the order management module is connected to the personalized customization module in one direction; the personalized customization module is connected to the user payment module in one direction; the user payment module is connected to the wireless communication module in one direction; the display screen is responsible for providing customers with a visual interface for interaction between customers and robots, allowing users to operate through a touch screen or display interface. Users can choose coffee types, customize flavors, and pay on the display screen to realize self-service ordering and checkout functions. The display screen can display information such as coffee making progress and remaining time in real time, so that users can understand the order status at any time. At the same time, it can also display the working status and fault prompts of the coffee robot, so that maintenance personnel can find and solve problems in time; the order management module is responsible for automating the order processing process, including order entry, confirmation and production, real-time tracking of order status, ensuring the transparency and timeliness of production, and real-time updating of inventory information to ensure the accuracy of remaining materials during order processing to avoid shortages or surpluses of materials; the personalized customization module is responsible for selecting the parameters of coffee beans, grinding coarseness, coffee temperature and milk foam ratio according to their own preferences, and can also choose the capacity of coffee, pull The coffee beans are made from natural coffee leaves, with a variety of patterns and sugar levels to meet the diverse needs of different users and improve user satisfaction and loyalty; the user payment module is responsible for allowing users to order and check out by themselves through a touch screen or display interface. Users can choose the type of coffee and customize the flavor on the display screen and complete the payment process. This self-service method is convenient and fast, and can be made after charging to prevent customers from running away from the order. It also reduces manual intervention and waiting time, and improves overall operational efficiency; the wireless communication module is responsible for inputting instructions based on the type of coffee selected by the customer and personalized choices, and transmitting instructions based on the different production processes of different coffees and different flavors entered, so as to perform mechanized operations according to the instructions; the user feedback module collects customer feedback at the peak value for continuous improvement and optimization of the system.

[0031] The robotic arm unit includes a PLC controller, a robotic arm control module, a motor driver, an end effector, a multi-degree-of-freedom robotic arm and a quilt grabber; the communication module is unidirectionally connected to the PLC controller; the wireless communication module is respectively connected to the visual positioning unit and the robotic arm control module WSN network; the PLC controller and the robotic arm control module are respectively unidirectionally connected to the motor driver; the motor driver is respectively unidirectionally connected to the end effector and the multi-degree-of-freedom robotic arm; the end effector is unidirectionally connected to the cup grabber; the PLC controller is responsible for receiving signals from the positioning analysis module and accurately controlling the movements of the robotic arm according to these signals, including the movement, grabbing and placing of objects by the robotic arm. Through the precise control of the PLC controller, the robotic arm can accurately perform various complex tasks; the robotic arm control module is responsible for receiving signal inputs from the order management module and the personalized customization module. Through a large amount of model training, the robotic arm control module transmits different instructions, thereby performing subsequent robotic arm operations according to the instructions, thereby making different coffees according to different conditions. The motor driver is responsible for receiving signals from the PLC controller and the robot control module, and inputting electrical signals based on these signals, so as to accurately control the movement, grabbing and placing of objects by the robot arm; the end effector is responsible for the position adjustment and posture control of objects through the control of the robot arm, which means that no matter where the object is placed, the end effector can accurately adjust its position and angle for subsequent operations; the multi-degree-of-freedom robot arm is responsible for accurately manipulating the various components of the coffee machine according to the input command signals, and can easily reach different positions, whether high or narrow spaces, to complete operations such as taking cups, adding ingredients, stirring, and drawing and delivering coffee. It usually has six or more degrees of freedom, allowing it to move and position accurately in three-dimensional space; the cup gripper is usually at the tail end of the end effector, and can accurately grab and place various objects, such as coffee cups, kettles and other tools. This function enables the unmanned coffee robot to automatically complete the entire process from picking up objects to making coffee, improving efficiency and accuracy.

