Material detection method and device based on fixing seat and fixing seat

Abstract

The embodiment of the application discloses a kind of fixed seat-based material detection method, device and fixed seat, applied to material detection technical field, can solve the problem of huge workload of manual operation, reduce efficiency, and also there will be placement error, clamping unstable problem.Reflection strip is configured on the fixed seat, and the image to be measured is obtained, which is obtained by the camera shooting the fixed seat when the automatic guided vehicle is located at the specified position, and the camera and the fill light are configured on the automatic guided vehicle.The image to be measured is subjected to image recognition, and the target light spot area is extracted.If the size information of the target light spot area is less than the preset size information, it is determined that there is a measured object on the fixed seat, and the size information of the reflection strip when the fixed seat is in the empty state is the preset size information.

Description

Technical Field

[0001] This application relates to the field of material detection technology, and in particular to a material detection method, apparatus and fixture based on a fixed base. Background Technology

[0002] Objective image quality testing for cameras primarily involves using a mobile phone / tablet camera to capture images of various standard charts under specific environmental conditions (light source, color temperature) and then analyzing the image quality indicators of the photos. Traditional objective testing of mobile phone or tablet cameras mainly relies on manual labor in an objective laboratory. The quality of the captured images directly affects the test results, making automated camera testing particularly important. While automated testing can use machines to replace manual labor in taking photos, staff still need to manually place the phone or tablet under test onto a fixture before each test, using a robotic arm to hold the fixture and secure the device for the test. This approach still heavily relies on manual operation, resulting in a huge workload, reduced efficiency, and issues such as placement errors and unstable clamping. Summary of the Invention

[0003] To solve the above-mentioned technical problems, or at least partially solve them, this application provides a material detection method, device, and fixed base based on a fixed base, which solves the problems of high workload and reduced efficiency of manual operation, as well as the occurrence of placement errors and unstable clamping.

[0004] To achieve the above objectives, the technical solutions provided in this application are as follows:

[0005] In a first aspect, embodiments of this application provide a material detection method based on a fixed base, wherein the fixed base is equipped with a reflective strip, and the material detection method includes: acquiring a test image, wherein the test image is obtained by taking a picture of the fixed base with a camera when the automated guided vehicle is located at a designated position, and the automated guided vehicle is equipped with the camera and a supplementary light;

[0006] Image recognition is performed on the image to be tested to extract the target spot region;

[0007] If the size of the target light spot area is detected to be smaller than the preset size information, it is determined that there is an object to be measured on the fixed base. The preset size information is the size information of the reflective strip when the fixed base is in an unoccupied state.

[0008] As an optional implementation, in a first aspect of the embodiments of this application, the method further includes:

[0009] When the mounting base is in an unused state, the camera takes a picture of the mounting base to obtain a pre-configured image;

[0010] Perform image recognition on the pre-configured image to extract the pre-configured spot area;

[0011] The size information of the pre-configured light spot area is determined to be the preset size information.

[0012] As an optional implementation, in a first aspect of this application embodiment, the step of determining that an object to be measured exists on the fixture if the size information of the target light spot region is detected to be smaller than preset size information includes:

[0013] If the size information of the target light spot area is detected to be smaller than the preset size information, and the difference between the target light spot area and the preset size information is greater than the preset difference, then it is determined that the object to be measured exists on the fixed base;

[0014] The size information includes at least: height information and area information.

[0015] As an optional implementation, in a first aspect of the embodiments of this application, acquiring the image to be tested includes:

[0016] Send a target location number to the automated guided vehicle so that the automated guided vehicle moves to the designated location according to the target location number, wherein the target location number is the number corresponding to the designated location;

[0017] When the automated guided vehicle is detected to be at the designated location, the image to be tested is acquired by the camera on the automated guided vehicle.

[0018] As an optional implementation, in a first aspect of this application, the step of acquiring the image to be tested via a camera on the automated guided vehicle when the automated guided vehicle is detected to be located at the designated position includes:

[0019] When the automated guided vehicle is detected to be at the designated position, the auxiliary lights on the automated guided vehicle are turned on, and the image to be tested is acquired through the camera on the automated guided vehicle.

[0020] As an optional implementation, in a first aspect of the embodiments of this application, sending the target location number to the automated guided vehicle includes:

[0021] When the target hopper completes its discharge operation, the hopper location information of the target hopper is determined.

[0022] The target location number corresponding to the hopper positioning information is determined based on the hopper positioning information, and the target location number is sent to the automated guided vehicle.

