Mechanical arm posture measurement offset calibration method and device and electronic equipment

Abstract

The invention discloses a mechanical arm posture measurement offset calibration method and device, electronic equipment and a computer storage medium. The method comprises the steps that a digital twin model corresponding to mechanical equipment is obtained; adjusting the attitude of a target mechanical arm on the mechanical equipment, and obtaining first attitude information obtained by performing attitude measurement on the target mechanical arm subjected to attitude adjustment by target measurement equipment; the posture of a corresponding target virtual mechanical arm on the digital twin model is adjusted to be consistent with the posture of the adjusted target mechanical arm, and when the posture of the target virtual mechanical arm is consistent with the posture of the target mechanical arm, second posture information of the target virtual mechanical arm in the digital twin model is obtained; and according to the first attitude information and the second attitude information, the measurement offset of the target measurement equipment to the attitude of the target mechanical arm is determined. According to the method, calibration of the measurement offset of the posture of the mechanical arm can be automatically completed without manual participation, and the calibrated measurement offset is more accurate.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular, to a method, device, electronic device, and computer-readable storage medium for calibrating the measurement offset of a robotic arm attitude. Background Art

[0002] Currently, the accurate measurement of the attitude of a loader robotic arm is a prerequisite for the autonomous operation of an unmanned loader. Generally, an IMU (Inertial Measurement Unit) sensor deployed on the loader is used to sense the attitude of the loader robotic arm. However, since the IMU sensor is affected by various factors in actual use, there is a certain offset in the measurement of the robotic arm attitude. Therefore, before calibrating the attitude of the robotic arm using the IMU sensor, the measurement offset of the IMU sensor is usually calibrated to improve the accuracy of the IMU measurement data, so as to more accurately calibrate the attitude of the loader robotic arm.

[0003] In the related art, it is necessary to manually lift the loader robotic arm to a horizontal position, that is, to observe the angle of the robotic arm with the human eye as 0 degrees, record the readings of the IMU sensor when the loader robotic arm is manually judged to be in a horizontal state, and calculate the difference between the angle measurement data of the IMU sensor and 0 degrees as the measurement offset of the IMU sensor for the robotic arm attitude. However, this method depends on the judgment of the calibrator on "lifting the robotic arm to a horizontal position", which is greatly affected by personal subjective factors, and this requires professional personnel to operate to complete the calibration of the measurement offset, which cannot meet the efficiency and cost requirements for large-scale delivery of unmanned loaders.

[0004] Therefore, there is an urgent need for an automatic method for calibrating the robotic arm attitude to automatically complete the calibration of the measurement offset of the IMU sensor without manual participation, so as to more accurately calibrate the attitude of the loader robotic arm. Summary of the Invention

[0005] This application provides a method, device, electronic device, and computer-readable storage medium for calibrating the measurement offset of a robotic arm attitude, so as to provide a method for automatically calibrating the measurement offset of a robotic arm attitude without manual participation, thereby more accurately calibrating the attitude of a loader robotic arm.

[0006] In a first aspect, an embodiment of this application provides a method for calibrating the measurement offset of a robotic arm attitude, and the method includes:

[0007] Obtain the digital twin model corresponding to the mechanical equipment, where each virtual robotic arm on the digital twin model corresponds one-to-one with each robotic arm on the mechanical equipment, and the postures of the virtual robotic arms on the digital twin model are consistent with the initial postures of the corresponding robotic arms on the mechanical equipment;

[0008] Adjust the posture of the target robotic arm on the mechanical equipment, and obtain the first posture information obtained by the target measuring device measuring the posture of the target robotic arm after the posture adjustment;

[0009] Adjust the posture of the corresponding target virtual robotic arm on the digital twin model to be consistent with the posture of the adjusted target robotic arm, and when the postures of the target virtual robotic arm and the target robotic arm are consistent, obtain the second posture information of the target virtual robotic arm in the digital twin model;

[0010] Determine the measurement offset of the target measuring device for the posture of the target robotic arm according to the first posture information and the second posture information.

[0011] In a second aspect, an embodiment of the present application provides a device for calibrating the measurement offset of a robotic arm posture, and the device includes:

[0012] An acquisition module, configured to acquire the digital twin model corresponding to the mechanical equipment, where each virtual robotic arm on the digital twin model corresponds one-to-one with each robotic arm on the mechanical equipment, and the postures of the virtual robotic arms on the digital twin model are consistent with the initial postures of the corresponding robotic arms on the mechanical equipment;

[0013] An adjustment module, configured to adjust the posture of the target robotic arm on the mechanical equipment, and obtain the first posture information obtained by the target measuring device measuring the posture of the target robotic arm after the posture adjustment;

[0014] A processing module, configured to adjust the posture of the corresponding target virtual robotic arm on the digital twin model to be consistent with the posture of the adjusted target robotic arm, and when the postures of the target virtual robotic arm and the target robotic arm are consistent, obtain the second posture information of the target virtual robotic arm in the digital twin model;

[0015] A determination module, configured to determine the measurement offset of the target measuring device for the posture of the target robotic arm according to the first posture information and the second posture information.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, and the electronic device includes:

[0017] A memory and a processor, and the memory and the processor are coupled;

[0018] The memory is used to store one or more computer instructions;

[0019] The processor is used to execute the one or more computer instructions to implement the method for calibrating the measurement offset of the robotic arm posture according to any one of the above first aspects.

[0020] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which one or more computer instructions are stored, characterized in that the instructions are executed by a processor to implement the method for calibrating the measurement offset of the robotic arm posture according to any one of the above first aspects.

[0021] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, where the computer program, when executed by a processor, implements the method for calibrating the measurement offset of the robotic arm posture according to any one of the above first aspects.

[0022] Compared with the prior art, the present application has the following advantages:

[0023] The method for calibrating the measurement offset of the robotic arm posture provided by the present application first obtains a digital twin model corresponding to the mechanical equipment. Each virtual robotic arm on the digital twin model corresponds one-to-one to each robotic arm on the mechanical equipment, and the postures of each virtual robotic arm on the digital twin model are consistent with the initial postures of the corresponding robotic arms on the mechanical equipment. Adjust the posture of the target robotic arm on the mechanical equipment, and obtain the first posture information obtained by the target measuring device for measuring the posture of the target robotic arm after the posture adjustment. Adjust the posture of the corresponding target virtual robotic arm on the digital twin model to be consistent with the posture of the adjusted target robotic arm, and when the postures of the target virtual robotic arm and the target robotic arm are consistent, obtain the second posture information of the target virtual robotic arm in the digital twin model. In this way, reading the posture of the target virtual robotic arm of the digital twin model obtains the true posture of the target robotic arm in the mechanical equipment. By comparing the first posture information and the second posture information obtained by the target measuring device for measuring the posture of the target robotic arm, the measurement offset of the target measuring device for the posture of the target robotic arm can be determined.

