Scraper recognition and positioning method and device based on fusion of planar camera and sensor

Abstract

The disclosure provides a kind of based on planar camera and sensor fusion's scraper identification positioning method and device, the method comprises: first, the planar camera installed at the first fixed distance position above the center of distance from the scraper pile area is acquired on workpiece grab and gathers the scraper pile image;Second, based on image recognition module, according to the scraper pile image, determine the scraper information of the scraper to be grabbed;Then control workpiece grab drop, and according to the scraper information, control laser displacement sensor when workpiece grab is located at the second fixed distance position above the center point of the scraper to be grabbed Range finding;Finally, in the process of workpiece grab drop, in the case where the distance between workpiece grab and the scraper to be grabbed is equal to the preset value, control workpiece grab completes the scraper grabbing task.This embodiment combines planar camera and laser ranging sensor to realize scraper positioning, not only can effectively reduce technical cost, but also can realize the position identification and accurate positioning of scraper incoming material.

Description

Technical Field

[0001] This disclosure relates to the field of intelligent manufacturing technology, and more specifically, to a scraper identification and positioning method and apparatus based on the fusion of planar camera and sensor. Background Technology

[0002] As an important piece of industrial equipment, scraper conveyors rely heavily on the scraper components for efficient loading and unloading in automated production. Currently, scraper loading methods are mainly divided into manual and automated methods. However, manual operation presents challenges such as high labor intensity and operational risks, including the potential for scraper detachment during hoisting.

[0003] In response, related technologies have proposed using smarter automated methods to complete scraper loading. These automated methods utilize 3D intelligent cameras to identify the scraper's position, significantly improving operational safety and accurately acquiring the scraper's 3D coordinates. However, the high cost of the equipment and the complex operating procedures limit its widespread application. Furthermore, subsequent technical maintenance and scraper model updates also present considerable challenges and costs. Therefore, there is a need to find a smarter, more cost-effective, and safer solution to improve the efficiency and reliability of the scraper loading and unloading process. Summary of the Invention

[0004] This disclosure provides at least one method and apparatus for scraper identification and positioning based on the fusion of planar camera and sensor, which can not only effectively reduce technical costs, but also realize the position identification and accurate positioning of scraper material.

[0005] This disclosure provides a scraper identification and positioning method based on the fusion of planar camera and sensor, including:

[0006] The image of the scraper stack is acquired by a planar camera mounted on the workpiece gripper; the workpiece gripper is located at a first fixed distance above the center of the scraper stack area; the workpiece gripper is also equipped with a laser displacement sensor;

[0007] Based on the image recognition module, the scraper information of the scraper to be grabbed is determined according to the scraper stack image; the scraper information includes the center point coordinates of the scraper to be grabbed;

[0008] The workpiece gripper is controlled to descend, and the laser displacement sensor is controlled to measure the distance when the workpiece gripper is located at a second fixed distance above the center point of the scraper to be gripped, based on the scraper information.

[0009] During the descent of the workpiece gripper, when the distance between the workpiece gripper and the scraper to be gripped is equal to a preset value, the workpiece gripper is controlled to complete the scraper gripping task.

[0010] In some possible embodiments, prior to acquiring the scraper stack image captured by a planar camera mounted on the workpiece gripper, the process includes:

[0011] Different types of scrapers are stacked in their respective scraper stack areas according to preset standards, and the parameter information corresponding to each scraper type is sent to the image recognition module. The parameter information includes scraper type, scraper stack height, number of scraper stack layers, number of scrapers per layer, target number of scrapers, and scraper outline information.

[0012] The center point of each scraper stack area is determined based on the scraper stack area corresponding to each scraper, and a plane coordinate system is established using the center point of the area as the origin.

[0013] In some possible embodiments, the scraper information further includes angle information; the step of determining the scraper information of the scraper to be grasped based on the image recognition module according to the scraper stack image includes:

[0014] The image recognition module matches the image of the scraper stack with the outline information of the scraper corresponding to the scraper stack, and determines the scraper grasping order based on the matching result and the number of target scrapers.

[0015] The scraper to be grabbed is determined according to the scraper grabbing order, and the center point coordinates of the scraper to be grabbed are determined based on the planar coordinate system.

