Soldering flux supplementing method, system and equipment based on robot with body and medium

Abstract

The invention relates to a soldering flux supplementing method, system and device based on a robot with a body and a medium, and the method comprises the steps that firstly, an image of a soldering flux container is shot according to a shooting assembly, and a first coordinate of the container is determined; based on the first coordinates, the container is moved to the target position through the clamping jaw; shooting a container image at the target position through a shooting assembly, and determining a second coordinate of the container; and then, on the basis of the second coordinates, the material supplementing pipeline is controlled to move to a preset position in the container. And finally, when the signal that the material supplementing pipeline is located at the preset position is received in response, the soldering flux supplementing assembly is started, and when the soldering flux supplementing amount reaches the preset supplementing amount, the soldering flux supplementing assembly is closed. According to the soldering flux supplementing method and device, automatic operation of soldering flux supplementing is achieved, the problem that in the prior art, a soldering flux supplementing mode depends on manual operation, and the supplementing efficiency is low is solved, and the soldering flux supplementing precision is improved.

Description

Technical Field

[0001] The present application relates to the field of industrial automation technology, and in particular to a flux replenishment method, system, equipment, and medium for an embodied robot. Background Art

[0002] The stringer production line is a core component of the photovoltaic module production line, primarily used to connect low-voltage solar cells in series or parallel to meet practical application requirements. The stringer production line requires the continuous use of flux to ensure welding quality.

[0003] The existing flux replenishment method relies on manual operation and has the problem of low replenishment efficiency. Summary of the Invention

[0004] The embodiments of the present application provide a flux replenishment method, system, device and medium based on an embodied robot, so as to at least solve the problem that the flux replenishment method in the related art relies on manual operation and has low replenishment efficiency.

[0005] In a first aspect, an embodiment of the present application provides a flux refilling method based on an embodied robot, wherein the embodied robot includes a camera assembly, a refilling pipe, a flux refilling assembly, and a gripper. When performing flux refilling, the method includes:

[0006] determining a first coordinate of the container based on an image of the flux container captured by the capturing component;

[0007] Based on the first coordinate, the container is moved to a target position by the gripper; an image of the container at the target position is captured by the camera assembly to determine a second coordinate of the container;

[0008] Based on the second coordinate, controlling the feeding pipe to move to a predetermined position in the container;

[0009] In response to receiving a signal indicating that the material supply pipeline is located at a predetermined position, the soldering flux replenishing component is activated, and when the soldering flux replenishing amount reaches a preset replenishing amount, the soldering flux replenishing component is closed.

[0010] In one embodiment, the image of the flux container captured by the capturing component includes a color image and a depth image, and determining the first coordinate of the container based on the image of the flux container captured by the capturing component includes:

[0011] Preprocessing the color image to enhance the contrast and reduce the noise of the image;

[0012] Identify the bounding box of the container in the color image using an object detection algorithm, and extract the center point of the container as an XY coordinate point;

[0013] Obtaining the Z coordinate of the container according to the pixel value corresponding to the XY coordinate point in the depth image;

[0014] The XY coordinate point and the Z coordinate are combined to generate a first coordinate of the container.

[0015] In one embodiment, moving the container to a target position by the gripper based on the first coordinate includes:

[0016] generating a motion path of the gripper according to the first coordinate, wherein the motion path includes a straight line segment and a circular arc transition segment from a current gripper position to a gripping point of the container;

[0017] Controlling the gripper to move along the motion path to a gripping point of the container;

[0018] Identify the material type of the container, dynamically adjust the gripping force of the gripper, and move the container to a target position.

[0019] In one embodiment, a force sensor is installed on the gripper, and identifying the material type of the container and dynamically adjusting the gripping force of the gripper includes:

[0020] Capturing a surface image of the container by the shooting component, and extracting texture features and color features of the image;

[0021] Inputting the texture features and color features into a pre-trained material classification model to output the material type of the container;

[0022] Determine the grasping force threshold of the current material type based on the mapping relationship between material type and grasping force;

[0023] Based on the grasping force threshold, the grasping force data is fed back in real time by the force sensor to dynamically adjust the grasping force of the gripper.

[0024] In one embodiment, before determining the grasping force threshold of the current material type based on the mapping relationship between the material type and the grasping force, the method further includes:

[0025] Conduct multiple grasping experiments on containers of each material type, recording the minimum grasping force required for successful grasping and the maximum grasping force required without causing deformation of the container. The material types include metal, plastic, glass, and ceramic.

[0026] Based on multiple grasping experiment data, a mapping relationship between material type and grasping force threshold is established, wherein the mapping relationship includes the minimum grasping force and the maximum grasping force corresponding to each material type;

[0027] The mapping relationship is stored in a database.