[0024] Compared with the prior art, when the postures of the virtual robotic arms on the digital twin model are consistent with the postures of the corresponding robotic arms on the mechanical equipment, only need to adjust the posture of the target robotic arm to any posture, and then by adjusting the posture of the corresponding target virtual robotic arm on the digital twin model to be consistent with the adjusted posture of the target robotic arm, the true posture of the target robotic arm after the posture adjustment can be quickly determined with the help of the digital twin model, without the need for manual participation to calibrate the robotic arm to the horizontal position by human eyes, and the measurement offset of the target measurement device for the posture of the target robotic arm can be calibrated unmanned, automatically and more accurately, reducing the calibration threshold, enabling non-professional personnel to also calibrate results meeting the accuracy requirements through this method, thereby improving the delivery efficiency of large-scale mechanical equipment and reducing the deployment cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present application, and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application, and do not constitute an improper limitation of the present application. In the drawings:

[0026] Figure 1 is a schematic flow chart of a method for calibrating the measurement offset of the posture of a robotic arm provided in one embodiment of the present application;

[0027] Figure 2 is a schematic diagram of a digital twin model corresponding to a loader provided in one embodiment of the present application;

[0028] Figure 3 is a schematic diagram for determining whether the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm according to the difference between the second point cloud information and the first point cloud information provided in one embodiment of the present application;

[0029] Figure 4 is a schematic structural diagram of a device for calibrating the measurement offset of the posture of a robotic arm provided in one embodiment of the present application;

[0030] Figure 5 is a schematic hardware structure diagram of an electronic device provided in one embodiment of the present application.

[0031] Through the above drawings, the clear embodiments of the present application have been shown, and there will be more detailed descriptions hereinafter. These drawings and text descriptions are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] To make the objectives, advantages, and features of this application clearer, the following provides a clear and complete description of this application in conjunction with the accompanying drawings and specific embodiments. In the following description, many specific details are set forth to facilitate a full understanding of this application. However, the described embodiments are only a part of the embodiments of this application, rather than all of them. All other embodiments obtained by those of ordinary skill in the art without making creative efforts fall within the scope of protection of this application.

[0033] It should be noted that in the description of this application, terms such as "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance, as well as a specific order or sequence. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances. In addition, in the description of this application, unless otherwise specified, the term "plurality" means two or more. The term "and / or" describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after. The terms "comprise" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that comprises a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0034] To solve the problems existing in the above related technologies, this application provides a method for calibrating the measurement offset of a robotic arm posture, a device for calibrating the measurement offset of a robotic arm posture corresponding to this method, an electronic device capable of implementing this method for calibrating the measurement offset of a robotic arm posture, and a computer-readable storage medium. The following provides embodiments to elaborate on the above method, device, electronic device, and computer-readable storage medium in detail.

[0035] To make the objectives and technical solutions of this application clearer and more intuitive, the following will elaborate in detail on the method provided by the embodiments of this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application. It can be understood that the following several embodiments can exist independently, and the following embodiments and the features in the embodiments can be combined with each other without conflict in the embodiments provided by this application. For the same or similar content, it will not be repeated in different embodiments. In addition, the step timings in the following method embodiments are only for example and are not strictly limited. In some cases, the steps shown or described can be executed in a different order than this.

[0036] The present application provides a method, apparatus, electronic device, and computer-readable storage medium for calibrating the measurement offset of a robotic arm attitude. Specifically, the method for calibrating the measurement offset of a robotic arm attitude according to one embodiment of the present application can be executed by a computer device, where the computer device can be a terminal or a server, etc. The terminal can be a terminal device such as a smart phone, a tablet computer, a notebook computer, a touch screen, etc. The terminal can also include a client, and the client can be an application client, a browser client carrying an application program, or an instant messaging client, etc. The server can be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers. It can also be a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, and big data and artificial intelligence platforms.

[0037] Next, in combination with Figure 1 , a method for calibrating the measurement offset of a robotic arm attitude provided by one embodiment of the present application will be described. Figure 1 FIG. is a schematic flowchart of a method for calibrating the measurement offset of a robotic arm attitude provided by one embodiment of the present application.

[0038] As Figure 1 shown, the method for calibrating the measurement offset of a robotic arm attitude includes S10 - S40:

[0039] S10. Obtain a digital twin model corresponding to the mechanical equipment. Each virtual robotic arm on the digital twin model corresponds one-to-one to each robotic arm on the mechanical equipment, and the attitude of each virtual robotic arm on the digital twin model is consistent with the initial attitude of the corresponding robotic arm on the mechanical equipment.

[0040] S20. Adjust the attitude of the target robotic arm on the mechanical equipment, and obtain the first attitude information obtained by the target measurement device for measuring the attitude of the target robotic arm after the attitude adjustment.

[0041] S30. Adjust the attitude of the corresponding target virtual robotic arm on the digital twin model to be consistent with the attitude of the adjusted target robotic arm. When the attitudes of the target virtual robotic arm and the target robotic arm are consistent, obtain the second attitude information of the target virtual robotic arm in the digital twin model.

[0042] S40. Determine the measurement offset of the target measurement device for the attitude of the target robotic arm according to the first attitude information and the second attitude information.

[0043] Next, steps S10 - S40 will be described in detail.

[0044] As mentioned above, a mechanical device refers to a mechanical apparatus that includes robotic arms, such as a loader, an excavator, an industrial robot, and so on.

[0045] As mentioned above, digital twin is a technology that constructs a virtual model of a physical entity through digital means, and is used to monitor, analyze, and optimize the operating state of a physical entity system in real time. The digital twin model corresponding to a mechanical device refers to a digital virtual model constructed for the mechanical device by means of the above-mentioned digital twin technology. This model completely corresponds to the actual mechanical device in terms of structure, function, and operating state, and can reflect the dynamic behavior and performance of the mechanical device in real time.

[0046] Exemplarily, in combination with Figure 2 , taking the mechanical device as a loader as an example, an example description of the digital twin model corresponding to the loader is given. Figure 2 This is a schematic diagram of the digital twin model corresponding to the loader provided in one embodiment of the present application. As Figure 2 shown, Figure 2 in the left figure is the physical loader, and the right figure is the digital twin model corresponding to the loader. The digital twin model corresponding to the loader completely corresponds to the physical loader in terms of structure, size, function, and operating state.