[0023] The correspondence between the hopper positioning information and the target location number is pre-stored, and the designated location corresponding to the target location number is the position of the fixed seat of the discharge port of the target hopper.

[0024] Secondly, this application provides a material detection device based on a fixed base, wherein the fixed base is equipped with a reflective strip, and the material detection device includes: an acquisition module for acquiring an image to be tested, wherein the image to be tested is obtained by a camera taking a picture of the fixed base when the automated guided vehicle is located at a designated position, and the automated guided vehicle is equipped with the camera and a supplementary light;

[0025] The processing module is used to perform image recognition on the image to be tested and extract the target spot area;

[0026] The processing module is further configured to determine that there is an object to be measured on the fixed base if the size information of the target light spot area is detected to be smaller than the preset size information, wherein the preset size information is the size information of the reflective strip when the fixed base is in an unoccupied state.

[0027] As an optional implementation, in a second aspect of the embodiments of this application, the acquisition module is further configured to take a picture of the fixed base by the camera when the fixed base is in an idle state to obtain a pre-configured image;

[0028] The processing module is also used to perform image recognition on the pre-configured image and extract the pre-configured spot area;

[0029] The processing module is further configured to determine the size information of the pre-configured spot area as the preset size information.

[0030] As an optional implementation, in a second aspect of the embodiments of this application, the processing module is specifically used to determine that the object to be tested exists on the fixing base if the size information of the target light spot area is detected to be smaller than the preset size information and the difference between the target light spot area and the preset size information is greater than the preset difference.

[0031] The size information includes at least: height information and area information.

[0032] As an optional implementation, in a second aspect of the embodiments of this application, the processing module is specifically used to send a target location number to the automated guided vehicle, so that the automated guided vehicle moves to the designated location according to the target location number, wherein the target location number is the number corresponding to the designated location;

[0033] The acquisition module is specifically used to acquire the image to be tested through the camera on the automated guided vehicle when the automated guided vehicle is detected to be located at the designated position.

[0034] As an optional implementation, in a second aspect of the embodiments of this application, the acquisition module is specifically used to turn on the supplementary light on the automated guided vehicle when it is detected that the automated guided vehicle is located at the designated position, and to acquire the image to be tested through the camera on the automated guided vehicle.

[0035] As an optional implementation, in a second aspect of the embodiments of this application, the processing module is specifically used to determine the hopper positioning information of the target hopper when the discharge operation of the target hopper is detected to be completed;

[0036] The processing module is specifically used to determine the target location number corresponding to the hopper positioning information based on the hopper positioning information, and send the target location number to the automated guided vehicle;

[0037] The correspondence between the hopper positioning information and the target location number is pre-stored, and the designated location corresponding to the target location number is the position of the fixed seat of the discharge port of the target hopper.

[0038] Thirdly, embodiments of this application provide a mounting base with reflective strips configured thereon. The reflective strips are used to reflect light to form a light spot, so as to determine whether there is an object to be measured on the mounting base based on the size change of the light spot.

[0039] Fourthly, embodiments of this application provide an electronic device, the electronic device comprising:

[0040] Memory containing executable program code;

[0041] A processor coupled to the memory;

[0042] The processor calls the executable program code stored in the memory to execute the material detection method based on a fixed base in the first aspect of the embodiments of this application.

[0043] Fifthly, embodiments of this application provide a computer-readable storage medium storing a computer program that causes a computer to execute the material detection method based on a fixed base as described in the first aspect of this application. The computer-readable storage medium includes ROM / RAM, a magnetic disk, or an optical disk, etc.

[0044] In a sixth aspect, embodiments of this application provide a computer program product that, when run on a computer, causes the computer to perform some or all of the steps of any of the methods of the first aspect.

[0045] In a seventh aspect, embodiments of this application provide an application publishing platform for publishing computer program products, wherein when the computer program product is run on a computer, the computer performs some or all of the steps of any of the methods in the first aspect.