[0028] In one embodiment, controlling the feeding pipe to move to a predetermined position in the container based on the second coordinate includes:

[0029] generating a global motion path of the feeding pipe according to the second coordinate, wherein the global motion path includes a collision-free path of the feeding pipe from a current position to the container port;

[0030] Controlling the feeding pipe to move along the global motion path to the container port;

[0031] When the distance between the feeding pipe and the container opening is at a preset distance, dynamically adjusting the end posture of the feeding pipe to control the feeding pipe to be aligned with the container opening;

[0032] After the feed pipe is aligned with the container opening, the feed pipe is controlled to move to a predetermined position in the container.

[0033] In one embodiment, the feed pipe is equipped with a flow sensor, and the container is equipped with a liquid level sensor. In response to receiving a signal indicating that the feed pipe is located at a predetermined position, the flux replenishing component is activated, and when the flux replenishment amount reaches a preset replenishment amount, the flux replenishing component is closed, including:

[0034] In response to receiving a signal indicating that the material supply pipe is located at a predetermined position, starting the flux replenishing assembly to replenish flux into the container through the material supply pipe;

[0035] monitoring the replenishment flow of the soldering flux in real time by means of the flow sensor, and / or monitoring the soldering flux liquid level in the container in real time by means of the liquid level sensor;

[0036] When the liquid level sensor detects that the soldering flux liquid level in the container reaches a set liquid level, a signal that the soldering flux replenishment amount reaches a preset replenishment amount is issued; and / or when the accumulated replenishment amount of the flow sensor reaches a set value, a signal that the soldering flux replenishment amount reaches a preset replenishment amount is issued;

[0037] When the soldering flux replenishment amount reaches a preset replenishment amount, the soldering flux replenishment component is closed.

[0038] In a second aspect, an embodiment of the present application provides a flux replenishing system based on an embodied robot, wherein the embodied robot includes a shooting component, a replenishing pipe, a flux replenishing component, and a gripper, and the system includes a first coordinate module, a second coordinate module, a replenishing pipe moving module, and a replenishing module; wherein,

[0039] The first coordinate module is used to determine the first coordinates of the container based on the image of the flux container captured by the shooting component;

[0040] The second coordinate module is configured to move the container to a target position via the gripper based on the first coordinate; and to capture an image of the container at the target position via the photographing component to determine a second coordinate of the container;

[0041] The feeding pipe moving module is used to control the feeding pipe to move to a predetermined position in the container based on the second coordinate;

[0042] The feeding module is configured to start the flux replenishing component in response to receiving a signal indicating that the feeding pipeline is located at a predetermined position, and to shut down the flux replenishing component when the flux replenishment amount reaches a preset replenishment amount.

[0043] In a third aspect, an embodiment of the present application provides a computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements a flux replenishment method based on an embodied robot as described in the first aspect above.

[0044] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a flux replenishment method based on an embodied robot as described in the first aspect above.

[0045] The flux replenishment method, system, equipment and medium based on the embodied robot provided in the embodiments of the present application have at least the following technical effects.

[0046] First, the imaging component captures an image of the flux container to determine the container's first coordinates. Based on the first coordinates, the gripper moves the container to a target position. The imaging component captures an image of the container at the target position to determine the container's second coordinates. Subsequently, based on the second coordinates, the refill pipe is controlled to move to a predetermined position within the container. Finally, in response to receiving a signal indicating the refill pipe is at the predetermined position, the flux refill component is activated. When the flux refill reaches a preset level, the flux refill component is deactivated. This automated flux refill process addresses the issue of manual refilling and low refill efficiency in related art, improving flux refill accuracy.

[0047] The details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0049] Figure 1 It is a flow chart of a flux replenishment method based on an embodied robot;

[0050] Figure 2 is a flow chart showing a method for a gripper to move a container to a target position according to an exemplary embodiment;

[0051] Figure 3 is a flowchart of step S1023 according to an exemplary embodiment;

[0052] Figure 4 is a flowchart showing step S103 according to an exemplary embodiment.

[0053] Figure 5 is a block diagram of a system structure for flux replenishment based on an embodied robot according to an exemplary embodiment;

[0054] Figure 6 It is a structural block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is described and illustrated below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely used to explain this application and are not intended to limit this application. Based on the embodiments provided in this application, all other embodiments obtained by those of ordinary skill in the art without making any creative efforts are within the scope of protection of this application.

