Automatic equipment control method and device, computer equipment and readable storage medium

Abstract

The invention relates to an automation equipment control method and device, computer equipment and a readable storage medium. The method comprises the following steps: acquiring a preset working position of target equipment and an accumulated working time length of the target equipment before a current moment; wherein the target equipment is automatic equipment; according to the preset working position and the accumulated working duration, determining a corresponding position error of the target equipment at the preset working position at the current moment; and generating a control instruction for the target equipment according to the preset working position and the position error, and controlling the target equipment according to the control instruction. By adopting the method, the operation precision of automatic equipment can be kept.

Description

Technical Field

[0001] The present application relates to the technical field of automation equipment, and in particular to an automation equipment control method, device, computer equipment and readable storage medium. Background Art

[0002] Automation equipment, including industrial robots and CNC machine tools, has been widely used in various fields and links of industrial production, such as installation, handling, production lines and processing. Automation equipment can improve production efficiency and production accuracy.

[0003] However, as the use time of automation equipment increases, its operating accuracy will degrade to varying degrees, and the operating error will gradually increase, affecting the quality of its processed products. Based on this, how to avoid the decline in product quality caused by the degradation of automation equipment is an urgent problem to be solved. Summary of the invention

[0004] Based on this, it is necessary to provide an automation equipment control method, device, computer equipment and readable storage medium that can maintain the operation accuracy of automation equipment in response to the above technical problems.

[0005] In a first aspect, the present application provides an automation equipment control method, comprising:

[0006] Obtaining a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0007] According to the preset working position and the accumulated working time, determine the position error corresponding to the target device at the preset working position at the current moment;

[0008] According to the preset working position and position error, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0009] In one embodiment, determining the position error corresponding to the target device at the preset working position at the current moment according to the preset working position and the accumulated working time includes:

[0010] Based on the trained position error determination model, the preset working position and the accumulated working time are processed to obtain the position error corresponding to the target device at the preset working position at the current moment.

[0011] In one embodiment, the position error determination model is trained in the following manner:

[0012] Acquire joint variables of the target device; wherein the joint variables include at least one of rotation variables corresponding to the rotational joints of the target device and translation variables corresponding to the translational joints of the target device;

[0013] Extracting a sample data set of the corresponding joint variables within the preset limit range of each joint variable;

[0014] Determine at least two sample space parameters based on the sample data set of each joint variable;

[0015] Training a pre-trained position error determination model according to at least two sample space parameters to obtain a trained position error determination model;

[0016] Among them, any sample space parameter is determined in the following way: for a sample data set corresponding to any joint variable, a sample data is extracted from the sample data set as candidate data; and the candidate data corresponding to each joint variable are combined into a sample space parameter.

[0017] In one embodiment, training a pre-trained position error determination model according to at least two sample space parameters to obtain a trained position error determination model includes:

[0018] For any sample space parameter, determining a standard working position of the target device corresponding to the sample space parameter; and,

[0019] Determine the actual working position of the target device corresponding to the sample space parameters;

[0020] According to the standard working position and the actual working position corresponding to each sample space parameter, the pre-trained position error determination model is trained to obtain a trained position error determination model.

[0021] In one embodiment, determining the actual working position of the target device corresponding to the sample space parameters includes:

[0022] Generate test control instructions for target equipment based on sample space parameters;

[0023] Control the target equipment according to the test control instructions;

[0024] The actual working position reached by the target device when performing the working task in response to the test control instruction is obtained.

[0025] In one embodiment, a pre-trained position error determination model is trained according to the standard working position and the actual working position corresponding to each sample space parameter to obtain a trained position error determination model, including:

[0026] For any sample space parameter, according to the standard working position and the actual working position corresponding to the sample space parameter, determine the sample position error corresponding to the sample space parameter;

[0027] According to the sample position error, the standard working position, and the corresponding cumulative working time of the samples when the target device responds to the corresponding test control instructions, the pre-trained position error determination model is trained to obtain the trained position error determination model.

[0028] In one embodiment, a control instruction for a target device is generated according to a preset working position and a position error, and the target device is controlled according to the control instruction, including:

[0029] Determine the target working position according to the preset working position and position error;

[0030] Based on the target working position, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0031] In a second aspect, the present application also provides an automation equipment control device, comprising:

[0032] A data acquisition module, used to acquire a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0033] An error determination module is used to determine the position error corresponding to the target device at the preset working position at the current moment according to the preset working position and the accumulated working time;

[0034] The device control module is used to generate control instructions for the target device according to the preset working position and position error, and control the target device according to the control instructions.