[0046] Compared with the prior art, the embodiments of this application have the following beneficial effects:

[0047] This application provides a material detection method, apparatus, and fixed base based on a fixed base. The fixed base is equipped with a reflective strip to acquire a test image, which is obtained by a camera taking a picture of the fixed base when the automated guided vehicle (AGV) is in a designated position. The AGV is equipped with a camera and a supplementary light. Image recognition is performed on the test image to extract the target light spot area. If the size of the detected target light spot area is smaller than a preset size, it is determined that there is a test object on the fixed base. The preset size is the size of the reflective strip when the fixed base is in an empty state. With this solution, no manual operation is required. The movement of the test object before and after testing is completely replaced by the AGV. The robotic arm on the AGV can automatically grip the object. Before gripping, it can pre-determine whether there is an object at the designated position, greatly reducing the probability of the robotic arm damaging the test object or the base. This allows for uninterrupted material handling and improves testing efficiency. Attached Figure Description

[0048] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0049] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart illustrating a material detection method based on a fixed base provided in an embodiment of this application. Figure 1 ;

[0051] Figure 2 This is a schematic diagram of a fixing base provided in an embodiment of this application. Figure 1 ;

[0052] Figure 3 This is a schematic diagram of a fixing base provided in an embodiment of this application. Figure 2 ;

[0053] Figure 4This is a flowchart illustrating a material detection method based on a fixed base provided in an embodiment of this application. Figure 2 ;

[0054] Figure 5 This is a schematic diagram of an electric gripper provided in an embodiment of this application. Figure 1 ;

[0055] Figure 6 This is a schematic diagram of an electric gripper provided in an embodiment of this application. Figure 2 ;

[0056] Figure 7 This is a schematic diagram of a material detection device based on a fixed base provided in an embodiment of this application;

[0057] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0058] To better understand the above-mentioned objectives, features, and advantages of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features of this application can be combined with each other. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0059] The terms “first” and “second”, etc., used in the specification and claims of this application are used to distinguish different objects, rather than to describe a specific order of objects.

[0060] The terms “comprising” and “having”, and any variations thereof, in this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0061] It should be noted that in the embodiments of this application, the words "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0062] Automated Guided Vehicles (AGVs), also known as automated guided vehicles, automated guided transport vehicles, or automated guided chassis, are transportation vehicles with autonomous driving capabilities. They navigate automatically to designated locations using specific landmarks to complete transportation tasks with high precision and without the need for human drivers. AGVs are used in warehousing, manufacturing, post offices, libraries, ports, and airports, and can be customized to suit different applications and operational needs. The main advantages of AGVs lie in their automation and intelligence. They can autonomously complete transportation tasks without human intervention, significantly improving work efficiency and reducing labor costs. Furthermore, AGVs achieve high-precision transportation through precise navigation and positioning, avoiding errors caused by human factors. In addition, AGVs are flexible and scalable, adapting to different operating environments and task requirements.

[0063] A robotic arm is a complex system characterized by high precision, multiple inputs and multiple outputs, high nonlinearity, and strong coupling. Due to its unique operational flexibility, it has been widely used in fields such as warehousing and material handling, industrial assembly, and safety and explosion protection. The robotic arm mentioned in this embodiment consists of six modular joints, each of which can move within a defined range according to a certain motion posture angle, and the joints move independently of each other.

[0064] By combining a traditional AGV chassis with a robotic arm, and mounting the robotic arm on the AGV chassis, the robotic arm essentially becomes "feet," while the AGV becomes "hands." The AGV's automatic movement, combined with the robotic arm's joint movements, allows for free guidance within a spatial range, with the robotic arm performing corresponding joint postures, thereby enabling various complex application scenarios. The automated guided vehicle (hereinafter referred to as AGV) mentioned in this application embodiment is equipped with a robotic arm for object gripping.

[0065] Objective image quality testing for cameras primarily involves using a mobile phone / tablet camera to capture images of various standard charts under specific environmental conditions (light source, color temperature) and then analyzing the image quality metrics of the photos. Traditional objective testing of mobile phone or tablet cameras mainly relies on manual labor in an objective laboratory, and the quality of the captured images directly affects the test results. For example, shooting angle, shooting distance, and shooting stability all affect image quality and ultimately the image quality metrics. Therefore, the need for automated camera testing is particularly important. One crucial aspect of automated testing is using machines to replace manual labor in taking photos, a process that requires no human intervention and avoids human interference. Currently, there are many automated camera shooting solutions on the market, each with its own characteristics. For example, some offer customized universal fixtures for specific product sizes. However, this requires staff to manually place the phone or tablet under test onto the fixture before each test, using a robotic arm to hold the fixture and secure the device for the test. This approach still requires manual clamping of each device, heavily relying on manual labor, resulting in a huge workload and potential issues such as incorrect placement and unstable clamping.