[0056] Obviously, the drawings described below are merely examples or embodiments of the present application. Those skilled in the art can, without inventive effort, apply the present application to other similar scenarios based on these drawings. Furthermore, it is also understood that, although the effort involved in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, changes in design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as an insufficiency of the content disclosed in this application.

[0057] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it refer to independent or alternative embodiments that are mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments unless there is a conflict.

[0058] Unless otherwise defined, the technical or scientific terms used in this application should have the ordinary meaning understood by a person of ordinary skill in the technical field to which this application belongs. The words "one", "a", "the" and the like used in this application do not indicate a limit on quantity and may indicate the singular or plural. The terms "include", "comprise", "have" and any variations thereof used in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units that are inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The word "multiple" used in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist. For example, "A and / or B" can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects before and after are in an "or" relationship. The terms "first", "second", "third", etc. involved in this application are only used to distinguish similar objects and do not represent a specific order for the objects.

[0059] It should be understood that the terms herein may be technical means for implementing a part of the present invention or other summary technical terms. For example, the terms may include:

[0060] Embodied Robot: An embodied robot is an intelligent robot with a physical body that can perceive, learn, and perform tasks through real-time interaction between its body and the environment. In the embodiments of this application, an embodied robot in the form of an AGV is used. An AGV-type embodied robot is an intelligent robot that uses an automated guided vehicle (AGV) as a carrier and, in combination with embodied cognition theory, achieves autonomous navigation, task execution, and adaptive learning through dynamic interaction between its physical body and the environment.

[0061] In a first aspect, an embodiment of the present application provides a flux replenishment method based on an embodied robot, wherein the embodied robot includes a shooting component, a replenishment pipe, a flux replenishment component, and a gripper. Figure 1 It is a flow chart of a flux replenishment method based on an embodied robot, such as Figure 1 As shown, the method includes:

[0062] Step S101 : determining a first coordinate of a flux container by taking an image of the flux container by a photographing component.

[0063] Step S102: Based on the first coordinate, the container is moved to a target position by the gripper; an image of the container at the target position is captured by the camera assembly to determine a second coordinate of the container.

[0064] Step S103: Based on the second coordinate, control the feeding pipeline to move to a predetermined position in the container.

[0065] Step S104 : in response to receiving a signal indicating that the material supply pipeline is located at a predetermined position, starting the flux replenishing component; when the amount of flux replenished reaches a preset replenishing amount, closing the flux replenishing component.

[0066] In summary, the embodiments of the present application provide a flux refilling method based on an embodied robot. This method uses a camera component to precisely locate the flux container and determine its coordinates, controls the gripper to move the container to the target position, and then precisely locates the refilling pipe based on the secondary coordinates to insert it into the container. Once the refilling pipe is in place, the flux refilling component is activated, and the refilling volume is monitored in real time via flow and level sensors. Refilling automatically stops when the preset value is reached. This method achieves fully automated operation, achieving high-precision positioning and precise refilling, significantly improving production efficiency. This method addresses the problem of low refilling efficiency in related art flux refilling methods that rely on manual operation.

[0067] In one embodiment, the embodied robot includes a camera assembly, a feeding pipe, a gripper, and a robotic arm. The camera assembly (including an RGB-D camera and a lidar) is mounted at the end of the robotic arm to capture images of the container and determine the distance between the feeding pipe and the container opening. The gripper module (including a force sensor) is located at the end of the robotic arm and is used to grasp the container. The feeding pipe is connected to the flux replenishment assembly via a one-way valve, and the robotic arm is used to perform grasping, insertion, and resetting operations. The camera assembly, feeding pipe, gripper, and robotic arm ensure precise positioning, grasping, and feeding operations.

[0068] In one embodiment, step S101, based on the image of the flux container captured by the camera assembly, determines the first coordinates of the container. Specifically, it includes:

[0069] Preprocess the color image to enhance the contrast and reduce the noise of the image;

[0070] The bounding box of the container in the color image is identified by the object detection algorithm, and the center point of the container is extracted as the XY coordinate point;

[0071] Obtain the Z coordinate of the container based on the pixel value corresponding to the XY coordinate point in the depth image;

[0072] Combine the XY coordinate point and the Z coordinate to generate the first coordinate of the container.

[0073] Optionally, the embodied robot captures a color image of the flux container using an RGB-D camera and a depth image using a depth camera. First, the color image is preprocessed, including histogram equalization to enhance contrast and Gaussian filtering to reduce noise. Next, an object detection algorithm (such as YOLOv5) is used to identify the container's bounding box and extract its center as the XY coordinate point. The Z coordinate of the container is then determined based on the pixel values ​​corresponding to the XY coordinate point in the depth image. Finally, the XY coordinate point and the Z coordinate are combined to generate the container's first coordinate (X, Y, Z).