[0035] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0036] Obtaining a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0037] According to the preset working position and the accumulated working time, determine the position error corresponding to the target device at the preset working position at the current moment;

[0038] According to the preset working position and position error, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0039] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the following steps are implemented:

[0040] Obtaining a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0041] According to the preset working position and the accumulated working time, determine the position error corresponding to the target device at the preset working position at the current moment;

[0042] According to the preset working position and position error, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0043] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0044] Obtaining a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0045] According to the preset working position and the accumulated working time, determine the position error corresponding to the target device at the preset working position at the current moment;

[0046] According to the preset working position and position error, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0047] After obtaining the preset working position of the target device, the above-mentioned automation equipment control method, device, computer equipment and readable storage medium do not directly generate control instructions for the target device according to the preset working position. Instead, according to the accumulated working time and preset working position corresponding to the target device at the current moment, the position error corresponding to the target device at the preset working position at the current moment is determined, and then the control instructions for the target device are generated according to the preset working position and the position error. That is to say, in the above process, in the process of generating the control instructions for the target device, not only the position error is considered, but also the accumulated working time corresponding to the target device at the current moment is considered, which can significantly improve the accuracy of the control instructions for the target device. Furthermore, controlling the target device according to the control instructions can maintain the working accuracy of the target device. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments of the present application or the related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary users in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0049] Figure 1 A schematic diagram of a flow chart of an automation equipment control method in one embodiment;

[0050] Figure 2 A schematic diagram of a flow chart of a training step of a position error determination model in one embodiment;

[0051] Figure 3 A schematic flow chart of a training step of a position error determination model in another embodiment;

[0052] Figure 4 A schematic diagram of a flow chart of an automation equipment control method in another embodiment;

[0053] Figure 5 A structural block diagram of an automation equipment control device in one embodiment;

[0054] Figure 6 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0056] Before introducing the automation equipment control method provided by the present application, it should be noted that automation equipment, such as CNC machine tools and industrial robots, has a certain working space. At present, automation equipment has important applications in industries such as aerospace, shipbuilding and automobiles, and the quality of its operation accuracy has an important impact on the operation effect. However, the operation accuracy of automation equipment has obvious differences in different positions in the workspace. In addition, as time goes by, its operation accuracy continues to deteriorate and the operation error gradually increases.

[0057] At present, the main method to solve the large operation error of automation equipment is to perform corresponding calibration compensation on the transmission chain of its operation, such as establishing a kinematic model of the equipment operation transmission chain, performing error tests on multiple positions in the operation space, and then obtaining a set of optimal solutions through matrix operations or fitting optimization, as the optimization values ​​of its motion model parameters (taking robots as an example: the industry currently mainly uses testing and calibration methods to improve the motion accuracy of robots. Through laser trackers, machine vision technologies, etc., robot motion accuracy tests are completed, robot motion models are established, the actual motion parameters of the robot are identified and compensation is performed to improve the robot's motion accuracy). The operation accuracy of the equipment can be improved to a certain extent through calibration compensation, but this calibration work is generally carried out before the equipment leaves the factory, and some companies will also perform it again after the performance of the equipment has declined after a period of operation. However, there are two problems with this: first, the execution of calibration compensation requires the equipment to be shut down, and the process takes a long time, affecting the operation efficiency of the production line and the production efficiency of the enterprise; second, calibration compensation in instruments and equipment is passive, and calibration compensation can only be performed after performance degradation is detected. At this time, the performance has already declined, which has affected the accuracy of some products.

[0058] In addition, the established kinematic model also has a great influence on the accuracy of calibration compensation, because the factors affecting motion accuracy may be multivariate, and the kinematic model can only select the main influencing factors for calculation.

[0059] The present application is to study a method that can characterize the overall workspace error and its degradation of the automation equipment, and use this method to maintain the operating accuracy of the automation equipment.

[0060] In one embodiment, Figure 1 As shown, a method for controlling an automation device is provided. This embodiment is illustrated by applying the method to a controller of an automation device. In this embodiment, the method includes the following steps:

[0061] S110, obtaining a preset working position of the target device and a cumulative working time of the target device before the current moment.

[0062] Wherein, the target device is an automated device. For example, the target device may be an industrial robot or a CNC machine tool, and this application does not impose any limitation on this. The preset working position of the target device may be set by the user as required, and this application does not impose any limitation on the number of preset working positions. Furthermore, in order to improve the accuracy of the preset working position, the preset working position may include the position coordinates of the actuator end of the target device, and may also include the posture coordinates of the actuator end of the target device.

[0063] For example, when the user wants to control the target device to go to a certain location to perform a production task, the coordinates of the location can be used as the preset working position of the target device. When the user wants to control the target device to go to a first location to perform a first production task first, and then go to a second location to perform a second production task after the first production task is completed, the first location and the second location can be used as the preset working positions of the target device in sequence.