[0016] The angular offset of the scraper to be grabbed is determined based on the coordinates of the center point of the scraper to be grabbed, and the angle information is determined based on the determination result.

[0017] In some possible embodiments, determining the angle information based on the judgment result includes:

[0018] If the scraper to be grabbed has an angular offset, the angular offset value is calculated based on the center point coordinates of the scraper to be grabbed, and the angle information is determined based on the calculation result.

[0019] If there is no angular offset in the scraper to be grabbed, the angle information is zero.

[0020] In some possible embodiments, after determining the angle information based on the judgment result, the process includes:

[0021] Adjust the gripping angle of the workpiece gripper based on the angle information.

[0022] In some possible embodiments, before determining the scraper grabbing order based on the matching results and the target scraper quantity, the method further includes:

[0023] Determine whether the matching result and the target number of scrapers are the same;

[0024] If the matching result and the number of target scrapers are the same, the scraper grabbing order is determined according to a preset rule;

[0025] An alarm message is issued if the matching result and the target number of scrapers are not the same.

[0026] In some possible embodiments, after controlling the workpiece gripper to complete the scraper gripping task, the following steps are included:

[0027] The number of target scrapers corresponding to the scraper layer where the scraper to be identified is located is updated in the image recognition module based on the completion result.

[0028] This disclosure provides a scraper identification and positioning device based on the fusion of a planar camera and sensors, including:

[0029] The image acquisition module is used to acquire images of the scraper stack captured by a planar camera mounted on the workpiece gripper; the workpiece gripper is located at a first fixed distance above the center of the scraper stack area; the workpiece gripper is also equipped with a laser displacement sensor;

[0030] The information determination module is used to determine the scraper information of the scraper to be grasped based on the scraper stack image, according to the image recognition module; the scraper information includes the center point coordinates of the scraper to be grasped.

[0031] The distance measurement module is used to control the workpiece gripper to descend, and according to the scraper information, to control the laser displacement sensor to measure the distance when the workpiece gripper is located at a second fixed distance above the center point of the scraper to be gripped.

[0032] The scraper gripping module is used to control the workpiece gripper to complete the scraper gripping task when the distance between the workpiece gripper and the scraper to be gripped is equal to a preset value during the descent of the workpiece gripper.

[0033] In some possible embodiments, the image acquisition module is further configured to:

[0034] Different types of scrapers are stacked in their respective scraper stack areas according to preset standards, and the parameter information corresponding to each scraper type is sent to the image recognition module. The parameter information includes scraper type, scraper stack height, number of scraper stack layers, number of scrapers per layer, target number of scrapers, and scraper outline information.

[0035] The center point of each scraper stack area is determined based on the scraper stack area corresponding to each scraper, and a plane coordinate system is established using the center point of the area as the origin.

[0036] In some possible embodiments, the scraper information further includes angle information; the information determination module is specifically used for:

[0037] The image recognition module matches the image of the scraper stack with the outline information of the scraper corresponding to the scraper stack, and determines the scraper grasping order based on the matching result and the number of target scrapers.

[0038] The scraper to be grabbed is determined according to the scraper grabbing order, and the center point coordinates of the scraper to be grabbed are determined based on the planar coordinate system.

[0039] The angular offset of the scraper to be grabbed is determined based on the coordinates of the center point of the scraper to be grabbed, and the angle information is determined based on the determination result.

[0040] In some possible embodiments, the information determination module is further configured to:

[0041] If the scraper to be grabbed has an angular offset, the angular offset value is calculated based on the center point coordinates of the scraper to be grabbed, and the angle information is determined based on the calculation result.

[0042] If there is no angular offset in the scraper to be grabbed, the angle information is zero.

[0043] In some possible embodiments, the information determination module is further configured to:

[0044] Adjust the gripping angle of the workpiece gripper based on the angle information.

[0045] In some possible embodiments, the information determination module is further configured to:

[0046] Determine whether the matching result and the target number of scrapers are the same;

[0047] If the matching result and the number of target scrapers are the same, the scraper grabbing order is determined according to a preset rule;

[0048] An alarm message is issued if the matching result and the target number of scrapers are not the same.