[0074] For example, the coordinates of the center point of the container in the image are (320, 240), which means that the point is at the 320th pixel in the width direction and the 240th pixel in the height direction of the image. The depth image and the color image are registered, that is, their pixels correspond one to one. Therefore, the coordinates in the color image can be directly mapped to the same coordinates in the depth image. Find the pixel value at the position (320, 240) in the depth image. Assume that the pixel value is 800, which means that the distance from the point to the camera is 800 mm. The pixel value in the depth image is the Z coordinate (depth value). The Z coordinate is 800 mm. The first coordinate is (320, 240, 800).

[0075] Step S101 achieves high-precision three-dimensional positioning of the flux container through image processing and coordinate transformation, significantly improving the accuracy of subsequent grasping and refilling operations. The combination of preprocessing and object detection algorithms effectively enhances image quality and feature recognition capabilities, laying a solid foundation for fully automated refilling.

[0076] Figure 2 FIG. 1 is a flow chart showing a method for moving a container to a target position by a gripper according to an exemplary embodiment. Figure 2 As shown, step S102, based on the first coordinate, the container is moved to the target position by the gripper, which specifically includes the following steps:

[0077] Step S1021: Generate a motion path of the gripper according to the first coordinate, where the motion path includes a straight line segment and an arc transition segment from the current gripper position to the gripping point of the container;

[0078] Step S1022: Control the gripper to move along the motion path to the gripping point of the container;

[0079] Step S1023: Identify the material type of the container, dynamically adjust the gripping force of the gripper, and move the container to the target position.

[0080] Optionally, the embodied robot generates a motion path for the gripper based on the first coordinate. The path planning can utilize the RRT* (Rapidly-exploring Random Tree Sta) algorithm to ensure a collision-free and optimal path from the current gripper position to the container grasping point. The path consists of straight segments and circular transition segments. The straight segments are used to quickly approach the container, while the circular transition segments are used for smooth steering to avoid jitter in the robotic arm's motion. After controlling the gripper to move along the path to the grasping point, an RGB-D camera is used to capture images of the container surface, extracting texture and color features. These images are then fed into a pre-trained material classification model (e.g., ResNet-18) to output the container material type (e.g., metal, plastic, glass). A preset gripping force threshold range is applied based on the material type, and a fuzzy PID algorithm can be used to dynamically adjust the gripper's closing speed and force. For example, when the gripper contacts a metal container, the initial gripping force is set to 20N. Through real-time feedback from the force sensor, the force is gradually increased to 30N to ensure a secure grip without damaging the container. Finally, the gripper moves the container smoothly to the target position. During the movement, the visual system and distance sensor (lidar) monitor the container position and posture in real time to ensure collision-free.

[0081] Step S102 significantly improves the accuracy and safety of the gripper operation through path planning and dynamic gripping force control. The arc transition design in path planning makes the robot arm movement smoother and reduces the impact of vibration on positioning accuracy.

[0082] Figure 3 is a flowchart of step S1023 according to an exemplary embodiment. Figure 3 As shown, step S1023, identifying the material type of the container, dynamically adjusting the gripping force of the gripper, and moving the container to the target position. Specifically, the following steps are included:

[0083] Step S10231: Capture a surface image of the container through a photographing component, and extract texture features and color features of the image;

[0084] Step S10232: Input the texture features and color features into a pre-trained material classification model to output the material type of the container;

[0085] Step S10233: Determine the grasping force threshold of the current material type according to the mapping relationship between the material type and the grasping force;

[0086] Step S10234: Based on the grasping force threshold, the grasping force data is fed back in real time by the force sensor to dynamically adjust the grasping force of the gripper.

[0087] Optionally, the embodied robot captures surface images of the container using a camera (e.g., an RGB-D camera) and extracts texture features (e.g., contrast and entropy in the grayscale co-occurrence matrix) and color features (e.g., hue and saturation in the HSV color space). These features are fed into a pre-trained material classification model (e.g., a convolutional neural network based on ResNet-18), which outputs the container's material type (e.g., metal, plastic, glass). Based on the mapping between material type and gripping force (e.g., 20-50N for metal containers and 10-30N for plastic containers), a gripping force threshold for the current material type is determined. Force sensors on the gripper provide real-time feedback on the gripping force, enabling a fuzzy PID algorithm to dynamically adjust the gripper's closing speed and force to ensure the gripping force remains within the threshold range. For example, when the gripper contacts a metal container, the initial gripping force is set to 20N. Using real-time feedback from the force sensor, the force is gradually increased to 30N to ensure a secure grip without damaging the container. Finally, the gripper moves the container smoothly to the target position. During the movement, the visual system and distance sensor monitor the container position and posture in real time to ensure collision-free.