[0064] Optionally, the target device in this embodiment can record the working hours corresponding to each task executed since it left the factory, as well as the cumulative working hours from the time it left the factory to the current moment. Accordingly, in the case where there is a demand for automated device control for the target device, the corresponding cumulative working hours recorded by the target device at the current moment are obtained. Exemplarily, in the case where there is a demand for automated device control for the target device, the cumulative working hours of the target device before the current moment are obtained from a preset storage location in the controller of the target device.

[0065] In this embodiment, when the preset working position of the target device input by the user is received, the cumulative working time of the target device before the current moment can be obtained from the preset storage location. The method in which the user inputs the preset working position is not limited in this application. Optionally, the controller of the target device can be provided with a control screen, and the user can input the preset working position through the control screen; the controller of the target device can also be bound to a control terminal, and the user can input the preset working position through the control terminal.

[0066] S120, determining, according to the preset working position and the accumulated working time, a position error corresponding to the target device at the preset working position at the current moment.

[0067] The position error is used to characterize the difference between the actual working position reached by the execution end of the target device and the preset working position after the target device responds to the production task corresponding to the preset working position.

[0068] In an optional implementation, a position error determination formula with the preset working position and the accumulated working time as independent variables and the position error corresponding to the target device at the preset working position as the dependent variable can be determined in advance through a large number of experiments. After substituting the preset working position and the accumulated working time into the position error determination formula, the position error corresponding to the target device at the preset working position at the current moment is determined.

[0069] In an optional implementation, the preset working position and the accumulated working time can be processed based on the trained position error determination model to obtain the position error corresponding to the target device at the preset working position at the current moment. Among them, the position error determination model can be constructed based on a common neural network, which will not be described in detail here. Furthermore, in the process of training the position error determination model, the sample working position and the accumulated working time corresponding to the sample working position can be input into the position error determination model, and the position error determination model can be trained according to the position error prediction result output by the position error determination model and the position error label corresponding to the corresponding sample working position to improve the model accuracy of the position error determination model.

[0070] Of course, the subject that determines the position error corresponding to the target device at the preset working position at the current moment may also be a device other than the controller of the target device, so as to reduce the workload of the controller of the target device. For example, the controller of the target device outputs the preset working position and the accumulated working time to the position error determination device, and receives the position error input by the position error determination device.

[0071] S130, generating a control instruction for the target device according to the preset working position and the position error, and controlling the target device according to the control instruction.

[0072] In an optional implementation, the preset working position and position error may be input into a pre-trained control instruction generation model to generate a control instruction for the target device, and then the target device may be controlled according to the control instruction.

[0073] Among them, the control instruction generation model can be constructed based on a common neural network, which will not be described in detail here. Furthermore, in the process of training the control instruction generation model, the sample working position and the sample position error corresponding to the sample working position can be input into the control instruction generation model, and the control instruction generation model is trained according to the predicted control instruction input by the control instruction generation model and the control instruction label corresponding to the sample working position, so as to improve the model accuracy of the control instruction generation model.

[0074] In an optional implementation, the target working position can be determined based on the preset working position and the position error; based on the target working position, a control instruction for the target device is generated, and the target device is controlled according to the control instruction. Exemplarily, if the position error indicates that the execution end of the target device will have a forward error, the preset working position is adjusted backward to obtain the target working position. For example, if the preset working position is (1, 1, 1) and the position error is (-0.1, -0.1, 0.1), the target working position is (1.1, 1.1, 0.9).

[0075] Furthermore, based on the target working position, a control instruction for the target device is generated, and the target device is controlled according to the control instruction to ensure that the execution end of the target device can accurately reach the preset working position, that is, to ensure the accuracy of the target device.

[0076] In the above-mentioned automation equipment control method, after the preset working position of the target device is obtained, the control instruction for the target device is not directly generated according to the preset working position. Instead, the position error corresponding to the target device at the preset working position at the current moment is determined according to the cumulative working time and the preset working position corresponding to the target device at the current moment, and then the control instruction for the target device is generated according to the preset working position and the position error. That is to say, in the above-mentioned process, in the process of generating the control instruction for the target device, not only the position error is considered, but also the cumulative working time corresponding to the target device at the current moment is considered, which can significantly improve the accuracy of the control instruction for the target device. Furthermore, controlling the target device according to the control instruction can maintain the working accuracy of the target device.

[0077] It is worth noting that in the prior art, after the preset working position of the target device is obtained, a control instruction for the target device is directly generated according to the preset working position. In this case, if the operating accuracy of the target device at the preset working position is degraded, the control instruction cannot control the target device to reach the preset working position, that is, the operating error of the target device becomes larger.