[0049] In some possible embodiments, the scraper gripping module is further configured to:

[0050] The number of target scrapers corresponding to the scraper layer where the scraper to be identified is located is updated in the image recognition module based on the completion result.

[0051] This disclosure provides a computer device, including a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the computer device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the scraper recognition and positioning method based on planar camera and sensor fusion as described in any of the above possible embodiments.

[0052] This disclosure provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the scraper identification and positioning method based on planar camera and sensor fusion as described in any of the above possible embodiments.

[0053] The scraper identification and positioning method and apparatus based on planar camera and sensor fusion provided in this disclosure embodiment, by installing a planar camera and a laser rangefinder on the workpiece gripper, uses the planar camera to acquire images of the scraper stack to analyze the scraper information of the scraper to be gripped, and then uses the laser rangefinder to achieve the positioning of the scraper to be gripped. This not only effectively reduces technical costs but also enables precise identification and positioning of the scraper's incoming material position.

[0054] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings referenced in the embodiments will be briefly described below. These drawings are incorporated in and constitute a part of this specification. They illustrate embodiments conforming to this disclosure and, together with the specification, serve to explain the technical solutions of this disclosure. It should be understood that the following drawings only show some embodiments of this disclosure and should not be considered as limiting the scope. Those skilled in the art can obtain other related drawings based on these drawings without creative effort.

[0056] Figure 1 A flowchart of a scraper identification and positioning method based on the fusion of a planar camera and a sensor provided in an embodiment of this disclosure is shown;

[0057] Figure 2 This diagram illustrates the workpiece gripping position in the scraper recognition and positioning method based on planar camera and sensor fusion provided in this embodiment of the present disclosure.

[0058] Figure 3 This illustration shows a schematic diagram of planar camera image acquisition in the scraper recognition and positioning method based on planar camera and sensor fusion provided in the embodiments of this disclosure;

[0059] Figure 4 The flowchart of the image recognition method in the scraper recognition and positioning method based on the fusion of planar camera and sensor provided in the embodiments of this disclosure is shown.

[0060] Figure 5 The diagram shows a workpiece gripper located at a second fixed position in the scraper recognition and positioning method based on planar camera and sensor fusion provided in this embodiment of the present disclosure.

[0061] Figure 6 This diagram illustrates the structure of a scraper identification and positioning device based on the fusion of a planar camera and a sensor, according to an embodiment of this disclosure.

[0062] Figure 7 A schematic diagram of the structure of a computer device provided in an embodiment of this disclosure is shown. Detailed Implementation

[0063] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. The components of the embodiments of this disclosure described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this disclosure provided in the accompanying drawings is not intended to limit the scope of the claimed disclosure, but merely represents selected embodiments of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0064] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0065] In this document, the term "and / or" merely describes a relationship, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" in this document means any combination of at least two of any one or more elements. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set consisting of A, B, and C.

[0066] As an important piece of industrial equipment, scraper conveyors rely heavily on the scraper's loading and unloading process for automated production. Research has revealed that scraper loading methods in related technologies are mainly divided into manual and automated methods. However, manual operation presents challenges due to high labor intensity and operational risks, particularly the significant safety hazard of scraper detachment during hoisting.

[0067] To address the problems associated with manual operation, related technologies propose using more intelligent automated methods for scraper feeding. These automated methods utilize 3D intelligent cameras to identify the scraper's position and perform precise 3D coordinate positioning, significantly improving operational safety and accuracy. This not only reduces safety risks associated with manual operation but also increases production efficiency and accuracy, meeting the demands of modern industry for highly efficient automated production. However, despite the numerous advantages of automation, its high equipment costs and complex operating procedures limit its widespread adoption in practical applications. Furthermore, subsequent technical maintenance and scraper model updates also present considerable challenges and costs.

[0068] Based on the above research, this disclosure provides a scraper identification and positioning method and apparatus based on the fusion of a planar camera and a sensor. First, a scraper stack image is acquired by a planar camera mounted on a workpiece gripper at a first fixed distance above the center of the scraper stack area. Second, based on the image recognition module, the scraper information of the scraper to be gripped is determined according to the scraper stack image. Then, the workpiece gripper is controlled to descend, and a laser displacement sensor is controlled to measure the distance when the workpiece gripper is located at a second fixed distance above the center point of the scraper to be gripped, according to the scraper information. Finally, during the descent of the workpiece gripper, when the distance between the workpiece gripper and the scraper to be gripped is equal to a preset value, the workpiece gripper is controlled to complete the scraper gripping task.