[0047] In the embodiment of the present application, a digital twin model corresponding to a mechanical device is obtained. Each virtual robotic arm on the digital twin model corresponds one-to-one with each robotic arm on the mechanical device, and the posture of each virtual robotic arm on the digital twin model is the same as the initial posture of the corresponding robotic arm on the mechanical device. For example, when the mechanical device includes robotic arms such as a boom and a forearm, when the posture of the digital twin model corresponding to the mechanical device is the same as that of the mechanical device, the posture of the boom on the mechanical device is the same as the posture of the virtual boom in the digital twin model, and the posture of the forearm on the mechanical device is the same as the posture of the virtual forearm in the digital twin model.

[0048] It should be noted that since there is a linkage between the robotic arms on the mechanical equipment, for example, changing the posture of the large arm will drive the change of the position of the small arm. Only when the postures of the virtual robotic arms on the digital twin model are consistent with the postures of the corresponding robotic arms on the mechanical equipment, during the subsequent adjustment of the posture of the target robotic arm on the mechanical equipment, the corresponding target virtual robotic arm on the digital twin model can be synchronously adjusted to ensure that for the mechanical equipment and the digital twin model, the variable between the two is only the target robotic arm or the corresponding virtual robotic arm, that is, the variable is single. For example, first obtain a digital twin model that is exactly the same as the posture of the mechanical equipment, adjust the posture of the large arm (i.e., the target robotic arm) in the mechanical equipment, and synchronously adjust the posture of the virtual large arm of the digital twin model, so as to ensure that the posture difference between the adjusted mechanical equipment and the digital twin model is only reflected in the large arm or the virtual large arm.

[0049] In the embodiments of the present application, since there is a linkage relationship between different robotic arms included in the mechanical equipment, that is, when the posture of one robotic arm changes, it may simultaneously drive the corresponding posture change of another robotic arm. For example, the change in the posture of the large arm on the mechanical equipment will drive the change of the small arm. The method for calibrating the measurement offset of the robotic arm posture provided in the embodiments of the present application is used to measure the difference between the posture measurement value of the robotic arm on the mechanical equipment by a target measurement device such as an IMU sensor (Inertial Measurement Unit) and the true posture of the robotic arm, that is, the measurement offset (or error) of the target measurement device for the robotic arm posture. In order to avoid the measurement error caused by the linkage, only one robotic arm in the mechanical equipment is targeted in one measurement to obtain the measurement offset of the target measurement device for the posture of this robotic arm.

[0050] As mentioned above, the target robotic arm is any one of the robotic arms in the mechanical equipment, such as the large arm or the small arm, etc.

[0051] In the embodiments of the present application, first, the staff can be allowed to adjust the posture of the target robotic arm in the mechanical equipment so that the postures of the target robotic arm before and after the adjustment are inconsistent. After the adjustment of the posture of the target robotic arm is completed, a target measurement device such as an IMU sensor is used to measure the current posture of the target robotic arm on the mechanical equipment, and then the first posture information obtained by the target measurement device for measuring the posture of the target robotic arm after the posture adjustment is acquired.

[0052] Since the digital twin model corresponding to the mechanical device is a digital virtual model, when controlling the attitude adjustment of the target virtual robotic arm in the digital twin model, the digital twin model can timely feedback the attitude state of the target virtual robotic arm after the attitude adjustment. Based on this, in the embodiments of the present application, when the attitude of the target virtual robotic arm on the digital twin model is adjusted to be consistent with the attitude of the target robotic arm after the attitude adjustment, the true attitude of the target robotic arm after the attitude adjustment - that is, the second attitude information, can be obtained based on the digital twin model.

[0053] In the embodiments of the present application, according to the first attitude information and the second attitude information, the measurement offset of the target measurement device for the attitude of the target robotic arm is determined. Specifically, the attitude difference information between the first attitude information and the second attitude information is used to determine the measurement offset of the target measurement device for the attitude of the target robotic arm.

[0054] An alternative implementation manner is that the first attitude information includes the joint angles of the target robotic arm measured by the target measurement device, and the second attitude information includes the joint angles of the target virtual robotic arm in the digital twin model.

[0055] As described above, a possible implementation manner of step S40, "According to the first attitude information and the second attitude information, determine the measurement offset of the target measurement device for the attitude of the target robotic arm", includes step S401:

[0056] S401. Based on the joint angles of the target robotic arm measured by the target measurement device and the joint angles of the target virtual robotic arm, determine the measurement offset of the target measurement device for the attitude of the target robotic arm.

[0057] An alternative implementation manner is to determine the difference between the joint angles of the target robotic arm measured by the target measurement device and the joint angles of the target virtual robotic arm as the measurement offset of the target measurement device for the attitude of the target robotic arm.

[0058] Exemplarily, taking the target robotic arm as the upper arm as an example, assume that the joint angle of the target robotic arm measured by the target measuring device is 50°, and the joint angle of the target virtual robotic arm is 55°. Then, the difference between the joint angle of the target robotic arm measured by the target measuring device and the joint angle of the target virtual robotic arm is 50° - 55° = -5°. Therefore, the measurement offset of the target measuring device for the posture of the target robotic arm is -5°. That is to say, the measured value of the joint angle of the target robotic arm by the target measuring device is 5° smaller than the actual joint angle of the target robotic arm. Also assume that the joint angle of the target robotic arm measured by the target measuring device is 50°, and the joint angle of the target virtual robotic arm is 45°. Then, the difference between the joint angle of the target robotic arm measured by the target measuring device and the joint angle of the target virtual robotic arm is 50° - 45° = 5°. Therefore, the measurement offset of the target measuring device for the posture of the target robotic arm is 5°. That is to say, the measured value of the joint angle of the target robotic arm by the target measuring device is 5° larger than the actual joint angle of the target robotic arm.

[0059] In another alternative implementation, the difference between the joint angle of the target virtual robotic arm and the joint angle of the target robotic arm measured by the target measuring device is determined as the measurement offset of the target measuring device for the posture of the target robotic arm.