[0066] To address some or all of the aforementioned technical problems, this application provides a material detection method, apparatus, and fixed base based on a fixed base. The fixed base is equipped with a reflective strip to acquire a test image, which is obtained by a camera capturing the fixed base when the automated guided vehicle (AGV) is in a designated position. The AGV is equipped with a camera and a supplementary light. Image recognition is performed on the test image to extract the target light spot area. If the size of the detected target light spot area is smaller than a preset size, it is determined that an object to be tested exists on the fixed base. The preset size is the size of the reflective strip when the fixed base is in an empty state. This solution eliminates the need for manual operation; the movement of the object before and after testing is entirely replaced by the AGV. The robotic arm on the AGV can automatically grip the object, and before gripping, it can pre-determine whether there is an object at the designated position, greatly reducing the probability of the robotic arm damaging the test item or the base. This allows for uninterrupted material handling and improves testing efficiency.

[0067] like Figure 1 As shown, Figure 1 A flowchart of a material detection method based on a fixed base provided in this application embodiment, the method may include the following steps:

[0068] 101. Obtain the image to be tested.

[0069] The image to be tested is obtained by taking a picture of the fixed seat with a camera when the automated guided vehicle is in a designated position. The automated guided vehicle is equipped with a camera and a supplementary light, and the fixed seat is equipped with a reflective strip. The supplementary light can illuminate the fixed seat to reflect the light spot of the reflective strip.

[0070] In the embodiments of this application, such as Figure 2 As shown, the mounting base is used to place the object to be measured. A reflective strip is fixed inside the mounting base facing the channel. Figure 2 Area 21; after the material is discharged from the hopper, the object to be tested will appear on the fixed seat, such as... Figure 3 As shown, area 22 is the object to be tested, which can be a mobile phone or tablet. The robotic arm on the automated guided vehicle will grasp the object to be tested, remove it from the fixed seat, and perform subsequent imaging tests.

[0071] It should be noted that this designated position is pre-stored and corresponds to the position of the fixed seat. In other words, when the automated guided vehicle (AGV) is in this designated position, the camera can capture the fixed seat and the reflection. This camera can be mounted on the AGV's body or on its robotic arm.

[0072] 102. Perform image recognition on the image to be tested and extract the target spot area.

[0073] In this embodiment of the application, after acquiring the image to be tested, image recognition can be performed on the image to be tested. Since the mounting base is equipped with a reflective strip, when the mounting base is photographed, the position of the reflective strip will reflect light and produce a light spot in the image to be tested. Therefore, the position and size of the reflective strip can be indicated by the position and size of the light spot in the image to be tested.

[0074] In some embodiments, image recognition is performed on the image to be tested to extract the target spot region. Specifically, the image to be tested can be preprocessed as needed, including grayscale processing, noise reduction, contrast enhancement, etc., which can improve the visibility of the spot region. Then, the spot region and the background region can be distinguished by threshold segmentation. Since reflections (exposure) occur when shooting reflective strips, the pixel value of the area corresponding to the reflective strip will be greater than the pixel value of other background areas, and may even be close to the pixel value of white light. Therefore, a threshold close to the pixel value of white light can be preset for distinction, and the area composed of pixels with pixel values ​​greater than the threshold is determined as the target spot region.

[0075] Furthermore, morphological operations such as erosion and dilation can be performed on the target spot area to further clean and enhance its boundaries, helping to eliminate small noise points and smooth the boundaries. Then, contour detection algorithms (such as the Canny edge detection algorithm) can be used to extract the spot boundaries. Specifically, the boundaries are composed of pixels whose pixel values ​​differ from their adjacent pixels by a preset difference. Finally, post-processing can be performed on the extracted spot area, such as filling holes and smoothing boundaries, to obtain more accurate results.

[0076] It should be noted that the specific implementation method may vary depending on the specific image and requirements. The parameters and algorithms in the above steps can be adjusted according to the actual situation. In addition, specialized image processing libraries (such as OpenCV) can be used to simplify the implementation of this process, which will not be elaborated here.

[0077] 103. If the size of the target light spot area is smaller than the preset size, it is determined that there is an object to be measured on the fixed base.

[0078] In this embodiment, after extracting the target light spot area, the size information of the target light spot area can be determined. This size information is compared with preset size information, and the comparison result determines whether an object to be measured exists on the mounting base. The preset size information is the size information of the reflective strip when the mounting base is in an unoccupied state.