[0069] In this embodiment, a planar camera and a laser rangefinder are mounted on the workpiece gripper. The planar camera acquires images of the scraper stack to analyze the scraper information of the scraper to be gripped, and then the laser rangefinder is used to locate the scraper to be gripped. In this way, using a planar camera instead of the 3D intelligent camera in related technologies can effectively reduce technical costs; and by combining the planar camera and the laser rangefinder, it is also possible to achieve position recognition and precise positioning of the incoming scraper material.

[0070] To facilitate understanding of this embodiment, the executing entity of the scraper recognition and positioning method based on planar camera and sensor fusion provided in this disclosure will first be described in detail. The executing entity of the scraper recognition and positioning method based on planar camera and sensor fusion provided in this disclosure is a computer device. This computer device can be a server. Specifically, the server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud storage, big data, and artificial intelligence platforms.

[0071] The scraper recognition and positioning method based on the fusion of planar camera and sensor provided in this application will be described in detail below with reference to the accompanying drawings. See also Figure 1 The diagram shows a flowchart of a scraper identification and positioning method based on the fusion of a planar camera and a sensor, according to an embodiment of this disclosure. The method includes the following steps S101 to S104:

[0072] S101, acquire the scraper stack image captured by the planar camera installed on the workpiece gripper; the workpiece gripper is located at a first fixed distance above the center of the scraper stack area; the workpiece gripper is also equipped with a laser displacement sensor.

[0073] Understandably, planar cameras are primarily used to acquire high-resolution images on a flat surface. Unlike 3D intelligent cameras in related technologies, they focus on capturing two-dimensional images on a plane, rather than objects in three-dimensional space. The planar camera is mounted on the workpiece gripper using a follow-along installation method, ensuring that the camera moves with the gripper, thus better capturing images of the scraper stack without causing image distortion or excessive changes in viewing angle.

[0074] Specifically, refer to Figure 2-3 As shown in this embodiment, the workpiece gripper A, equipped with a planar camera B, is positioned 1.6 meters above the center of the scraper stack area C, thus acquiring images of the scraper stack D. In some other embodiments, the distance value of the first fixed distance position can be determined based on the camera parameters of the planar camera, such as 1.2 meters or 1.8 meters, etc., and is not specifically limited here.

[0075] Here, the workpiece gripper is also equipped with a laser displacement sensor. The laser displacement sensor is a high-precision measuring device, mainly used to measure the minute displacement of the object surface. It uses the interference principle of laser to measure distance and can provide very accurate distance data.

[0076] For example, before acquiring the scraper stack image captured by a planar camera mounted on the workpiece gripper, the following (1) to (2) may be included:

[0077] (1) Stack different types of scrapers in their respective scraper stack areas according to preset standards, and send the parameter information corresponding to each type of scraper to the image recognition module;

[0078] (2) Determine the center point of the region based on the scraper stack area corresponding to each scraper, and establish a plane coordinate system with the center point of the region as the origin.

[0079] Understandably, when different models of scrapers are received into the warehouse, they can be stacked according to preset standards in their respective fixed scraper stack areas. Simultaneously, the parameter information corresponding to each scraper model is sent to the image recognition module for storage and management. This parameter information can include the scraper model, scraper stack height, number of scraper stack layers, number of scrapers per layer, target scraper quantity, and scraper outline information. The target scraper quantity refers to the number of scrapers in the scraper stack to be grabbed, and its initial value is equal to the number of scrapers per layer in the initially stacked scraper stack. When the workpiece gripper begins to grab the scrapers from the scraper stack, the image recognition module updates the target scraper quantity in real time based on the completion result of the grabbing task, reflecting the completion status of the grabbing task and the current state of the scraper stack.