[0032] A specific application of this embodiment is: the user interactively selects the type of coffee and customized flavors through the display screen and completes the payment, the order management module automatically processes the order and updates the status in real time, the personalized customization module adjusts the production parameters according to the customer's choice, so as to select the desired coffee flavor and latte art pattern, the wireless communication module is responsible for inputting the production instructions of different coffees, the visual positioning unit captures the environmental image through the camera array, the high-definition camera provides high-resolution images to capture detailed features, the infrared camera works in a low-light environment to identify the target position, the image acquisition module performs data preprocessing to improve the image quality, the feature extraction module extracts useful features such as contour, color and shape features from the preprocessed image, and the positioning analysis module uses multi-view image data and SLAM algorithm to calculate the camera position and posture to construct a three-dimensional map Figure 1. The PnP problem solving method is used to calculate the position and direction of the camera relative to the known landmarks. The communication module sends the customer's order information to the PLC controller. The PLC controller receives the signal from the positioning analysis module to accurately control the actions of the robotic arm, including moving, grabbing and placing items. The robotic arm control module transmits instructions based on the signal input from the order management module and the personalized customization module. The motor driver controls the movement and operation of the robotic arm. The end effector adjusts the position and posture of the item. The multi-degree-of-freedom robotic arm manipulates the various components of the coffee machine to complete the operations of taking cups, adding ingredients, stirring, latte art and delivering coffee. The cup gripper accurately grabs and places coffee cups and kettle tools at the tail end of the end effector, thereby accurately making coffee. The user feedback module collects customer feedback for continuous improvement and optimization of the system.

[0033] It is worth noting that in the above system embodiment, the various units included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0034] In addition, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiments can be completed by instructing related hardware through a program, and the corresponding program can be stored in a computer-readable storage medium.

[0035] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A highly flexible unmanned coffee robot system based on visual positioning, comprising a user interaction unit, a visual positioning unit and a robotic arm unit; characterized in that: The visual positioning unit includes a camera array, an image acquisition module, a feature extraction module, a positioning analysis module and a communication module. The camera array includes a high-definition camera and an infrared camera; the camera array is unidirectionally connected to the image acquisition module; the image acquisition module is unidirectionally connected to the feature extraction module; the feature extraction module is unidirectionally connected to the positioning analysis module; the positioning analysis module is unidirectionally connected to the communication module; The high-definition camera is responsible for collecting high-resolution images of the environment, providing clear visual information, and capturing detailed features; The infrared camera is responsible for working in low-light environments and identifying the target position by detecting infrared radiation; it can make up for the shortcomings of high-definition cameras in dark environments and ensure that the unmanned coffee robot can be accurately positioned under various lighting conditions; the image acquisition module is responsible for capturing the image information of the object in real time through the combination of high-definition cameras and infrared cameras, and performing data preprocessing, such as filtering, denoising, and image enhancement operations, to improve image quality and reduce the complexity of subsequent processing. These image information are the basis for subsequent feature extraction and position calculation processing; the feature extraction module is responsible for extracting features useful for object recognition and positioning from the preprocessed image. These features may include contour features, color features, and shape features, which can reflect the essential attributes and spatial position information of the object. After feature extraction, through feature selection and optimization, the most useful features for recognition and positioning can be retained, while removing redundant and noise features; The positioning analysis module is responsible for using multiple cameras to capture multi-view image data in the working environment. By analyzing the feature matching relationship between the multi-view images, the SLAM algorithm can calculate the position and posture of the camera at different time points and gradually build a three-dimensional map of the environment. Once the three-dimensional map and the image data of the current frame are available, the PnP problem solving method can be used to calculate the position and direction of the camera relative to the known landmarks. Its nonlinear optimization method: Construct a least squares problem and solve it iteratively, namely Bundle Adjustment (BA). This method regards both the camera pose and the spatial point position as optimization variables and optimizes them together. The reprojection error formula solved by BA is expressed as: Among them, P i is the pixel coordinate of the i-th feature point, P i is the corresponding 3D world point coordinate, K is the camera intrinsic parameter matrix, and [R|t] is the camera extrinsic parameter matrix. By minimizing the reprojection error, the optimal camera pose and spatial point position can be iteratively solved. The communication module is responsible for sending corresponding instructions to the controller to control the operating status of the device or adjust the working parameters of the device according to the requirements of the controller and system design.