[0079] Specifically, since the thickness of a mobile phone or tablet is fixed, the reflector can be designed to be 1.5 to 2 times the product thickness. The presence of a device on the mounting base is determined by the height and area of ​​the light spot captured and detected by the vision camera. If a device such as a mobile phone is on the mounting base, the height of the detected light spot will be less than a threshold, which can be adjusted according to actual conditions; currently, it can be preset to 10mm. In other words, when the mounting base is empty (i.e., there is no device on it), the reflector strip is not obstructed, and the light spot area obtained by photographing the reflector strip can indicate the height, width, and area of ​​the entire reflector strip. However, if a device such as a mobile phone or tablet is placed on the mounting base, the reflector strip will be partially obstructed, and the light spot area obtained by photographing the reflector strip will be smaller. Therefore, the presence of a test object on the mounting base can be determined by the height, width, and area of ​​the light spot area.

[0080] In some embodiments, if the size information of the target light spot area is detected to be smaller than the preset size information, it is determined that there is an object to be measured on the fixture.

[0081] In some embodiments, if the size information of the target light spot area is detected to be equal to the preset size information, it is determined that there is no object to be measured on the fixture.

[0082] In some embodiments, in order to further improve the accuracy of determining whether an object to be measured exists, a preset difference can be set. Specifically, if the size information of the target light spot area is detected to be smaller than the preset size information, and the difference between the detected size information and the preset size information is greater than the preset difference, then it is determined that an object to be measured exists on the fixture.

[0083] The size information includes at least height and area information, and may also include width information.

[0084] It should be noted that there may be some deviation when the automated guided vehicle moves to the designated position, such as a difference of 5cm or a slight rotation; in addition, the position of the camera may also be off; and there may also be some errors during the image recognition process after the image to be captured. Therefore, it is possible that the fixed seat is empty, but the size of the target spot area is smaller than the preset size. However, the difference between the size and the preset size is not large. In this case, a misjudgment may occur, mistakenly believing that there is a target object on the fixed seat. Therefore, in order to further improve accuracy, a threshold can be set for the difference between the size information and the preset size information. Only when the difference is greater than the preset difference can it be said that the difference is caused by the placement of the target object on the fixed seat, and only then can it be confirmed that there is a target object on the fixed seat.

[0085] This application provides a material detection method based on a fixed base. The fixed base is equipped with a reflective strip to acquire a test image. The test image is obtained by a camera taking a picture of the fixed base when the automated guided vehicle (AGV) is in a designated position. The AGV is equipped with a camera and a supplementary light. Image recognition is performed on the test image to extract the target light spot area. If the size of the detected target light spot area is smaller than a preset size, it is determined that there is a test object on the fixed base. The preset size is the size of the reflective strip when the fixed base is in an empty state. With this solution, no manual operation is required. The movement of the test object before and after testing is completely replaced by the AGV. The robotic arm on the AGV can automatically grip the object. Before gripping, it can pre-determine whether there is an object at the designated position, greatly reducing the probability of the robotic arm damaging the test object or the base. This allows for uninterrupted material handling and improves testing efficiency.

[0086] like Figure 4 As shown, Figure 4 A flowchart of a material detection method based on a fixed base provided in this application embodiment, the method may further include the following steps:

[0087] 401. When the mounting base is in an unused state, take a picture of the mounting base with a camera to obtain a pre-configured image.

[0088] In this embodiment of the application, the automated guided vehicle needs to pre-configure the reflective strips on the fixed seat, that is, to ensure that the fixed seat is empty and unobstructed above, and to ensure that the reflective strips are intact. Then the automated guided vehicle moves to the designated position, uses a supplementary light to illuminate it, and takes a picture of the fixed seat with a camera to obtain a pre-configured image.

[0089] 402. Perform image recognition on the pre-configured image and extract the pre-configured spot area.

[0090] In this embodiment, the description of step 402 is the same as the detailed description of step 102 in the above embodiment. The method of extracting the pre-configured spot region from the pre-configured image and the method of extracting the target spot region from the image to be tested are the same, and will not be repeated in this embodiment.

[0091] 403. Determine the size information of the pre-configured light spot area as the preset size information.

[0092] In this embodiment of the application, the size information of the pre-configured spot area is determined, which may include height information and area information, and the size information of the pre-configured spot area is determined as the preset size information.

[0093] It should be noted that steps 401 to 403 above can be executed when the reflective strip is configured. Then, the preset size information will be stored in the server. The preset size information can be retrieved for judgment when clamping, testing, or placing any object in the future.

[0094] 404. Send the target location number to the automated guided vehicle so that the automated guided vehicle moves to the designated location according to the target location number.