[0080] Among them, the height of the scraper stack and the number of scraper stack layers are used to determine the distance between the workpiece gripper and the surface of the scraper stack. Specifically, during image acquisition, the formula for determining the distance between the workpiece gripper and the surface of the scraper stack is expressed as follows:

[0081] L1 = h × n + l1;

[0082] Where L1 represents the distance between the workpiece gripper and the scraper stack during image acquisition; h represents the height of the scraper stack; n represents the number of scraper stack layers; and l1 represents the first fixed distance.

[0083] Simultaneously, after the scrapers are stacked, the center point of each scraper stack area is determined, and a planar coordinate system is established using this center point as the origin. Determining the center point typically involves calculating the geometric center or centroid of each scraper stack area. Once the center point is determined, a planar camera can use it as a reference for image acquisition. By establishing a planar coordinate system, the position and orientation of each scraper on the plane can be accurately calculated and described.

[0084] S102, Based on the image recognition module, determine the scraper information of the scraper to be grabbed according to the scraper stack image; the scraper information includes the center point coordinates of the scraper to be grabbed.

[0085] Understandably, the scraper information includes the center point coordinates and angle information of the scraper to be grasped. After acquiring the scraper stack image, an image recognition module is used to perform image recognition on the scraper stack image to obtain the scraper information for the scraper to be grasped. Specifically, refer to... Figure 4The diagram shown is a flowchart of an image recognition method provided in an embodiment of this disclosure. The method includes the following steps S1021 to S1023:

[0086] S1021, Based on the image recognition module, the scraper stack image and the scraper contour information corresponding to the scraper stack are matched, and the scraper grasping order is determined based on the matching result and the number of target scrapers.

[0087] Here, based on the image recognition module, the stored scraper contour information corresponding to the scraper stack is matched with the acquired scraper stack image to obtain the number of scrapers in the layer to be grasped in the scraper stack. The matched number of scrapers is then compared with the target number of scrapers to determine whether the matching result and the target number of scrapers are the same. If they are the same, the scraper grasping order is determined according to preset rules (e.g., grasping from left to right or from right to left). If they are not the same, an alarm message is issued to notify the relevant operators to check and intervene.

[0088] S1022, determine the scraper to be grabbed according to the scraper grabbing order, and determine the center point coordinates of the scraper to be grabbed based on the plane coordinate system.

[0089] Understandably, after determining the scraper to be gripped according to the scraper gripping sequence, the center point coordinates of the scraper to be gripped are determined based on the established planar coordinate system to ensure that the workpiece gripper can be accurately positioned to the ideal gripping position of the scraper.

[0090] S1023, determine whether there is an angular offset of the scraper to be grabbed based on the center point coordinates of the scraper to be grabbed, and determine the angle information based on the judgment result.

[0091] Specifically, after obtaining the center point coordinates of the scraper to be gripped, the system uses these coordinates to determine if there is an angular offset by comparing them with the vertical direction of the x-axis or y-axis in the planar coordinate system. This angular offset may be due to irregular material stacking or minor errors in operator operation. If an angular offset exists, the offset value can be calculated based on the center point coordinates of the scraper. Specific methods may include using the arctangent function to calculate the offset angle. After determining the angle information based on the calculation results, the gripping angle of the workpiece clamp is adjusted to ensure that subsequent gripping operations can grip the scraper at the correct angle, thus guaranteeing accuracy and stability during operation. If there is no angular offset in the scraper, it indicates that the scraper is in the ideal gripping position, and its angle information is zero, therefore no further adjustment of the workpiece clamp's gripping angle is needed.

[0092] In this way, the angular deviation of the scraper to be grabbed can be effectively handled, ensuring the precise positioning and accurate grabbing of the scraper during the operation, thereby improving efficiency and reliability.

[0093] S103, control the workpiece gripper to descend, and according to the scraper information, control the laser displacement sensor to measure the distance when the workpiece gripper is located at a second fixed distance above the center point of the scraper to be gripped.

[0094] Here, after acquiring the scraper information, as the workpiece gripper descends, it is moved to a position above the center point of the scraper to be gripped, based on the scraper information. At a second fixed distance above the center point of the scraper, the laser displacement sensor is controlled to measure the distance. This second fixed position can be specifically set according to the laser displacement sensor; for example, it could be 0.5m, 0.8m, etc., but is not specifically set here.