[0078] Based on this, in the automation equipment control method provided by the present application, after obtaining the preset working position of the target device, the control instruction for the target device is not directly generated according to the preset working position, but the position error corresponding to the preset working position at the current moment is determined according to the cumulative working time and the preset working position of the target device before the current time, and then based on the position error, a more accurate control instruction is determined, so that the control instruction can control the target device to reach the preset working position. In other words, the automation equipment control method provided by the present application can compensate for the degradation of the control instruction corresponding to the target device when the target device is degraded, and then generate accurate control instructions to control the target device, so that the working accuracy of the target device is improved.

[0079] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the training method of the position error determination model is introduced in detail.

[0080] See also Figure 2 The position error determination model training steps shown include:

[0081] S210, obtaining joint variables of the target device.

[0082] The joint variables include at least one of a rotation variable corresponding to a rotation joint of the target device and a translation variable corresponding to a translation joint of the target device.

[0083] It should be noted that the target device may be a device including only rotational joints, a device including only translational joints, or a device including both rotational joints and translational joints. Of course, the number of each type of joints of the target device is determined when the target device leaves the factory.

[0084] S220, extracting a sample data set of the corresponding joint variable within a preset limit range of each joint variable.

[0085] Among them, the preset limit range of each joint variable of the target device has been set as required when the target device leaves the factory.

[0086] For example, the target device includes both rotational joints and translational joints, and the number of rotational joints and translational joints is three. Accordingly, the joint variables of the target device include rotational variable R1, rotational variable R2, rotational variable R3, translational variable T1, translational variable T2, and translational variable T3. Among them, the preset limit range of R1 is [θ 1l ,θ 1h ], the preset limit range of R2 is [θ 2l ,θ 2h ], the preset limit range of R3 is [θ 3l ,θ 3h ]; the preset limit range of T1 is [x 1l , x 1h ], the preset limit range of T2 is [x 2l , x 2h ], the preset limit range of T3 is [x 3l , x 3h ].

[0087] Further, a preset sampling method is used to extract a sample data set of the corresponding joint variable within the preset limit range of each joint variable. The number of data in the sample data set can be determined based on manual experience, and illustratively, it can be 10 or 20, and this application does not impose any limitation on this. Optionally, a random sampling method or a Latin hypercube sampling method can be used.

[0088] S230, determining at least two sample space parameters according to the sample data sets of each joint variable.

[0089] Among them, any sample space parameter is determined in the following manner: for a sample data set corresponding to any joint variable, a sample data is extracted from the sample data set as candidate data; the candidate data corresponding to each joint variable is combined into a sample space parameter. In other words, a sample space parameter includes a sample data in each joint variable.

[0090] For example, if the sample data set of each joint variable includes m sample data, the sample space parameter can be expressed as: (θ 1k ,θ 2k , ..., θ nk , x 1k , x 2k , ..., x nk ), where k=1…m.

[0091] S240: training a pre-trained position error determination model according to at least two sample space parameters to obtain a trained position error determination model.

[0092] In this embodiment, for any sample space parameter, the standard working position corresponding to the target device under the sample space parameter can be determined; and the actual working position corresponding to the target device under the sample space parameter can be determined; according to the standard working position and the actual working position corresponding to each sample space parameter, the pre-trained position error determination model is trained to obtain a trained position error determination model.

[0093] The standard working position is the working position of the execution end of the target device corresponding to the corresponding sample space parameter without considering the device error. The actual working position is the working position of the execution end of the target device corresponding to the corresponding sample space parameter when the actual device error is taken into account. It can be understood that, under normal circumstances, for any sample space parameter, there is a certain difference between the standard working position corresponding to the target device under the sample space parameter and the actual working position, and the difference may become larger as the target device is put into use for a longer time.

[0094] In an optional implementation, the standard working position corresponding to the target device under the sample space parameters may be determined by inputting the sample space parameters into the motion space model to obtain the standard working position corresponding to the sample space parameters. The motion space model is a common motion space model, and this application does not impose any limitation on this.

[0095] In an optional embodiment, the method for determining the actual working position corresponding to the target device under the sample space parameters can be, based on the sample space parameters, generating a test control instruction for the target device; controlling the target device according to the test control instruction; and obtaining the actual working position reached by the target device when performing the work task in response to the test control instruction. The test control instruction is used to instruct each device joint of the target device to adjust to the variable corresponding to the corresponding sample space parameter. Furthermore, after the target device is controlled based on the test control instruction, the actual working position of the corresponding position can be measured using test equipment such as a laser tracker and a visual sensor.

[0096] It is understandable that although the test control instruction instructs the target device's device joints to adjust to the variables corresponding to the corresponding sample space parameters, under normal circumstances, due to the long use time of the device, the target device's execution end may not respond accurately to the instruction, resulting in the standard working position and actual working position corresponding to the same sample space parameter may be different. For example, for the same sample space parameter, its corresponding standard working position may be (X a , Y a , Z a , A a , B a , C a )(a=1…m), the corresponding actual working position may be(X b , Y b , Z b , A b , B b , C b )(b=1…m). Where (X, Y, Z) represents the position coordinates of the actuator end of the target device, and (A, B, C) represents the attitude coordinates of the actuator end of the target device.