[0088] Through the multimodal perception and dynamic gripping force control in step S1023, the accuracy and safety of the gripper operation are significantly improved, providing a solid guarantee for subsequent feeding operations.

[0089] In one embodiment, before determining the grasping force threshold of the current material type according to the mapping relationship between the material type and the grasping force in step S10233, the method further includes:

[0090] Conduct multiple grasping experiments on containers of each material type, recording the minimum grasping force required for successful grasping and the maximum grasping force required without causing deformation of the container. The material types include metal, plastic, glass, and ceramic.

[0091] Based on multiple grasping experiment data, a mapping relationship between material type and grasping force threshold is established. The mapping relationship includes the minimum grasping force and maximum grasping force corresponding to each material type.

[0092] Store the mapping relationship in the database.

[0093] Optionally, multiple grasping experiments are performed on containers of each material type (such as metal, plastic, and glass). The minimum grasping force for successful grasping and the maximum grasping force that does not cause deformation or leakage of the container are recorded for each experiment. The experimental environment covers different temperature (-20℃~60℃) and humidity (30%~90%) conditions. Environmental compensation factors (such as temperature and humidity) can be introduced to dynamically adjust the grasping force threshold. Ensure the comprehensiveness of the data. Based on the data of multiple grasping experiments, establish a mapping relationship between material type and grasping force threshold. For example:

[0094] The minimum gripping force for metal containers is 20N and the maximum gripping force is 50N.

[0095] The minimum gripping force for plastic containers is 10N and the maximum gripping force is 30N.

[0096] The minimum gripping force for glass containers is 5N and the maximum gripping force is 15N.

[0097] The mapping between material type and gripping force thresholds is stored in the robot control system's database using SQLite structured storage. The fields include material type, minimum gripping force, maximum gripping force, and temperature and humidity compensation coefficients. During actual gripping operations, the camera component identifies the container material type and retrieves the corresponding gripping force threshold from the database, which serves as the basis for gripper control.

[0098] Through scientific experiments and data analysis, a precise mapping relationship between material type and gripping force threshold was established, significantly improving the reliability and adaptability of the gripper's operation. Furthermore, by introducing an environmental compensation factor, high reliability can be maintained even under extreme temperature and humidity conditions, providing a solid foundation for subsequent refilling operations.

[0099] In one embodiment, step S102 captures an image of the container at the target location using a camera assembly to determine the second coordinates of the container. This specifically includes:

[0100] The embodied robot captures a color image of the flux container using an RGB-D camera and a depth image using a depth camera. First, the color image is preprocessed, including histogram equalization to enhance contrast and Gaussian filtering to reduce noise. Next, an object detection algorithm (such as YOLOv5) is used to identify the container's bounding box and extract its center as the XY coordinate point. The Z coordinate of the container is then determined based on the pixel values ​​corresponding to the XY coordinate point in the depth image. Finally, the XY coordinate point and the Z coordinate are combined to generate the container's first coordinate (X, Y, Z). These coordinates are converted to the robot's base coordinate system through hand-eye calibration. It is worth noting that determining the container's second coordinate is consistent with determining the container's first coordinate in step S101 above, and this will not be elaborated on here.

[0101] Figure 4is a flowchart of step S103 according to an exemplary embodiment. Figure 4 As shown, step S103, based on the second coordinate, controls the feeding pipe to move to a predetermined position in the container. Specifically, it includes the following steps:

[0102] Step S1031: Generate a global motion path of the feeding pipe according to the second coordinate, where the global motion path includes a collision-free path of the feeding pipe from the current position to the container port;

[0103] Step S1032: Control the feeding pipeline to move to the container port along the global motion path;

[0104] Step S1033: When the distance between the feeding pipe and the container opening is at a preset distance, dynamically adjust the terminal posture of the feeding pipe to control the feeding pipe to be aligned with the container opening;

[0105] Step S1034: After the feeding pipe is aligned with the container opening, the feeding pipe is controlled to move to a predetermined position in the container.