[0095] For example, similar to the method in step S101 above, the distance between the workpiece gripper and the center point of the scraper to be gripped is determined using the scraper stack height and the number of scraper stack layers. The formula is expressed as follows:

[0096] L2 = h × n + l2;

[0097] Where L2 represents the distance between the workpiece gripper and the center point of the scraper to be gripped; h represents the height of the scraper stack; n represents the number of scraper stacks; and l2 represents the second fixed distance.

[0098] Reference Figure 5 As shown in this embodiment, the value of the second fixed position is set to 0.5m, that is, when the workpiece gripper A is located 0.5m above the center point of the scraper E to be gripped, the laser displacement sensor starts to measure the distance.

[0099] S104, during the descent of the workpiece gripper, when the distance between the workpiece gripper and the scraper to be gripped is equal to a preset value, the workpiece gripper is controlled to complete the scraper gripping task.

[0100] Understandably, during the descent of the workpiece gripper, a laser displacement sensor continuously measures the distance until the distance between the workpiece gripper and the scraper to be gripped equals a preset value. At this point, the workpiece gripper stops descending and triggers the corresponding gripping action to complete the scraper gripping task. Then, based on the completion result, the number of target scrapers corresponding to the scraper layer where the scraper to be identified is located is updated in the image recognition module. Here, the preset distance can be set according to the parameter information of the workpiece gripper or the size of the scraper to be gripped, and is not specifically limited here.

[0101] The scraper identification and positioning method and apparatus based on planar camera and sensor fusion provided in this disclosure involves installing a planar camera and a laser rangefinder on the workpiece gripper. The planar camera acquires images of the scraper stack to analyze the scraper information of the scraper to be gripped, and then the laser rangefinder is used to locate the scraper to be gripped. In this way, using a planar camera instead of the 3D intelligent camera in related technologies can effectively reduce technical costs, shorten the required time, and lower the technical threshold, which is conducive to the promotion and application of the technology. Furthermore, by combining the planar camera and the laser rangefinder, it is also possible to achieve position identification and precise positioning of the incoming scraper material.

[0102] Those skilled in the art will understand that, in the above-described method of the specific implementation, the order in which each step is written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of each step should be determined by its function and possible internal logic.

[0103] Based on the same inventive concept, this disclosure also provides a scraper identification and positioning device based on planar camera and sensor fusion, which corresponds to the scraper identification and positioning method based on planar camera and sensor fusion. Since the principle of the device in this disclosure is similar to the scraper identification and positioning method based on planar camera and sensor fusion described above, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0104] Reference Figure 6 The diagram shown is a schematic of a scraper identification and positioning device 600 based on the fusion of a planar camera and a sensor, according to an embodiment of this disclosure. The device includes:

[0105] The image acquisition module 601 is used to acquire images of the scraper stack captured by a planar camera mounted on the workpiece gripper; the workpiece gripper is located at a first fixed distance above the center of the scraper stack area; the workpiece gripper is also equipped with a laser displacement sensor;

[0106] The information determination module 602 is used to determine the scraper information of the scraper to be grasped based on the scraper stack image by the image recognition module; the scraper information includes the center point coordinates of the scraper to be grasped;

[0107] The distance measurement module 603 is used to control the workpiece gripper to descend and, based on the scraper information, control the laser displacement sensor to measure the distance when the workpiece gripper is located at a second fixed distance above the center point of the scraper to be gripped.

[0108] The scraper gripping module 604 is used to control the workpiece gripper to complete the scraper gripping task when the distance between the workpiece gripper and the scraper to be gripped is equal to a preset value during the descent of the workpiece gripper.

[0109] In some possible embodiments, the image acquisition module 601 is further configured to:

[0110] Different types of scrapers are stacked in their respective scraper stack areas according to preset standards, and the parameter information corresponding to each scraper type is sent to the image recognition module. The parameter information includes scraper type, scraper stack height, number of scraper stack layers, number of scrapers per layer, target number of scrapers, and scraper outline information.

[0111] The center point of each scraper stack area is determined based on the scraper stack area corresponding to each scraper, and a plane coordinate system is established using the center point of the area as the origin.