[0060] Exemplarily, taking the target robotic arm as the upper arm as an example, assume that the joint angle of the target robotic arm measured by the target measuring device is 50°, and the joint angle of the target virtual robotic arm is 55°. Then, the difference between the joint angle of the target virtual robotic arm and the joint angle of the target robotic arm measured by the target measuring device is 55° - 50° = 5°. Therefore, the measurement offset of the target measuring device for the posture of the target robotic arm is 5°. That is to say, the measured value of the joint angle of the target robotic arm by the target measuring device is 5° smaller than the actual joint angle of the target robotic arm. Also assume that the joint angle of the target robotic arm measured by the target measuring device is 50°, and the joint angle of the target virtual robotic arm is 45°. Then, the difference between the joint angle of the target virtual robotic arm and the joint angle of the target robotic arm measured by the target measuring device is 45° - 50° = -5°. Therefore, the measurement offset of the target measuring device for the posture of the target robotic arm is -5°. That is to say, the measured value of the joint angle of the target robotic arm by the target measuring device is 5° larger than the actual joint angle of the target robotic arm.

[0061] Further, steps S20 - S40 can be executed multiple times, and the average value of the measurement offsets obtained separately each time is determined as the measurement offset of the target measurement device for the target robotic arm's pose. For example, steps S20 - S40 are executed 5 times, and the measurement offsets of the target measurement device for the target robotic arm's pose obtained in these 5 times are k1, k2, k3, k4, k5 in sequence. Then the final measurement offset of the target measurement device for the target robotic arm's pose is (k1 + k2 + k3 + k4 + k5) / 5.

[0062] In the method for calibrating the measurement offset of the robotic arm's pose provided in the embodiments of the present application, first, a digital twin model corresponding to the mechanical equipment is obtained. Each virtual robotic arm on the digital twin model corresponds one - to - one with each robotic arm on the mechanical equipment, and the poses of each virtual robotic arm on the digital twin model are consistent with the initial poses of the corresponding robotic arms on the mechanical equipment. The pose of the target robotic arm on the mechanical equipment is adjusted, and the first pose information obtained by the target measurement device measuring the pose of the target robotic arm after the pose adjustment is acquired. The pose of the corresponding target virtual robotic arm on the digital twin model is adjusted to be consistent with the pose of the adjusted target robotic arm. When the poses of the target virtual robotic arm and the target robotic arm are consistent, the second pose information of the target virtual robotic arm in the digital twin model is acquired. In this way, reading the pose of the target virtual robotic arm in the digital twin model obtains the true pose of the target robotic arm in the mechanical equipment. By comparing the first pose information and the second pose information obtained by the target measurement device measuring the target robotic arm, the measurement offset of the target measurement device for the target robotic arm's pose can be determined.

[0063] Compared with the prior art, in the case where the poses of each virtual robotic arm on the digital twin model are consistent with the poses of the corresponding robotic arms on the mechanical equipment, the present application only needs to adjust the pose of the target robotic arm to any pose, and then adjust the pose of the corresponding target virtual robotic arm on the digital twin model to be consistent with the adjusted pose of the target robotic arm. With the help of the digital twin model, the true pose of the target robotic arm after the pose adjustment can be quickly determined. There is no need for manual participation to calibrate the robotic arm to the horizontal position by human eyes. The measurement offset of the target measurement device for the target robotic arm's pose can be calibrated unmanned, automatically, and more precisely, reducing the calibration threshold, enabling non - professional personnel to also calibrate results that meet the accuracy requirements through this method, thereby improving the delivery efficiency of large - scale mechanical equipment and reducing the deployment cost.

[0064] Based on the above - mentioned embodiments, the method for calibrating the measurement offset of the robotic arm's pose provided in the embodiments of the present application is further described below.

[0065] An alternative implementation, a specific implementation of "adjusting the posture of the target virtual robotic arm corresponding to the digital twin model to be consistent with the posture of the adjusted target robotic arm" in the above steps includes steps S301 - S303:

[0066] S301. Obtain the first point cloud information of the target robotic arm with adjusted posture on the mechanical equipment.

[0067] S302. Perform a preliminary posture adjustment on the target virtual robotic arm on the digital twin model.

[0068] S303. Repeat the first step until the point cloud difference between the second point cloud information of the target virtual robotic arm with adjusted posture and the first point cloud information of the target robotic arm is less than a preset difference threshold.

[0069] The first step includes steps S3031 - S3033:

[0070] S3031. Obtain the second point cloud information of the target virtual robotic arm with adjusted posture simulated by the digital twin model.

[0071] S3032. Calculate the point cloud difference between the second point cloud information and the first point cloud information, and the magnitude of the point cloud difference is used to characterize the magnitude of the posture difference between the target virtual robotic arm and the target robotic arm.

[0072] S3033. Perform a posture adjustment on the target virtual robotic arm on the digital twin model to reduce the posture difference between the target virtual robotic arm and the target robotic arm.

[0073] Next, the above steps S301 - S303 will be described in detail.

[0074] The above-mentioned point cloud information of the target robotic arm refers to the spatial geometric data on the surface of the target robotic arm obtained by a certain measurement means (such as 3D sensing devices like lidar scanning, depth cameras, etc.), and these data are represented in the form of a point cloud, and the point cloud is a set composed of a large number of points in three-dimensional space.

[0075] It should be noted that taking lidar as the currently used point cloud measurement means as an example, in order to ensure that the target robotic arm on the mechanical equipment and the target virtual robotic arm on the digital twin model have the same point cloud information when their postures are consistent, it is necessary to ensure that the deployment method of the lidar on the mechanical equipment (such as deployment position, quantity, etc.) and the deployment method of the virtual lidar on the digital twin model corresponding to the mechanical equipment are exactly the same.

[0076] As described above, the second point cloud information of the target virtual robotic arm after the attitude adjustment simulated by the digital twin model refers to the point cloud information obtained by the digital twin model through point cloud simulation of the target virtual robotic arm on the digital twin model after the attitude adjustment. For example, by performing point cloud simulation on the target virtual robotic arm on the digital twin model using the virtual lidar deployed on the digital twin model, the second point cloud information of the target virtual robotic arm after the attitude adjustment can be obtained.

[0077] In the embodiment of the present application, after the attitude adjustment of the target robotic arm on the mechanical device ends in step S20, the first point cloud information of the target robotic arm on the mechanical device after the attitude adjustment is obtained. In order to adjust the attitude of the target virtual robotic arm on the digital twin model to be consistent with that of the target robotic arm, an attempt is made to adjust the attitude of the target virtual robotic arm in the digital twin model. During the first attitude adjustment, the target virtual robotic arm in the digital twin model can be adjusted arbitrarily, such as any adjustment. For example, the target virtual robotic arm includes a virtual joint 1. Adjusting the attitude of the target virtual robotic arm means adjusting the angle size of the virtual joint 1 on the robotic arm. There are only two adjustment directions for adjusting the angle size, that is, either increasing the joint angle or decreasing the joint angle. Therefore, during the first attitude adjustment, the attitude adjustment of the virtual joint 1 on the target virtual robotic arm can be increasing the joint angle or decreasing the joint angle, and either one is acceptable. The embodiment of the present application does not make any limitation in this regard.