[0106] Optionally, in step S103, the embodied robot generates a global motion path for the feeding pipe based on the second coordinate. First, the RRT* (rapidly expanding random tree) algorithm is used to plan a collision-free path from the current position to the container mouth. The RRT* algorithm gradually explores the optimal path by randomly sampling nodes in the configuration space and constructing a tree structure. The feeding pipe is controlled to move along the path to the container mouth. When the distance between the pipe and the container mouth is less than the preset distance, the preset distance can be up to 30mm-50mm. The relative position of the feeding pipe and the container mouth is captured in real time by the shooting component, an error signal is generated, and the movement of the robotic arm is controlled to reduce the error. The posture of the end of the pipe is dynamically adjusted to ensure that it is aligned with the axis of the container mouth. After alignment, the feeding pipe is controlled to slowly insert into the container to a predetermined position (such as a depth of 100mm), triggering the position sensor to detect the insertion depth and send an in-place signal.

[0107] Step S103: Through global path planning and dynamic posture adjustment, the accuracy and success rate of material feeding pipe insertion are significantly improved, providing a solid guarantee for subsequent flux replenishment operations.

[0108] In one embodiment, a flow sensor is installed in the feeding pipe and a liquid level sensor is installed in the container. In step S104, in response to receiving a signal indicating that the feeding pipe is at a predetermined position, the flux replenishing component is activated. When the flux replenishment amount reaches a preset replenishment amount, the flux replenishing component is closed. Specifically, the steps include:

[0109] In response to receiving a signal indicating that the material supply pipe is located at a predetermined position, the flux supply assembly is activated to supply flux into the container through the material supply pipe;

[0110] Real-time monitoring of the flux replenishment flow rate by a flow sensor, and / or real-time monitoring of the flux liquid level in the container by a liquid level sensor;

[0111] When the liquid level sensor detects that the soldering flux liquid level in the container reaches a set liquid level, it sends a signal that the soldering flux replenishment amount has reached a preset replenishment amount; and / or when the accumulated replenishment amount of the flow sensor reaches a set value, it sends a signal that the soldering flux replenishment amount has reached a preset replenishment amount;

[0112] When the flux replenishment amount reaches a preset replenishment amount, the flux replenishment component is closed.

[0113] Optionally, when the robot control receives a signal indicating that the refill pipe is at a predetermined position, it activates the flux refill assembly and refills flux into the container through the refill pipe. A high-precision flow sensor is installed on the refill pipe for real-time monitoring of the flux refill flow rate, and an ultrasonic level sensor is installed in the container for real-time monitoring of the flux level. During the refill process, data from both the flow sensor and the level sensor are received simultaneously for double verification. When the level sensor detects that the flux level in the container has reached a set level (e.g., a liquid level height of 100 mm), it signals that the flux refill amount has reached the preset amount. Alternatively, when the accumulated refill amount recorded by the flow sensor reaches a set value (e.g., 500 ml), it signals that the flux refill amount has reached the preset amount. Upon receiving the signal, the robot control system immediately shuts down the flux refill assembly and stops the refill operation. Furthermore, the flow rate, level, and time data for each refill are recorded and stored in a SQLite database for subsequent production analysis and equipment maintenance.

[0114] Step S104: Dual monitoring by the flow sensor and the level sensor ensures precise control of the flux replenishment amount. By recording the operational data of each refill, the system can generate a refill report to help optimize production processes and equipment maintenance plans.

[0115] In summary, the embodiments of the present application provide a flux refilling method based on an embodied robot. This method uses a camera component to precisely locate the flux container and determine its coordinates, controls the gripper to move the container to the target position, and then precisely locates the refilling pipe based on the secondary coordinates to insert it into the container. Once the refilling pipe is in place, the flux refilling component is activated, and the refilling volume is monitored in real time via flow and level sensors. Refilling automatically stops when the preset value is reached. This method achieves fully automated operation, achieving high-precision positioning and precise refilling, significantly improving production efficiency. This method addresses the problem of low refilling efficiency in related art flux refilling methods that rely on manual operation.

[0116] In a second aspect, an embodiment of the present application provides a flux replenishment system based on an embodied robot. Figure 5FIG. 1 is a block diagram of a system structure for flux replenishment based on an embodied robot according to an exemplary embodiment. Figure 5 As shown, the embodied robot includes a shooting component, a feeding pipe, a flux replenishing component and a gripper, and the system includes a first coordinate module 510, a second coordinate module 520, a feeding pipe moving module 530 and a feeding module 540; wherein,

[0117] A first coordinate module 510 is configured to determine a first coordinate of the flux container based on an image of the flux container captured by the capturing component;

[0118] The second coordinate module 520 is configured to move the container to a target position using the gripper based on the first coordinate; and to capture an image of the container at the target position using the camera assembly to determine a second coordinate of the container;

[0119] A feeding pipe moving module 530 is used to control the feeding pipe to move to a predetermined position in the container based on the second coordinate;

[0120] The feeding module 540 is configured to start the flux replenishing component in response to receiving a signal indicating that the feeding pipeline is located at a predetermined position, and to shut down the flux replenishing component when the flux replenishing amount reaches a preset replenishing amount.