[0097] After determining the standard working position and the actual working position corresponding to the sample space parameters, the pre-trained position error determination model is trained according to the standard working position and the actual working position corresponding to each sample space parameter to obtain a trained position error determination model. Exemplarily, the standard working position and the actual working position corresponding to each sample space parameter are input into the pre-trained position error determination model, the position error prediction result output by the model, and the position error label corresponding to each sample space parameter are used to train the position error determination model, thereby improving the model accuracy of the position error determination model and obtaining a trained position error determination model.

[0098] In the above embodiment, the construction method of the position error determination model is introduced in detail. Specifically, from the acquisition of joint variables, to the extraction of sample data sets of each joint variable, and then to the determination of at least two sample space parameters based on the sample data sets of each joint variable, and then the pre-trained position error determination model is trained based on the at least two sample space parameters. This makes the training process of the position error determination model clearer.

[0099] Based on the technical solutions of the above embodiments, the present application also provides a method for training a position error determination model.

[0100] See also Figure 3 The training steps of the position error determination model shown include:

[0101] S310 , for any sample space parameter, determine a sample position error corresponding to the sample space parameter according to a standard working position and an actual working position corresponding to the sample space parameter.

[0102] For example, the standard working position corresponding to the sample space parameter and the actual working position can be subtracted to obtain the sample position error corresponding to the corresponding sample space parameter. The standard working position corresponding to the sample space parameter is (X a , Y a , Z a , A a , B a , C a )(a=1…m), the actual working position is(X b , Y b , Z b , A b , B b , C b )(b=1…m) as an example, the sample position error corresponding to the sample space parameter can be (X c , Y c , Z c , A c , B c , C c )(c=1…m).

[0103] S320, training the pre-trained position error determination model according to the sample position error, the standard working position, and the corresponding sample cumulative working time when the target device responds to the corresponding test control instruction to obtain a trained position error determination model.

[0104] Exemplarily, the sample position error corresponding to each sample space parameter, the standard working position, and the corresponding sample cumulative working time when the target device responds to the corresponding test control instruction are input into the pre-trained position error determination model, and the position error prediction result output by the model and the position error label corresponding to each sample space parameter are used to train the position error determination model to improve the model accuracy of the position error determination model and obtain a trained position error determination model.

[0105] Furthermore, although the above embodiment provides a method for determining the position error based on a trained position error model, in this embodiment, the position error may also be determined by a position error determination formula.

[0106] For example, the position error determination formula can determine the sample position error corresponding to each sample space parameter in the manner of S310, and then obtain the mapping relationship between the standard working position corresponding to each sample space parameter and the corresponding sample position error. For example, taking the mapping relationship as (Y, X) as an example, where X is the standard working position (X a , Y a , Z a , A a , B a , C a ) (a=1…m), Y is the sample position error corresponding to the sample space parameter (X c , Y c , Z c , A c , B c , C c )(c=1…m). Further, the step test of S220-S230 is performed regularly under specific working conditions to obtain the set (Y, X, t) at different times, where t is the corresponding cumulative working time of the target equipment at the test time.

[0107] Furthermore, based on the formula determination formula, the (Y, X, t) set is processed to obtain the position error determination formula Y=f(X, t), that is, the position error determination formula with the preset working position X and the accumulated working time t as independent variables and the position error Y corresponding to the target device at the preset working position X as the dependent variable.

[0108] In the above embodiment, a specific method for training the position error determination model is provided. At the same time, a specific method for determining the position error determination formula is provided, so that the method for determining the position error in this embodiment is more diverse.

[0109] Based on the technical solutions of the above embodiments, the present application also provides an optional embodiment. In this optional embodiment, the automation equipment control method provided by the present application is introduced in detail.

[0110] See also Figure 4 The automation equipment control method shown includes:

[0111] S410, obtaining joint variables of the target device.

[0112] The joint variables include at least one of a rotation variable corresponding to a rotation joint of the target device and a translation variable corresponding to a translation joint of the target device.

[0113] S420, extracting a sample data set of the corresponding joint variable within a preset limit range of each joint variable.

[0114] S430, determining at least two sample space parameters according to the sample data set of each joint variable.

[0115] Among them, any sample space parameter is determined in the following way: for a sample data set corresponding to any joint variable, a sample data is extracted from the sample data set as candidate data; and the candidate data corresponding to each joint variable are combined into a sample space parameter.

[0116] S440, constructing a position error determination formula based on at least two sample space parameters.