[0078] After the first attitude adjustment ends, S3031: Obtain the second point cloud information of the target virtual robotic arm after the attitude adjustment. S3032: Calculate the point cloud difference between the second point cloud information and the first point cloud information. The size of the point cloud difference is used to characterize the size of the attitude difference between the target virtual robotic arm and the target robotic arm. S3033: Adjust the attitude of the target virtual robotic arm on the digital twin model to reduce the attitude difference between the target virtual robotic arm and the target robotic arm. Repeat the above S3031 - S3033 until the point cloud difference between the second point cloud information of the target virtual robotic arm after the attitude adjustment and the first point cloud information of the target robotic arm is less than the preset difference threshold. At this time, it is considered that the attitude of the target virtual robotic arm on the digital twin model has been adjusted to be consistent with the attitude of the target robotic arm after the attitude adjustment.

[0079] In the embodiment of the present application, by comparing whether the second point cloud information of the target virtual robotic arm is consistent with the first point cloud information of the target robotic arm, it is determined whether the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm. In this way, it is possible to accurately evaluate whether the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm, and avoid misjudgment caused by simple angular or position errors. At the same time, the setting of the preset difference threshold defines the allowable deviation range between the second point cloud information and the first point cloud information. By setting the preset difference threshold, the subjective "consistency" is converted into an objective quantitative index, which is convenient for automated judgment and systematic operation.

[0080] Next, in combination with Figure 3 , an exemplary description is given of determining whether the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm by comparing whether the second point cloud information of the target virtual robotic arm is consistent with the first point cloud information of the target robotic arm. Figure 3 FIG. is a schematic diagram for determining whether the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm according to the difference between the second point cloud information and the first point cloud information provided in one embodiment of the present application. Among them, Figure 3 In this example, the target robotic arm is taken as the boom, and the target virtual robotic arm is taken as the virtual boom for illustration.

[0081] As Figure 3 shown, it includes FIG. (a) and FIG. (b). As shown in FIG. (a), for the digital twin model corresponding to the loader, the second point cloud information of the virtual boom corresponding to the digital twin model is shown as the green point set in FIG. (a). When aligning the placement position of the real loader with the digital twin model, the first point cloud information of the boom on the real loader is shown as the white point set in FIG. (a). As shown in FIG. (a), the point cloud difference between the second point cloud information and the first point cloud information is large (that is, the point cloud difference is greater than or equal to the preset difference threshold) (that is, it can be seen that the points of the second point cloud information and the points of the first point cloud information hardly overlap at all), then it is determined that the posture of the virtual boom corresponding to the digital twin model at this time is inconsistent with the posture of the boom corresponding to the real loader. Subsequently, continue to adjust the posture of the virtual boom corresponding to the digital twin model to reduce the posture difference between the posture of the virtual boom corresponding to the digital twin model and the posture of the boom corresponding to the real loader. As shown in FIG. (b), after adjusting the posture of the virtual boom corresponding to the digital twin model, the point cloud difference between the second point cloud information of the virtual boom and the first point cloud information of the real loader is small (that is, the point cloud difference is less than the preset difference threshold) (that is, it can be seen that the points of the second point cloud information and the points of the first point cloud information almost completely overlap), then at this time it can be determined that the posture of the virtual boom corresponding to the digital twin model is consistent with the posture of the boom corresponding to the real loader.

[0082] An alternative implementation, a specific implementation of the above step S3033 "adjust the pose of the target virtual robotic arm on the digital twin model to reduce the pose difference between the target virtual robotic arm and the target robotic arm" includes S30331:

[0083] S30331. Adjust the pose of the target virtual robotic arm according to the point cloud difference between the second point cloud information and the first point cloud information.

[0084] An alternative implementation, the pose adjustment includes a first pose adjustment direction and a second pose adjustment direction opposite to the first pose adjustment direction. Specifically, the implementation of step S30331 "adjust the pose of the target virtual robotic arm according to the point cloud difference between the second point cloud information and the first point cloud information" includes steps A1 - A3:

[0085] A1. Compare the point cloud difference after the pose adjustment with the point cloud difference before the current pose adjustment, and determine whether the point cloud difference between the second point cloud information and the first point cloud information of the target virtual robotic arm after the pose adjustment has narrowed.

[0086] A2. If so, adjust the pose of the target virtual robotic arm in the target pose adjustment direction, and the target pose adjustment direction is the pose adjustment direction of the previous pose adjustment of the target virtual robotic arm.

[0087] A3. If not, adjust the pose of the target virtual robotic arm in the opposite direction of the target pose adjustment direction.

[0088] As mentioned above, the target pose adjustment direction is the pose adjustment direction of the previous pose adjustment of the target virtual robotic arm, and the target pose adjustment direction is the first pose adjustment direction or the second pose adjustment direction opposite to the first pose adjustment direction.

[0089] In the embodiments of the present application, taking the target pose adjustment direction as the first pose adjustment direction as an example for illustration, compared with the point cloud difference before the current pose adjustment, when it is determined that the point cloud difference between the second point cloud information and the first point cloud information of the target virtual robotic arm after the pose adjustment has narrowed, continue to adjust the pose of the target virtual robotic arm in the first pose adjustment direction to further narrow the point cloud difference between the second point cloud information and the first point cloud information. Or, compared with the point cloud difference before the current pose adjustment, when it is determined that the point cloud difference between the second point cloud information and the first point cloud information of the target virtual robotic arm after the pose adjustment has widened, then adjust the pose of the target virtual robotic arm in the second pose adjustment direction opposite to the first pose adjustment direction to narrow the point cloud difference between the second point cloud information and the first point cloud information, so as to avoid further widening of the point cloud difference between the second point cloud information and the first point cloud information.

[0090] An alternative implementation, the posture of the target virtual robotic arm includes the joint angles on the target virtual robotic arm. The first posture adjustment direction is to increase the joint angle, and the second posture adjustment direction is to decrease the joint angle.