[0095] In this embodiment, the automated guided vehicle (AGV) receives a movement command, determines its destination based on the command, generates a movement trajectory according to pre-stored map and route information, and moves to the destination along the trajectory. Therefore, to move the AGV to a designated location to clamp the object to be measured, a target location number can be sent to the AGV. This target location number corresponds to the designated location, allowing the AGV to automatically move to the designated location corresponding to that target location number.

[0096] In some embodiments, when the target hopper completes the discharge operation, the hopper positioning information of the target hopper is determined; the target location number corresponding to the hopper positioning information is determined based on the hopper positioning information, and the target location number is sent to the automated guided vehicle.

[0097] The correspondence between the hopper positioning information and the target location number is pre-stored, and the designated location corresponding to the target location number is the position of the fixed seat of the discharge port of the target hopper.

[0098] It's important to note that before using the AGV, map scanning and workstation setup are required. This is done manually by scanning the map based on the actual location on site and establishing workstations (each workstation has a unique and fixed number, such as "LM3" indicating the location of the hopper). This process only needs to be done once. Afterwards, the destination workstation is sent to the AGV, and the AGV can autonomously navigate to its destination according to the preset route. In other words, all workstations in the workshop are pre-planned, such as loading ports, conveyor belt entrances, unloading ports, hopper number one, hopper number two, etc., and each workstation is assigned a unique and fixed number. This way, you only need to tell the AGV the destination number, and the AGV can move automatically.

[0099] In some embodiments, when the object to be tested has left the warehouse, that is, the object to be tested has been processed and needs to be tested, the monitoring device will immediately determine the warehouse location information of the target warehouse where the object to be tested is located, and determine the target location number corresponding to the warehouse location information of the target warehouse according to the pre-stored correspondence between warehouse location information and location number. Then, it will promptly allocate AGVs, that is, determine the idle AGVs and send the target location number to the AGVs. After receiving the target location number, the AGV can move to the designated location according to the predetermined movement route. The designated location is the position of the fixed seat.

[0100] 405. When the automated guided vehicle is detected to be in the designated position, the image to be tested is acquired through the camera on the automated guided vehicle.

[0101] In some embodiments, when the automated guided vehicle is detected to be in a designated position, the auxiliary lights on the automated guided vehicle are turned on, and the image to be tested is acquired through the camera on the automated guided vehicle.

[0102] It should be noted that since the mounting base is equipped with reflective strips, supplementary lighting can be applied to the reflective strips when taking pictures of the images to improve the quality of the light spots in the images to be tested. In other words, supplementary lights will be installed on the automated guided vehicle.

[0103] 406. Perform image recognition on the image to be tested and extract the target spot area.

[0104] 407. If the size of the target light spot area is detected to be smaller than the preset size, it is determined that there is an object to be measured on the fixed base.

[0105] 408. Control the robotic arm of the automated guided vehicle to hold the object to be tested and perform imaging tests on the object.

[0106] In this embodiment, the robotic arm of the automated guided vehicle can only be controlled to grasp the object after it is confirmed that the object to be tested exists on the fixed base. Once the robotic arm of the automated guided vehicle has grasped the object, imaging testing can be performed on the object.

[0107] In some embodiments, the robotic arm of the automated guided vehicle may be equipped with an electric gripper, such as... Figure 5 The image shows a side view of the electric gripper. The electric gripper is equipped with an industrial camera, a gripping end, a collaborative robot hand, and a base, as shown below. Figure 6 As shown.

[0108] The industrial camera enables secondary positioning. The camera on the automated guided vehicle (AGV) determines that the object to be measured is on the fixed base. Then, the electric gripper on the robotic arm needs to further pinpoint the precise location of the object to ensure accurate gripping. The gripping end and the collaborative robot hand work together to hold the object. The base is used to secure the components and the object, and a laser rangefinder can be mounted on the base to detect the distance between the device and the object.

[0109] In some embodiments, after the robotic arm of the automated guided vehicle (AGV) grips the object to be tested, when the AGV is detected to have moved to the target test position, a standard image card is photographed through the object to be tested to obtain an image; the image is then analyzed to obtain the imaging result of the object to be tested.

[0110] In this embodiment of the application, after the robotic arm grips the object to be tested, it can perform imaging tests on the object. Specifically, it controls the automated guided vehicle to move the object to be tested to the target test position, and then controls the image to be captured by a standard image card through the object to be tested, thereby obtaining an image.

[0111] The target test location is a fixed position in the specific test space for the imaging test. The imaging test can only be carried out under specific conditions, so the test location is determined in advance.