[0117] Specifically, for any sample space parameter, based on the motion space model, the standard working position corresponding to the target device under the sample space parameter is determined. Based on the sample space parameter, a test control instruction for the target device is generated; according to the test control instruction, the target device is controlled; and the actual working position reached by the target device when performing the work task in response to the test control instruction is obtained.

[0118] Further, the sample position error corresponding to the sample space parameter is determined according to the standard working position and the actual working position corresponding to the sample space parameter. A position error determination formula is constructed according to the sample position error, the standard working position, and the sample cumulative working time before the target device responds to the test control instruction corresponding to the corresponding sample space parameter.

[0119] S450, obtaining a preset working position of the target device and a cumulative working time of the target device before the current moment.

[0120] S460, inputting the preset working position and the accumulated working time into a position error determination formula to obtain the position error corresponding to the target device at the preset working position at the current moment.

[0121] S470, determining a target working position according to a preset working position and a position error.

[0122] S480, generating a control instruction for the target device based on the target working position, and controlling the target device according to the control instruction.

[0123] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0124] Based on the same inventive concept, the embodiment of the present application also provides an automated equipment control device for implementing the automated equipment control method involved above. The implementation solution provided by the device to solve the problem is similar to the implementation solution recorded in the above method, so the specific limitations in one or more automated equipment control device embodiments provided below can refer to the limitations of the automated equipment control method above, and will not be repeated here.

[0125] In an exemplary embodiment, Figure 5 As shown, an automated equipment control device is provided, comprising: a data acquisition module 510, an error determination module 520 and an equipment control module 530, wherein:

[0126] The data acquisition module 510 is used to acquire the preset working position of the target device and the accumulated working time of the target device before the current moment.

[0127] Among them, the target device is an automation device.

[0128] The error determination module 520 is used to determine the position error corresponding to the target device at the preset working position at the current moment according to the preset working position and the accumulated working time.

[0129] The device control module 530 is used to generate a control instruction for the target device according to the preset working position and the position error, and control the target device according to the control instruction.

[0130] In one embodiment, the error determination module is used to process the preset working position and the accumulated working time based on the trained position error determination model to obtain the position error corresponding to the target device at the preset working position at the current moment.

[0131] In one embodiment, the automation equipment control device also includes a model building module, including a variable acquisition unit, which is used to acquire the joint variables of the target device; wherein the joint variables include rotation variables corresponding to the rotational joints of the target device, and at least one of translation variables corresponding to the translational joints of the target device; a data extraction unit, which is used to extract sample data sets of corresponding joint variables within a preset limit range of each joint variable; a parameter determination module, which is used to determine at least two sample space parameters based on the sample data sets of each joint variable; a model training unit, which is used to train a pre-trained position error determination model based on at least two sample space parameters to obtain a trained position error determination model; wherein any sample space parameter is determined in the following manner: for a sample data set corresponding to any joint variable, a sample data is extracted from the sample data set as candidate data; and the candidate data corresponding to each joint variable are combined into a sample space parameter.

[0132] In one embodiment, the model training unit includes a first position determination subunit, which is used to determine, for any sample space parameter, a standard working position corresponding to the target device under the sample space parameter; a second position determination subunit, which is used to determine the actual working position corresponding to the target device under the sample space parameter; and a model training subunit, which is used to train a pre-trained position error determination model according to the standard working position and the actual working position corresponding to each sample space parameter to obtain a trained position error determination model.

[0133] In one embodiment, the second position determination subunit is specifically used to generate a test control instruction for the target device based on the sample space parameters; control the target device according to the test control instruction; and obtain the actual working position reached by the target device when performing a work task in response to the test control instruction.

[0134] In one embodiment, the model training subunit is specifically used to determine, for any sample space parameter, the sample position error corresponding to the sample space parameter according to the standard working position and the actual working position corresponding to the sample space parameter; and to train the pre-trained position error determination model according to the sample position error, the sample space parameter, and the corresponding accumulated working time of the sample when the target device responds to the corresponding test control instruction, to obtain a trained position error determination model.

[0135] In one embodiment, the device control module includes a target working position determination unit, which is used to determine the target working position based on a preset working position and a position error; and a device control unit, which is used to generate a control instruction for a target device based on the target working position, and control the target device according to the control instruction.

[0136] Each module in the above automation equipment control device can be implemented in whole or in part by software, hardware and their combination. Each module can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0137] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit and an input device. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, near field communication (Near Field Communication, NFC) or other technologies. When the computer program is executed by the processor, an automated device control method is realized. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0138] Users in this field can understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0139] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0140] Obtaining a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0141] According to the preset working position and the accumulated working time, determine the position error corresponding to the target device at the preset working position at the current moment;

[0142] According to the preset working position and position error, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0143] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0144] Based on the trained position error determination model, the preset working position and the accumulated working time are processed to obtain the position error corresponding to the target device at the preset working position at the current moment.