[0091] In the embodiments of the present application, taking the target posture adjustment direction of increasing the joint angle as an example for illustration, compared with the point cloud difference before the current posture adjustment, when it is determined that the point cloud difference between the second point cloud information and the first point cloud information of the target virtual robotic arm after the posture adjustment has decreased, the joint angle of the target virtual robotic arm is continuously increased in the way of increasing the joint angle. Or, compared with the point cloud difference before the current posture adjustment, when it is determined that the point cloud difference between the second point cloud information and the first point cloud information of the target virtual robotic arm after the posture adjustment has increased, the joint angle of the target virtual robotic arm is decreased.

[0092] Exemplarily, since the movement direction of the joint is fixed, it is a one-dimensional search. The initial search randomly selects a direction for optimization. For example, the joint angle of the current target robotic arm is 0°, and the joint angle of the target virtual robotic arm in the simulation is 20°. The first calculation error is 20°. At this time, since there is no historical data, a direction is randomly selected for optimization, and the joint angle of the target virtual robotic arm is adjusted to 40°. At this time, the error obtained is 40°. Then the posture will be adjusted to 15° next time. At this time, the error obtained is 15°. Then the joint angle of the target virtual robotic arm is adjusted to -5° next time. At this time, the error obtained is 5°. Then the joint angle of the target virtual robotic arm may be adjusted to -10° next time, and the error obtained is 10°. Finally, the joint angle of the target virtual robotic arm may be adjusted to -0.2°, and the error obtained is 0.2°. If it is less than the preset threshold, it is considered that the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm at this time.

[0093] An alternative implementation, the specific implementation manner of the above step S3032 "calculate the point cloud difference between the second point cloud information and the first point cloud information" includes steps B1 - B3:

[0094] B1. For each target point in the second point cloud information, determine a point in the first point cloud information that is closest to the target point, and determine the closest point as the neighbor point corresponding to the target point in the first point cloud information.

[0095] B2. For each target point, calculate the distance between the target point and the corresponding neighbor point.

[0096] B3. Determine the average value of the distances between all target points and their corresponding neighbor points as the point cloud difference between the second point cloud information and the first point cloud information.

[0097] Next, steps B1 - B3 will be described in detail.

[0098] An alternative implementation manner, the specific implementation manner of "determining a point closest to the target point from the points included in the first point cloud information" in step B1 includes steps B11 - B12:

[0099] B11. Construct a KD - tree based on the first point cloud information.

[0100] B12. Use the nearest - neighbor search algorithm to determine the point closest to the target point from the KD - tree.

[0101] In the embodiments of the present application, constructing a KD - tree based on the first point cloud information is to recursively divide multiple three - dimensional points included in the first point cloud data into sub - regions to form a binary tree. Each division selects the median in one dimension as the splitting point. When using the nearest - neighbor search algorithm to determine the point closest to the target point from the KD - tree. In this way, a point closest to the target point can be quickly queried from the points included in the first point cloud information.

[0102] An alternative implementation manner, calculating the distance between the target point and the corresponding neighboring point can be calculating the Chebyshev distance.

[0103] An alternative implementation manner, the method for calibrating the measurement offset of the manipulator posture provided by the present application further includes step S50:

[0104] S50. Determine the true posture of the target manipulator based on the posture and measurement offset of the target manipulator measured by the target measuring device.

[0105] An alternative implementation manner, when the measurement offset of the target manipulator posture measured by the target measuring device is the difference between the joint angles of the target manipulator measured by the target measuring device and the joint angles of the target virtual manipulator, the difference between the posture of the target manipulator measured by the target measuring device and the measurement offset is determined as the true posture of the target manipulator.

[0106] Exemplarily, taking the mechanical equipment as a loader, the target robotic arm as the boom, and the target measuring device as an IMU sensor as an example for illustration, the true attitude of the target robotic arm on the loader = the measured value of the IMU sensor - the measurement offset. Assuming that when the joint angle of the boom on the loader is at the position of 0°, the reading of the IMU sensor at this time is 11.3°, then the measurement offset k of the IMU sensor for the joint angle of the boom is 11.3°. Subsequently, the joint angle of the boom on the loader is rotated to a certain position. If the reading of the IMU sensor is 21.3°, according to the true attitude (joint angle) of the boom on the loader = the measured value of the IMU sensor for the joint angle of the boom - the measurement offset k of the IMU sensor for the joint angle of the boom, the true attitude (joint angle) of the boom on the loader at this time can be calculated as 21.3° - 11.3° = 10°.

[0107] In another alternative embodiment, when the difference between the joint angle of the target virtual robotic arm and the joint angle of the target robotic arm measured by the target measuring device is determined as the measurement offset of the target measuring device for the attitude of the target robotic arm, the sum of the attitude of the target robotic arm measured by the target measuring device and the measurement offset is determined as the true attitude of the target robotic arm.

[0108] Exemplarily, taking the mechanical equipment as a loader, the target robotic arm as the boom, and the target measuring device as an IMU sensor as an example for illustration, the true attitude of the target robotic arm on the loader = the measured value of the IMU sensor + the measurement offset. Assuming that when the joint angle of the boom on the loader is at the position of 0°, the reading of the IMU sensor at this time is 11.3°, then the measurement offset k of the IMU sensor for the joint angle of the boom is -11.3°. Subsequently, the joint angle of the boom on the loader is rotated to a certain position. If the reading of the IMU sensor is 21.3°, according to the true attitude (joint angle) of the boom on the loader = the measured value of the IMU sensor for the joint angle of the boom + the measurement offset k of the IMU sensor for the joint angle of the boom, the true attitude (joint angle) of the boom on the loader at this time can be calculated as 21.3° + (-11.3°) = 10°.

[0109] The measurement offset calibration device for the robotic arm attitude provided by the present application will be described below. The measurement offset calibration device for the robotic arm attitude described below can be correspondingly referred to the measurement offset calibration method for the robotic arm attitude described above.

[0110] Figure 4 It is a schematic structural diagram of the measurement offset calibration device for the robotic arm attitude provided by one embodiment of the present application. As Figure 4 shown, the measurement offset calibration device 400 for the robotic arm attitude includes: an acquisition module 401, an adjustment module 402, a processing module 403, and a determination module 404.