[0112] In some embodiments, before photographing the standard chart through the object under test, the position and orientation of the object under test need to be pre-adjusted. Since the position of the standard chart is fixed, the position and orientation of the object under test can be adjusted based on the real-time imaging of the standard chart in the camera of the object under test, so that the standard chart is centered in the real-time imaging of the camera of the object under test after adjustment, and the specified FOV is met. Then, fine-tuning is required. Based on the fine-tuning information from the camera's viewfinder and focus, the posture of the robotic arm's end effector is adjusted according to the feedback fine-tuning information until the imaging test requirements are met.

[0113] In some embodiments, the imaging results are used to indicate the image quality of the object under test. If the imaging results indicate that the image quality of the object under test is poor, then the object under test may need to be reprocessed.

[0114] The material detection method based on a fixed base provided in this application embodiment requires no manual operation. The movement of the object to be tested before and after testing is completely replaced by an AGV. The robotic arm on the AGV can automatically grip the object. Before gripping, it can also pre-determine whether there is an object at a specified position, which greatly avoids the possibility of the robotic arm damaging the test item or the base. This allows for uninterrupted material handling and improves testing efficiency.

[0115] like Figure 7 As shown, this application embodiment provides a material detection device based on a fixed base, wherein a reflective strip is disposed on the fixed base, and the material detection device may include:

[0116] The acquisition module 701 is used to acquire the image to be tested. The image to be tested is obtained by taking a picture of the fixed seat by a camera when the automated guided vehicle is in a designated position. The automated guided vehicle is equipped with a camera and a supplementary light.

[0117] Processing module 702 is used to perform image recognition on the image under test and extract the target spot area;

[0118] The processing module 702 is also used to determine that there is an object to be measured on the fixed base if the size information of the detected target spot area is smaller than the preset size information. The preset size information is the size information of the reflective strip when the fixed base is in an empty state.

[0119] In some embodiments, the acquisition module 701 is further configured to take a picture of the fixed base with a camera when the fixed base is in an vacant state to obtain a pre-configured image;

[0120] The processing module 702 is also used to perform image recognition on the pre-configured image and extract the pre-configured spot area;

[0121] The processing module 702 is also used to determine the size information of the pre-configured spot area as preset size information.

[0122] In some embodiments, the processing module 702 is specifically used to determine that there is an object to be measured on the fixture if the size information of the target light spot area is detected to be smaller than the preset size information and the difference between the target light spot area and the preset size information is greater than the preset difference.

[0123] In some embodiments, the processing module 702 is specifically used to send a target location number to the automated guided vehicle, so that the automated guided vehicle moves to a designated location according to the target location number, wherein the target location number is the number corresponding to the designated location;

[0124] The acquisition module 701 is specifically used to acquire the image to be tested through the camera on the automated guided vehicle when the vehicle is detected to be in a designated position.

[0125] In some embodiments, the acquisition module 701 is specifically used to turn on the supplementary light on the automated guided vehicle when it is detected that the automated guided vehicle is in a designated position, and to acquire the image to be tested through the camera on the automated guided vehicle.

[0126] In some embodiments, the processing module 702 is specifically used to determine the hopper location information of the target hopper when the discharge operation of the target hopper is detected to be completed;

[0127] Processing module 702 is specifically used to determine the target location number corresponding to the hopper positioning information based on the hopper positioning information, and send the target location number to the automated guided vehicle;

[0128] The correspondence between the hopper positioning information and the target location number is pre-stored, and the designated location corresponding to the target location number is the position of the fixed seat of the discharge port of the target hopper.

[0129] In this embodiment, each module can implement the material detection method based on a fixed base provided in the above method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0130] like Figure 8 As shown in the illustration, this application also provides an electronic device, which may include:

[0131] Memory 801 storing executable program code;

[0132] Processor 802 coupled to memory 801;

[0133] Specifically, the processor 802 calls the executable program code stored in the memory 801 to execute the material detection method based on the fixed base executed by the electronic device in the above method embodiments.

[0134] This application provides a mounting base equipped with a reflective strip. The reflective strip is used to reflect light to form a light spot, so as to determine whether there is an object to be measured on the mounting base based on the size change of the light spot.

[0135] This application provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the fixed-base-based material detection method in the above-described method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0136] This application also provides a computer program product, which stores a computer program. When the computer program is executed by a processor, it implements each process of the fixed-base-based material detection method in the above-described method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0137] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code.