[0145] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0146] Acquire joint variables of the target device; wherein the joint variables include at least one of rotation variables corresponding to the rotational joints of the target device and translation variables corresponding to the translational joints of the target device;

[0147] Extracting a sample data set of the corresponding joint variables within the preset limit range of each joint variable;

[0148] Determine at least two sample space parameters based on the sample data set of each joint variable;

[0149] Training a pre-trained position error determination model according to at least two sample space parameters to obtain a trained position error determination model;

[0150] Among them, any sample space parameter is determined in the following way: for a sample data set corresponding to any joint variable, a sample data is extracted from the sample data set as candidate data; and the candidate data corresponding to each joint variable are combined into a sample space parameter.

[0151] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0152] For any sample space parameter, determining a standard working position of the target device corresponding to the sample space parameter; and,

[0153] Determine the actual working position of the target device corresponding to the sample space parameters;

[0154] According to the standard working position and the actual working position corresponding to each sample space parameter, the pre-trained position error determination model is trained to obtain a trained position error determination model.

[0155] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0156] Generate test control instructions for target equipment based on sample space parameters;

[0157] Control the target equipment according to the test control instructions;

[0158] The actual working position reached by the target device when performing the working task in response to the test control instruction is obtained.

[0159] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0160] For any sample space parameter, according to the standard working position and the actual working position corresponding to the sample space parameter, determine the sample position error corresponding to the sample space parameter;

[0161] According to the sample position error, sample space parameters, and the corresponding sample cumulative working time when the target device responds to the corresponding test control instruction, the pre-trained position error determination model is trained to obtain the trained position error determination model.

[0162] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0163] Determine the target working position according to the preset working position and position error;

[0164] Based on the target working position, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0165] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0166] Obtaining a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0167] According to the preset working position and the accumulated working time, determine the position error corresponding to the target device at the preset working position at the current moment;

[0168] According to the preset working position and position error, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0169] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0170] Based on the trained position error determination model, the preset working position and the accumulated working time are processed to obtain the position error corresponding to the target device at the preset working position at the current moment.

[0171] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0172] Acquire joint variables of the target device; wherein the joint variables include at least one of rotation variables corresponding to the rotational joints of the target device and translation variables corresponding to the translational joints of the target device;

[0173] Extracting a sample data set of the corresponding joint variables within the preset limit range of each joint variable;

[0174] Determine at least two sample space parameters based on the sample data set of each joint variable;

[0175] Training a pre-trained position error determination model according to at least two sample space parameters to obtain a trained position error determination model;

[0176] Among them, any sample space parameter is determined in the following way: for a sample data set corresponding to any joint variable, a sample data is extracted from the sample data set as candidate data; and the candidate data corresponding to each joint variable are combined into a sample space parameter.

[0177] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0178] For any sample space parameter, determining a standard working position of the target device corresponding to the sample space parameter; and,

[0179] Determine the actual working position of the target device corresponding to the sample space parameters;

[0180] According to the standard working position and the actual working position corresponding to each sample space parameter, the pre-trained position error determination model is trained to obtain a trained position error determination model.

[0181] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0182] Generate test control instructions for target equipment based on sample space parameters;

[0183] Control the target equipment according to the test control instructions;

[0184] The actual working position reached by the target device when performing the working task in response to the test control instruction is obtained.

[0185] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0186] For any sample space parameter, according to the standard working position and the actual working position corresponding to the sample space parameter, determine the sample position error corresponding to the sample space parameter;

[0187] According to the sample position error, sample space parameters, and the corresponding sample cumulative working time when the target device responds to the corresponding test control instruction, the pre-trained position error determination model is trained to obtain the trained position error determination model.

[0188] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0189] Determine the target working position according to the preset working position and position error;

[0190] Based on the target working position, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0191] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0192] Obtaining a preset working position of a target device and a cumulative working time of the target device before the current moment; wherein the target device is an automation device;

[0193] According to the preset working position and the accumulated working time, determine the position error corresponding to the target device at the preset working position at the current moment;

[0194] According to the preset working position and position error, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0195] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0196] Based on the trained position error determination model, the preset working position and the accumulated working time are processed to obtain the position error corresponding to the target device at the preset working position at the current moment.

[0197] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0198] Acquire joint variables of the target device; wherein the joint variables include at least one of rotation variables corresponding to the rotational joints of the target device and translation variables corresponding to the translational joints of the target device;

[0199] Extracting a sample data set of the corresponding joint variables within the preset limit range of each joint variable;

[0200] Determine at least two sample space parameters based on the sample data set of each joint variable;

[0201] Training a pre-trained position error determination model according to at least two sample space parameters to obtain a trained position error determination model;

[0202] Among them, any sample space parameter is determined in the following way: for a sample data set corresponding to any joint variable, a sample data is extracted from the sample data set as candidate data; and the candidate data corresponding to each joint variable are combined into a sample space parameter.