[0112] In some possible embodiments, the scraper information further includes angle information; the information determination module 602 is specifically used for:

[0113] The image recognition module matches the image of the scraper stack with the outline information of the scraper corresponding to the scraper stack, and determines the scraper grasping order based on the matching result and the number of target scrapers.

[0114] The scraper to be grabbed is determined according to the scraper grabbing order, and the center point coordinates of the scraper to be grabbed are determined based on the planar coordinate system.

[0115] The angular offset of the scraper to be grabbed is determined based on the coordinates of the center point of the scraper to be grabbed, and the angle information is determined based on the determination result.

[0116] In some possible embodiments, the information determination module 602 is further configured to:

[0117] If the scraper to be grabbed has an angular offset, the angular offset value is calculated based on the center point coordinates of the scraper to be grabbed, and the angle information is determined based on the calculation result.

[0118] If there is no angular offset in the scraper to be grabbed, the angle information is zero.

[0119] In some possible embodiments, the information determination module 602 is further configured to:

[0120] Adjust the gripping angle of the workpiece gripper based on the angle information.

[0121] In some possible embodiments, the information determination module 602 is further configured to:

[0122] Determine whether the matching result and the target number of scrapers are the same;

[0123] If the matching result and the number of target scrapers are the same, the scraper grabbing order is determined according to a preset rule;

[0124] An alarm message is issued if the matching result and the target number of scrapers are not the same.

[0125] In some possible embodiments, the scraper gripping module 604 is further configured to:

[0126] The number of target scrapers corresponding to the scraper layer where the scraper to be identified is located is updated in the image recognition module based on the completion result.

[0127] Based on the same technical concept, this disclosure also provides a computer device. (See also...) Figure 7 The diagram shows the structure of a computer device 700 provided in this embodiment of the present disclosure, including a processor 701, a memory 702, and a bus 703. The memory 702 stores execution instructions and includes a main memory 7021 and an external memory 7022. The main memory 7021, also called internal memory, is used to temporarily store computational data in the processor 701, as well as data exchanged with external memory 7022 such as a hard disk. The processor 701 exchanges data with the external memory 7022 through the main memory 7021.

[0128] In this embodiment, the memory 702 is specifically used to store application code that executes the solution of this application, and its execution is controlled by the processor 701. That is, when the computer device 700 is running, the processor 701 communicates with the memory 702 through the bus 703, so that the processor 701 executes the application code stored in the memory 702, and then executes the method described in any of the foregoing embodiments.

[0129] The memory 702 may be, but is not limited to, random access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0130] Processor 701 may be an integrated circuit chip with signal processing capabilities. The aforementioned processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor.

[0131] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the computer device 700. In other embodiments of this application, the computer device 700 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0132] This disclosure also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs the steps of the scraper identification and positioning method based on the fusion of a planar camera and sensor described in the above-described method embodiments. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0133] This disclosure also provides a computer program product carrying program code. The program code includes instructions that can be used to execute the steps of the scraper identification and positioning method based on the fusion of planar camera and sensor described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0134] The aforementioned computer program product can be implemented through hardware, software, or a combination thereof. In one optional embodiment, the computer program product is specifically embodied in a computer storage medium; in another optional embodiment, the computer program product is specifically embodied in a software product, such as a software development kit (SDK), etc.

[0135] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems and devices described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. In the several embodiments provided in this disclosure, it should be understood that the disclosed systems and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Another point is that the displayed or discussed mutual coupling or direct coupling or communication connection may be through some communication interfaces; the indirect coupling or communication connection of devices or units may be electrical, mechanical, or other forms.

[0136] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may 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.

[0137] In addition, the functional units in the various embodiments of this disclosure 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.

[0138] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0139] Finally, it should be noted that the above-described embodiments are merely specific implementations of this disclosure, used to illustrate the technical solutions of this disclosure, and not to limit it. The protection scope of this disclosure is not limited thereto. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features, within the scope of the technology disclosed in this disclosure. Such modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure, and should all be covered within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the protection scope of the claims.