[0121] In summary, the present embodiment provides a flux refilling system based on an embodied robot. Through the first coordinate module 510, the second coordinate module 520, the refilling pipe movement module 530, and the refilling module 540, the system automates the entire flux refilling process, achieving high-precision positioning and precise refilling, significantly improving production efficiency. This addresses the problem of low refilling efficiency in related art flux refilling methods that rely on manual operation.

[0122] It should be noted that the flux refilling system based on an embodied robot provided in this embodiment is used to implement the aforementioned embodiments, and details already described will not be repeated. As used above, the terms "module," "unit," "subunit," etc. may refer to a combination of software and / or hardware that implements a predetermined function. While the apparatus described in the above embodiments is preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0123] In a third aspect, an embodiment of the present application provides an electronic device, Figure 6 FIG is a block diagram of an electronic device according to an exemplary embodiment. Figure 6 As shown, the electronic device may include a processor 61 and a memory 62 storing computer program instructions.

[0124] Specifically, the processor 61 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0125] Among them, the memory 62 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 62 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 62 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 62 may be inside or outside the data processing device. In a specific embodiment, the memory 62 is a non-volatile memory. In a specific embodiment, the memory 62 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (Erasable Programmable Read-Only Memory, EPROM for short), an electrically erasable PROM (Electrically Erasable Programmable Read-Only Memory, EEPROM for short), an electrically alterable ROM (Electrically Alterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), where the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0126] The memory 62 may be used to store or cache various data files required for processing and / or communication, as well as possible computer program instructions executed by the processor 61 .

[0127] The processor 61 reads and executes computer program instructions stored in the memory 62 to implement any one of the flux replenishing methods based on the embodied robot in the above embodiments.

[0128] In one embodiment, a flux replenishing device based on an embodied robot may further include a communication interface 63 and a bus 60. Figure 6 As shown, the processor 61, the memory 62, and the communication interface 63 are connected via a bus 60 and communicate with each other.

[0129] The communication interface 63 is used to enable communication between the various modules, devices, units, and / or devices in the embodiments of the present application. The communication port 63 can also enable data communication with other components such as external devices, image / data acquisition devices, databases, external storage, and image / data processing workstations.

[0130] The bus 60 includes hardware, software, or both, and couples the components of the embodied robot-based flux refilling apparatus to one another. The bus 60 includes, but is not limited to, at least one of the following: a data bus, an address bus, a control bus, an expansion bus, and a local bus. By way of example and not limitation, bus 60 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of the above. Bus 60 may include one or more buses, where appropriate. Although embodiments herein describe and illustrate a particular bus, this application contemplates any suitable bus or interconnect.

[0131] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a program stored thereon. When the program is executed by a processor, the flux replenishment method based on an embodied robot provided in the first aspect is implemented.

[0132] The readable storage medium may include, but is not limited to, a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0133] In a possible embodiment, the present invention can also be implemented in the form of a program product, which includes program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of a flux replenishment method based on an embodied robot provided in the first aspect.

[0134] The program code for executing the present invention may be written in any combination of one or more programming languages, and may be executed entirely on the user device, partially on the user device, as an independent software package, partially on the user device and partially on a remote device, or entirely on the remote device.

[0135] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0136] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A flux replenishing method based on an embodied robot, characterized in that: The embodied robot includes a shooting component, a feeding pipe, a flux replenishing component and a gripper. When performing flux replenishment, the method includes: determining a first coordinate of the container based on an image of the flux container captured by the capturing component; Based on the first coordinate, the container is moved to a target position by the gripper; an image of the container at the target position is captured by the camera assembly to determine a second coordinate of the container; Based on the second coordinate, controlling the feeding pipe to move to a predetermined position in the container; In response to receiving a signal indicating that the material supply pipeline is located at a predetermined position, the soldering flux replenishing assembly is activated, and when the soldering flux replenishing amount reaches a preset replenishing amount, the soldering flux replenishing assembly is closed.

2. A flux replenishing method based on an embodied robot according to claim 1, characterized in that: The step of moving the container to a target position by the gripper based on the first coordinate comprises: generating a motion path of the gripper according to the first coordinate, wherein the motion path includes a straight line segment and a circular arc transition segment from a current gripper position to a gripping point of the container; Controlling the gripper to move along the motion path to a gripping point of the container; Identify the material type of the container, dynamically adjust the gripping force of the gripper, and move the container to a target position.