[0203] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0204] For any sample space parameter, determining a standard working position of the target device corresponding to the sample space parameter; and,

[0205] Determine the actual working position of the target device corresponding to the sample space parameters;

[0206] According to the standard working position and the actual working position corresponding to each sample space parameter, the pre-trained position error determination model is trained to obtain a trained position error determination model.

[0207] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0208] Generate test control instructions for target equipment based on sample space parameters;

[0209] Control the target equipment according to the test control instructions;

[0210] The actual working position reached by the target device when performing the working task in response to the test control instruction is obtained.

[0211] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0212] For any sample space parameter, according to the standard working position and the actual working position corresponding to the sample space parameter, determine the sample position error corresponding to the sample space parameter;

[0213] According to the sample position error, sample space parameters, and the corresponding sample cumulative working time when the target device responds to the corresponding test control instruction, the pre-trained position error determination model is trained to obtain the trained position error determination model.

[0214] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0215] Determine the target working position according to the preset working position and position error;

[0216] Based on the target working position, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

[0217] Ordinary users in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., but are not limited to this.

[0218] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0219] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for ordinary users in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for controlling an automated device, characterized in that: A controller applied to an automation device, the method comprising: Obtaining a preset working position of a target device and a cumulative working time of the target device before a current moment; wherein the target device is an automation device; Determine, according to the preset working position and the accumulated working time, a position error corresponding to the target device at the preset working position at the current moment; A control instruction for the target device is generated according to the preset working position and the position error, and the target device is controlled according to the control instruction.

2. The method according to claim 1, characterized in that The determining, according to the preset working position and the accumulated working time, a position error corresponding to the target device at the preset working position at the current moment includes: Based on the trained position error determination model, the preset working position and the accumulated working time are processed to obtain the position error corresponding to the target device at the preset working position at the current moment.

3. The method according to claim 2, characterized in that The position error determination model is trained in the following way: Acquire joint variables of the target device; wherein the joint variables include at least one of rotation variables corresponding to the rotational joints of the target device and translation variables corresponding to the translational joints of the target device; Extracting a sample data set of the corresponding joint variable within a preset limit range of each of the joint variables; Determining at least two sample space parameters according to the sample data sets of each of the joint variables; Training a pre-trained position error determination model according to the at least two sample space parameters to obtain a trained position error determination model; Among them, any of the sample space parameters is determined in the following manner: for a sample data set corresponding to any of the joint variables, a sample data is extracted from the sample data set as candidate data; and the candidate data corresponding to each of the joint variables are combined into the sample space parameter.

4. The method according to claim 3, characterized in that The step of training the pre-trained position error determination model according to the at least two sample space parameters to obtain a trained position error determination model includes: For any sample space parameter, determining a standard working position corresponding to the target device under the sample space parameter; and, Determine the actual working position of the target device corresponding to the sample space parameters; According to the standard working positions and actual working positions corresponding to the sample space parameters, the pre-trained position error determination model is trained to obtain a trained position error determination model.

5. The method according to claim 4, characterized in that The determining the actual working position of the target device corresponding to the sample space parameter includes: Based on the sample space parameters, generating a test control instruction for the target device; Controlling the target device according to the test control instruction; The actual working position reached by the target device when performing the working task in response to the test control instruction is obtained.

6. The method according to claim 5, characterized in that The pre-trained position error determination model is trained according to the standard working position and the actual working position corresponding to each of the sample space parameters to obtain a trained position error determination model, including: For any sample space parameter, determining a sample position error corresponding to the sample space parameter according to a standard working position and an actual working position corresponding to the sample space parameter; According to the sample position error, the standard working position, and the corresponding sample cumulative working time when the target device responds to the corresponding test control instruction, the pre-trained position error determination model is trained to obtain a trained position error determination model.

7. The method according to any one of claims 1 to 6, characterized in that The step of generating a control instruction for the target device according to the preset working position and the position error, and controlling the target device according to the control instruction includes: Determining a target working position according to the preset working position and the position error; Based on the target working position, a control instruction for the target device is generated, and the target device is controlled according to the control instruction.

8. An automation equipment control device, characterized in that: The device comprises: A data acquisition module, used to acquire a preset working position of a target device and the accumulated working time of the target device before the current moment; wherein the target device is an automation device; An error determination module, used to determine, according to the preset working position and the accumulated working time, a position error corresponding to the target device at the preset working position at the current moment; The device control module is used to generate a control instruction for the target device according to the preset working position and the position error, and control the target device according to the control instruction.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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