Claims

1. A scraper recognition and positioning method based on the fusion of planar camera and sensor, characterized in that, include: Different models of scrapers are stacked in their respective scraper stack areas according to preset standards, and the parameter information corresponding to each model of scraper is sent to the image recognition module. Furthermore, the center point of each scraper stack is determined based on the scraper stack area corresponding to each scraper, and a plane coordinate system is established using the center point of the area as the origin; the parameter information includes scraper model, scraper stack height, number of scraper stack layers, number of scrapers per layer, number of target scrapers, and scraper outline information; The image of the scraper stack is acquired by a planar camera mounted on the workpiece gripper; the workpiece gripper is located at a first fixed distance above the center of the scraper stack area; the workpiece gripper is also equipped with a laser displacement sensor; The image recognition module matches the image of the scraper stack with pre-stored scraper contour information corresponding to the scraper stack, and determines the scraper grasping order based on the matching result and the number of target scrapers; and determines the scraper to be grasped according to the scraper grasping order, and determines the center point coordinates of the scraper to be grasped based on the planar coordinate system; and determines whether the scraper to be grasped has an angular offset based on the center point coordinates of the scraper to be grasped, and determines the angle information based on the judgment result. The workpiece gripper is controlled to descend, and the laser displacement sensor is controlled to measure the distance when the workpiece gripper is located at a second fixed distance above the center point of the scraper to be gripped, based on the center point coordinates and the angle information. During the descent of the workpiece gripper, when the distance between the workpiece gripper and the scraper to be gripped is equal to a preset value, the workpiece gripper is controlled to complete the scraper gripping task.

2. The method according to claim 1, characterized in that, The determination of angle information based on the judgment result includes: If the scraper to be grabbed has an angular offset, the angular offset value is calculated based on the center point coordinates of the scraper to be grabbed, and the angle information is determined based on the calculation result. If there is no angular offset in the scraper to be grabbed, the angle information is zero.

3. The method according to claim 2, characterized in that, After determining the angle information based on the judgment result, it includes: Adjust the gripping angle of the workpiece gripper based on the angle information.

4. The method according to claim 1, characterized in that, Before determining the scraper grabbing order based on the matching results and the number of target scrapers, the process also includes: Determine whether the matching result and the target number of scrapers are the same; If the matching result and the number of target scrapers are the same, the scraper grabbing order is determined according to a preset rule; An alarm message is issued if the matching result and the target number of scrapers are not the same.

5. The method according to claim 4, characterized in that, After the workpiece gripper completes the scraper gripping task, the following steps are taken: The number of target scrapers corresponding to the scraper layer where the scraper to be identified is located is updated in the image recognition module based on the completion results.

6. A scraper identification and positioning device based on the fusion of a planar camera and a sensor, characterized in that, include: The parameter determination module is used to stack different models of scrapers in their respective scraper stack areas according to preset standards, and send the parameter information corresponding to each model of scraper to the image recognition module. Furthermore, the center point of each scraper stack is determined based on the scraper stack area corresponding to each scraper, and a plane coordinate system is established using the center point of the area as the origin; the parameter information includes scraper model, scraper stack height, number of scraper stack layers, number of scrapers per layer, number of target scrapers, and scraper outline information; The image acquisition module is used to acquire images of the scraper stack captured by a planar camera mounted on the workpiece gripper; the workpiece gripper is located at a first fixed distance above the center of the scraper stack area; the workpiece gripper is also equipped with a laser displacement sensor; The information determination module is used to match the image of the scraper stack with pre-stored scraper contour information corresponding to the scraper stack based on the image recognition module, and determine the scraper grasping order based on the matching result and the number of target scrapers; and to determine the scraper to be grasped according to the scraper grasping order, and determine the center point coordinates of the scraper to be grasped based on the planar coordinate system; and to determine whether the scraper to be grasped has an angular offset based on the center point coordinates of the scraper to be grasped, and determine the angle information based on the determination result. The distance measurement module is used to control the workpiece gripper to descend, and to control the laser displacement sensor to measure the distance when the workpiece gripper is located at a second fixed distance above the center point of the scraper to be gripped, based on the center point coordinates and the angle information. The scraper gripping module is used to control the workpiece gripper to complete the scraper gripping task when the distance between the workpiece gripper and the scraper to be gripped is equal to a preset value during the descent of the workpiece gripper.

7. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 5.

8. A computer device, comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 5.

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