3. The flux replenishing method based on an embodied robot according to claim 2, characterized in that: A force sensor is installed on the gripper to identify the material type of the container and dynamically adjust the gripping force of the gripper, including: Capturing a surface image of the container by the shooting component, and extracting texture features and color features of the image; Inputting the texture features and color features into a pre-trained material classification model to output the material type of the container; Determine the grasping force threshold of the current material type based on the mapping relationship between material type and grasping force; Based on the grasping force threshold, the grasping force data is fed back in real time by the force sensor to dynamically adjust the grasping force of the gripper.

4. The flux replenishing method based on an embodied robot according to claim 3, characterized in that: Before determining the grasping force threshold of the current material type according to the mapping relationship between the material type and the grasping force, the method further includes: Conduct multiple grasping experiments on containers of each material type, recording the minimum grasping force required for successful grasping and the maximum grasping force required without causing deformation of the container. The material types include metal, plastic, glass, and ceramic. Based on multiple grasping experiment data, a mapping relationship between material type and grasping force threshold is established, wherein the mapping relationship includes the minimum grasping force and the maximum grasping force corresponding to each material type; The mapping relationship is stored in a database.

5. The flux replenishing method based on an embodied robot according to claim 1, characterized in that: The image of the flux container taken by the photographing component includes a color image and a depth image, and determining the first coordinate of the container according to the image of the flux container taken by the photographing component includes: Preprocessing the color image to enhance the contrast and reduce the noise of the image; Identify the bounding box of the container in the color image using an object detection algorithm, and extract the center point of the container as an XY coordinate point; Obtaining the Z coordinate of the container according to the pixel value corresponding to the XY coordinate point in the depth image; The XY coordinate point and the Z coordinate are combined to generate a first coordinate of the container.

6. The flux replenishing method based on an embodied robot according to claim 1, characterized in that: Based on the second coordinate, controlling the feeding pipe to move to a predetermined position in the container includes: generating a global motion path of the feeding pipe according to the second coordinate, wherein the global motion path includes a collision-free path of the feeding pipe from a current position to the container port; Controlling the feeding pipe to move along the global motion path to the container port; When the distance between the feeding pipe and the container opening is at a preset distance, dynamically adjusting the end posture of the feeding pipe to control the feeding pipe to be aligned with the container opening; After the feed pipe is aligned with the container opening, the feed pipe is controlled to move to a predetermined position in the container.

7. The flux replenishing method based on an embodied robot according to claim 1, characterized in that: The feed pipe is equipped with a flow sensor, and the container is equipped with a liquid level sensor. In response to receiving a signal indicating that the feed pipe is located at a predetermined position, the flux replenishing component is activated, and when the flux replenishment amount reaches a preset replenishment amount, the flux replenishing component is closed, including: In response to receiving a signal indicating that the material supply pipe is located at a predetermined position, starting the flux replenishing assembly to replenish flux into the container through the material supply pipe; monitoring the replenishment flow of the soldering flux in real time by means of the flow sensor, and / or monitoring the soldering flux liquid level in the container in real time by means of the liquid level sensor; When the liquid level sensor detects that the soldering flux liquid level in the container reaches a set liquid level, it sends a signal that the soldering flux replenishment amount reaches a preset replenishment amount; and / or when the accumulated replenishment amount of the flow sensor reaches a set value, it sends a signal that the soldering flux replenishment amount reaches a preset replenishment amount; When the soldering flux replenishment amount reaches a preset replenishment amount, the soldering flux replenishment component is closed.

8. A flux replenishing system based on an embodied robot, characterized in that: The embodied robot includes a shooting component, a feeding pipe, a flux replenishing component and a gripper, and the system includes a first coordinate module, a second coordinate module, a feeding pipe moving module and a feeding module; wherein, The first coordinate module is used to determine the first coordinates of the container based on the image of the flux container captured by the shooting component; The second coordinate module is configured to move the container to a target position via the gripper based on the first coordinate; and to capture an image of the container at the target position via the photographing component to determine a second coordinate of the container; The feeding pipe moving module is used to control the feeding pipe to move to a predetermined position in the container based on the second coordinate; The feeding module is used to start the flux replenishing component in response to receiving a signal indicating that the feeding pipeline is located at a predetermined position, and to close the flux replenishing component when the flux replenishment amount reaches a preset replenishment amount.

9. An electronic device, characterized in that: The invention comprises a memory and a processor, a computer program stored in the memory and executable on the processor, and the processor implements a soldering flux replenishment method based on an embodied robot as claimed in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a flux replenishing method based on an embodied robot according to any one of claims 1 to 7 is implemented.

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