[0111] An acquisition module, configured to acquire a digital twin model corresponding to a mechanical device, where each virtual robotic arm on the digital twin model corresponds one-to-one to each robotic arm on the mechanical device, and the postures of each virtual robotic arm on the digital twin model are consistent with the initial postures of the corresponding robotic arms on the mechanical device;

[0112] An adjustment module, configured to adjust the posture of a target robotic arm on the mechanical device, and acquire first posture information obtained by a target measuring device measuring the posture of the target robotic arm after the posture adjustment;

[0113] A processing module, configured to adjust the posture of the corresponding target virtual robotic arm on the digital twin model to be consistent with the posture of the adjusted target robotic arm, and when the postures of the target virtual robotic arm and the target robotic arm are consistent, acquire second posture information of the target virtual robotic arm in the digital twin model;

[0114] A determination module, configured to determine a measurement offset of the target measuring device for the posture of the target robotic arm according to the first posture information and the second posture information.

[0115] An optional implementation manner, where the processing module is specifically configured to:

[0116] Acquire first point cloud information of the target robotic arm on the mechanical device after the posture adjustment;

[0117] Perform a preliminary posture adjustment on the target virtual robotic arm on the digital twin model;

[0118] Repeat the first step until the point cloud difference between the second point cloud information of the target virtual robotic arm after the posture adjustment and the first point cloud information of the target robotic arm is less than a preset difference threshold;

[0119] The first step includes:

[0120] Acquire second point cloud information of the target virtual robotic arm after the posture adjustment simulated by the digital twin model;

[0121] Calculate the point cloud difference between the second point cloud information and the first point cloud information, and the magnitude of the point cloud difference is used to characterize the magnitude of the posture difference between the target virtual robotic arm and the target robotic arm;

[0122] Perform a posture adjustment on the target virtual robotic arm on the digital twin model to reduce the posture difference between the target virtual robotic arm and the target robotic arm.

[0123] An optional implementation manner, where the processing module is specifically configured to:

[0124] Adjust the pose of the target virtual robotic arm according to the point cloud difference between the second point cloud information and the first point cloud information.

[0125] An optional implementation, the pose adjustment includes a first pose adjustment direction and a second pose adjustment direction opposite to the first pose adjustment direction; specifically, the processing module is configured to:

[0126] Compare with the point cloud difference before the current pose adjustment, and determine whether the point cloud difference between the second point cloud information and the first point cloud information of the target virtual robotic arm after the pose adjustment is reduced;

[0127] If so, adjust the pose of the target virtual robotic arm in the target pose adjustment direction, where the target pose adjustment direction is the pose adjustment direction of the previous pose adjustment of the target virtual robotic arm;

[0128] If not, adjust the pose of the target virtual robotic arm in the opposite direction of the target pose adjustment direction;

[0129] Wherein, the target pose adjustment direction is the first pose adjustment direction or the second pose adjustment direction opposite to the first pose adjustment direction.

[0130] An optional implementation, the pose of the target virtual robotic arm includes the joint angles on the target virtual robotic arm, the first pose adjustment direction is to increase the joint angle, and the second pose adjustment direction is to decrease the joint angle.

[0131] An optional implementation, specifically, the processing module is configured to:

[0132] For each target point in the second point cloud information, determine a point closest to the target point from the points included in the first point cloud information, and determine the closest point as the neighbor point corresponding to the target point in the first point cloud information;

[0133] For each of the target points, calculate the distance between the target point and the corresponding neighbor point;

[0134] Determine the average value of the distances between all the target points and the corresponding neighbor points as the point cloud difference between the second point cloud information and the first point cloud information.

[0135] An optional implementation, specifically, the processing module is configured to:

[0136] Construct a KD tree based on the first point cloud information;

[0137] Using the nearest neighbor search algorithm, determine the point in the KD tree that is closest to the target point.

[0138] An alternative implementation, the first pose information includes the joint angles of the target robotic arm measured by the target measuring device, and the second pose information includes the joint angles of the target virtual robotic arm in the digital twin model; specifically, the determination module is configured to include:

[0139] Based on the joint angles of the target robotic arm measured by the target measuring device and the joint angles of the target virtual robotic arm, determine the measurement offset of the pose of the target robotic arm measured by the target measuring device.

[0140] An alternative implementation, calculating the distance between the target point and the corresponding nearest neighbor point includes:

[0141] Calculate the Chebyshev distance between the target point and the corresponding nearest neighbor point.

[0142] An alternative implementation, the method further includes:

[0143] Based on the pose of the target robotic arm measured by the target measuring device and the measurement offset, determine the true pose of the target robotic arm.

[0144] The measuring offset calibration device for the robotic arm pose provided in this embodiment can be used to execute the technical solutions of the method embodiment for calibrating the measuring offset of the robotic arm pose. The implementation principle and technical effects are similar, and will not be elaborated here in this embodiment.

[0145] Figure 5 This is a schematic hardware structure diagram of an electronic device provided in one embodiment of the present application. As Figure 5 shown, the electronic device 500 in this embodiment includes: a processor 501 and a memory 502; where

[0146] The memory 502 is used to store computer execution instructions;

[0147] The processor 501 is configured to execute the computer execution instructions stored in the memory to implement each step performed by the method for calibrating the measuring offset of the robotic arm pose in the above embodiment. For details, reference can be made to the relevant descriptions in the foregoing method embodiment.

[0148] Optionally, the memory 502 can be either independent or integrated with the processor 501.

[0149] When the memory 502 is independently provided, the electronic device further includes a bus 503 for connecting the memory 502 and the processor 501.

[0150] One embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the technical solution corresponding to the method for calibrating the measurement offset of the robotic arm posture in any of the above embodiments executed by the above electronic device is implemented.

[0151] One embodiment of the present application further provides a computer program product, which includes: a computer program stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and the at least one processor executes the computer program to enable the electronic device to execute the technical solution corresponding to the method for calibrating the measurement offset of the robotic arm posture in any of the above embodiments.

[0152] Although the present application is disclosed above with preferred embodiments, it is not used to limit the present application. Any person skilled in the art can make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the protection scope of the present application should be subject to the scope defined by the claims of the present application.

[0153] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, indirect couplings or communication connections of devices or modules, which can be electrical, mechanical or other forms.

[0154] The integrated modules implemented in the form of software function modules as described above can be stored in a computer-readable storage medium. The above software function modules are stored in a storage medium, including several instructions for causing an electronic device (which can be a personal computer, a server, or a network device, etc.) or a processor (English: processor) to execute some steps of the methods described in various embodiments of the present application.

[0155] It should be understood that the above-mentioned processor may be a Central Processing Unit (CPU), or it may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in combination with the invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

[0156] The memory may include high-speed RAM memory, and may also include non-volatile storage NVM, such as at least one disk memory, and may also be a USB flash drive, a mobile hard disk, a read-only memory, a magnetic disk, or an optical disc, etc.