[0138] It should be understood, in the several embodiments provided in this application, that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0139] In this application, the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0140] In this application, memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, like read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0141] In this application, those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including permanent and non-permanent, removable and non-removable storage media. The storage medium can implement information storage by any method or technology, and the information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), other types of random access memory (RAM), read-only memory (ROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information that can be accessed by a computing device. As defined in this document, computer-readable media do not include transient media, such as modulated data signals and carrier waves.

[0142] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0143] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application. The above-mentioned multiple embodiments are not necessarily multiple independent embodiments; they are divided into multiple embodiments only to highlight different technical features in different embodiments. Those skilled in the art should understand that the above-mentioned multiple embodiments can also be combined arbitrarily.

[0144] In the various embodiments of this application, it should be understood that the sequence number of each process does not necessarily imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0145] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they can be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0146] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0147] If the aforementioned integrated units are implemented as software functional units and sold or used as independent products, they can be stored in a computer-accessible memory. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of this application.

[0148] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A material detection method based on a fixed base, characterized in that, The mounting base is equipped with a reflective strip, the height of which is greater than the product thickness. The method includes: Acquire a test image, which is obtained by taking a picture of the fixed seat with a camera when the automated guided vehicle is in a designated position. The automated guided vehicle is equipped with the camera and a supplementary light. Image recognition is performed on the image to be tested to extract the target spot region; When the mounting base is in an unused state, the camera takes a picture of the mounting base to obtain a pre-configured image; Perform image recognition on the pre-configured image to extract the pre-configured spot area; The size information of the pre-configured light spot area is determined to be the preset size information; If the size information of the target light spot area is detected to be smaller than the preset size information, and the difference between the target light spot area and the preset size information is greater than the preset difference, then it is determined that there is an object to be measured on the fixed base. The preset size information is the size information of the reflective strip when the fixed base is in an empty state. The size information includes at least: height information and area information.

2. The method according to claim 1, characterized in that, The acquisition of the image to be tested includes: Send a target location number to the automated guided vehicle so that the automated guided vehicle moves to the designated location according to the target location number, wherein the target location number is the number corresponding to the designated location; When the automated guided vehicle is detected to be at the designated location, the image to be tested is acquired by the camera on the automated guided vehicle.

3. The method according to claim 2, characterized in that, When the automated guided vehicle is detected to be at the designated position, acquiring the image to be tested via a camera on the automated guided vehicle includes: When the automated guided vehicle is detected to be at the designated position, the auxiliary lights on the automated guided vehicle are turned on, and the image to be tested is acquired through the camera on the automated guided vehicle.

4. The method according to claim 2, characterized in that, Sending the target location number to the automated guided vehicle includes: When the target hopper completes its discharge operation, the hopper location information of the target hopper is determined. The target location number corresponding to the hopper positioning information is determined based on the hopper positioning information, and the target location number is sent to the automated guided vehicle. The correspondence between the hopper positioning information and the target location number is pre-stored, and the designated location corresponding to the target location number is the position of the fixed seat of the discharge port of the target hopper.

5. A material detection device based on a fixed base, characterized in that, The mounting base is equipped with a reflective strip, the height of which is greater than the product thickness. The material detection device includes: The acquisition module is used to acquire the image to be tested, which is obtained by taking a picture of the fixed seat by a camera when the automated guided vehicle is in a designated position. The automated guided vehicle is equipped with the camera and a supplementary light. The processing module is used to perform image recognition on the image to be tested and extract the target spot area; The acquisition module is also used to take a picture of the fixed base with the camera when the fixed base is in an empty state to obtain a pre-configured image; The processing module is also used to perform image recognition on the pre-configured image and extract the pre-configured spot area; The processing module is further configured to determine the size information of the pre-configured spot area as preset size information; The processing module is further configured to determine that there is an object to be measured on the fixed base if the size information of the target light spot area is detected to be smaller than the preset size information and the difference between the target light spot area and the preset size information is greater than the preset difference. The preset size information is the size information of the reflective strip when the fixed base is in an empty state. The size information includes at least: height information and area information.

6. A fixing base, characterized in that, The mounting base is provided with a reflective strip, the height of which is greater than the thickness of the product. The reflective strip is used to reflect light to form a light spot, so as to determine whether there is an object to be tested on the mounting base based on the size change of the light spot. The mounting base is used to implement the material detection method as described in any one of claims 1-4.

7. An electronic device, characterized in that, include: Memory containing executable program code; and the processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the material detection method as described in any one of claims 1 to 4.

8. A computer-readable storage medium, characterized in that, include: The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the material detection method as described in any one of claims 1 to 4.

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