2. The highly flexible unmanned coffee robot system based on visual positioning according to claim 1, characterized in that: The user interaction unit includes a user feedback module, a display screen, an order management module, a personalized customization module, a user payment module and a wireless communication module; the display screen is unidirectionally connected to the user feedback module and the order management module respectively; the order management module is unidirectionally connected to the personalized customization module; the personalized customization module is unidirectionally connected to the user payment module; the user payment module is unidirectionally connected to the wireless communication module.

3. The highly flexible unmanned coffee robot system based on visual positioning according to claim 2 is characterized in that: The display screen is responsible for providing customers with a visual interface for interaction between customers and the robot, allowing users to operate through a touch screen or display interface. Users can choose coffee types, customize flavors, and pay on the display screen to realize self-service ordering and checkout functions. The display screen can display information such as coffee making progress and remaining time in real time, allowing users to understand the order status at any time. At the same time, it can also display the working status and fault prompts of the coffee robot; the order management module is responsible for automating the order processing process, including order entry, confirmation and production, real-time tracking of order status, ensuring transparency and timeliness of production, and real-time updating of inventory information to avoid material shortages or surpluses.

4. The highly flexible unmanned coffee robot system based on visual positioning according to claim 2 is characterized in that: The personalized customization module is responsible for selecting the parameters of the coffee bean type, bean grinding coarseness, coffee temperature and milk foam ratio according to the user's favorite, and can also select the coffee volume, latte art pattern and sugar level; the user payment module is responsible for allowing users to perform self-service ordering and checkout operations through a touch screen or display interface. Users can select coffee types and customize flavors on the display screen and complete the payment process. The coffee can be made after the payment is paid, preventing customers from escaping the order and reducing manual intervention and waiting time; the wireless communication module is responsible for inputting instructions according to the coffee type and personalized selection selected by the customer, and transmitting instructions according to the different production processes of different coffees and different flavors entered, so as to perform mechanized operations according to the instructions; The user feedback module collects customer feedback at the peak value for continuous improvement and optimization of the system.

5. The highly flexible unmanned coffee robot system based on visual positioning according to claim 1, characterized in that: The robotic arm unit includes a PLC controller, a robotic arm control module, a motor driver, an end effector, a multi-degree-of-freedom robotic arm and a quilt grabber; the communication module is unidirectionally connected to the PLC controller; the wireless communication module is respectively connected to the visual positioning unit and the robotic arm control module WSN network; the PLC controller and the robotic arm control module are respectively unidirectionally connected to the motor driver; the motor driver is respectively unidirectionally connected to the end effector and the multi-degree-of-freedom robotic arm; the end effector is unidirectionally connected to the cup grabber.

6. The highly flexible unmanned coffee robot system based on visual positioning according to claim 5, characterized in that: The PLC controller is responsible for receiving signals from the positioning analysis module, and accurately controlling the movements of the robotic arm based on these signals, including the movement, grabbing and placing of objects by the robotic arm. Through the precise control of the PLC controller, the robotic arm can accurately perform various complex tasks; the robotic arm control module is responsible for receiving signal inputs from the order management module and the personalized customization module. Through a large amount of model training, the robotic arm control module transmits different instructions, thereby performing subsequent robotic arm operations according to the instructions, thereby performing different instruction operations according to different coffee making; the motor driver is responsible for receiving signals from the PLC controller and the robotic arm control module, and inputting electrical signals based on these signals, thereby controlling the movement, grabbing and placing of objects by the robotic arm.

7. The highly flexible unmanned coffee robot system based on visual positioning according to claim 5, characterized in that: The end effector is responsible for adjusting the position and controlling the posture of objects through the control of the robotic arm, which means that no matter where the object is placed, the end effector can accurately adjust its position and angle for subsequent operations; the multi-degree-of-freedom robotic arm is responsible for accurately manipulating the various components of the coffee machine according to the input command signal, and can easily reach different positions, whether high or narrow spaces, to complete operations such as taking cups, adding ingredients, stirring, drawing and delivering coffee. It usually has six or more degrees of freedom, allowing it to move and position accurately in three-dimensional space; the cup gripper is usually at the tail end of the end effector and can accurately grasp and place various objects, such as coffee cups, kettles and other tools. This function enables the unmanned coffee robot to automatically complete the entire process from taking objects to making coffee.

Images