[0157] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience in representation, the bus in the attached drawings of this application is not limited to only one bus or one type of bus.

[0158] The above storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disc. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0159] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions. The foregoing program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above method embodiments; and the foregoing storage medium includes: ROM, RAM, magnetic disk, or optical disc and other media that can store program codes.

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for calibrating the measurement offset of a robot arm posture, characterized in that: The method comprises: Acquire a digital twin model corresponding to the mechanical device, wherein each virtual mechanical arm on the digital twin model corresponds one-to-one to each mechanical arm on the mechanical device, and the posture of each virtual mechanical arm on the digital twin model is consistent with the initial posture of each mechanical arm corresponding to the mechanical device; Adjusting the posture of the target mechanical arm on the mechanical device, and obtaining first posture information obtained by measuring the posture of the target mechanical arm after the posture adjustment by a target measuring device; Adjusting the posture of the corresponding target virtual robotic arm on the digital twin model to be consistent with the posture of the adjusted target robotic arm, and when the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm, acquiring second posture information of the target virtual robotic arm in the digital twin model; According to the first posture information and the second posture information, a measurement offset of the target mechanical arm posture by the target measurement device is determined.

2. The method according to claim 1, characterized in that The step of adjusting the posture of the target virtual mechanical arm corresponding to the digital twin model to be consistent with the posture of the adjusted target mechanical arm includes: Acquire first point cloud information of the target mechanical arm after posture adjustment on the mechanical device; Performing preliminary posture adjustment on the target virtual robotic arm on the digital twin model; Repeat the first step until the point cloud difference between the second point cloud information of the target virtual robotic arm after posture adjustment and the first point cloud information of the target robotic arm is less than a preset difference threshold; The first step includes: Acquire second point cloud information of the target virtual robotic arm after posture adjustment simulated by the digital twin model; Calculating a point cloud difference between the second point cloud information and the first point cloud information, wherein the size of the point cloud difference is used to characterize the size of a posture difference between the target virtual robotic arm and the target robotic arm; The target virtual robotic arm on the digital twin model is posture-adjusted to reduce the posture difference between the target virtual robotic arm and the target robotic arm.

3. The method according to claim 2, characterized in that The step of adjusting the posture of the target virtual robotic arm on the digital twin model includes: According to the point cloud difference between the second point cloud information and the first point cloud information, the posture of the target virtual robotic arm is adjusted.

4. The method according to claim 3, characterized in that The step of adjusting the posture of the target virtual robotic arm according to the point cloud difference between the second point cloud information and the first point cloud information includes: By comparing the point cloud difference before the current posture adjustment, determining whether the point cloud difference between the second point cloud information of the target virtual robotic arm after the posture adjustment and the first point cloud information is reduced; If yes, adjusting the posture of the target virtual robotic arm according to the target posture adjustment direction, wherein the target posture adjustment direction is the posture adjustment direction of the last posture adjustment of the target virtual robotic arm; If not, adjusting the posture of the target virtual robotic arm in the opposite direction of the target posture adjustment direction; The target posture adjustment direction is a first posture adjustment direction, or a second posture adjustment direction opposite to the first posture adjustment direction.

5. The method according to claim 4, characterized in that The posture of the target virtual robotic arm includes the joint angles on the target virtual robotic arm, the first posture adjustment direction is to increase the joint angles, and the second posture adjustment direction is to reduce the joint angles.

6. The method according to claim 2, characterized in that The calculating the point cloud difference between the second point cloud information and the first point cloud information comprises: For each target point in the second point cloud information, determine a point that is closest to the target point from the points included in the first point cloud information, and determine the point that is closest to the target point as a neighboring point corresponding to the target point in the first point cloud information; For each of the target points, calculating the distance between the target point and the corresponding neighboring point; An average value of the distances between all the target points and the corresponding neighboring points is determined as the point cloud difference between the second point cloud information and the first point cloud information.

7. The method according to claim 6, characterized in that The step of determining a point closest to the target point from the points included in the first point cloud information includes: Constructing a KD tree based on the first point cloud information; A nearest neighbor search algorithm is used to determine the point closest to the target point from the KD tree.

8. The method according to claim 1, characterized in that The first posture information includes the joint angle of the target robotic arm measured by the target measurement device, and the second posture information includes the joint angle of the target virtual robotic arm in the digital twin model; determining the measurement offset of the target robotic arm posture by the target measurement device according to the first posture information and the second posture information, including: Based on the joint angle of the target robotic arm measured by the target measurement device and the joint angle of the target virtual robotic arm, a measurement offset of the target robotic arm posture by the target measurement device is determined.

9. The method according to claim 7, characterized in that: The calculating the distance between the target point and the corresponding neighboring point includes: The Chev distance between the target point and the corresponding neighboring point is calculated.

10. The method according to claim 1, characterized in that The method further comprises: Based on the posture of the target mechanical arm measured by the target measurement device and the measured offset, a true posture of the target mechanical arm is determined.

11. A device for calibrating the measurement offset of a robot arm posture, characterized in that: The device comprises: An acquisition module is used to acquire a digital twin model corresponding to the mechanical equipment, wherein each virtual mechanical arm on the digital twin model corresponds one-to-one to each mechanical arm on the mechanical equipment, and the posture of each virtual mechanical arm on the digital twin model is consistent with the initial posture of each mechanical arm corresponding to the mechanical equipment; An adjustment module, used for adjusting the posture of the target mechanical arm on the mechanical device, and obtaining first posture information obtained by a target measurement device through posture measurement of the target mechanical arm after the posture adjustment; A processing module, used to adjust the posture of the corresponding target virtual robotic arm on the digital twin model to be consistent with the posture of the adjusted target robotic arm, and when the posture of the target virtual robotic arm is consistent with the posture of the target robotic arm, obtain second posture information of the target virtual robotic arm in the digital twin model; A determination module is used to determine a measurement offset of the target mechanical arm posture by the target measurement device according to the first posture information and the second posture information.

12. An electronic device, characterized in that: The electronic device comprises: Processor; and The memory is used to store a data processing program. After the electronic device is powered on and runs the program through the processor, the measurement offset calibration method of the robot arm posture described in any one of claims 1-10 is executed.

13. A computer-readable storage medium, characterized in that: A data processing program is stored, and the program is run by a processor to execute the measurement offset calibration method of the robot arm posture as described in any one of claims 1-10.

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