Simulation method of robot, simulation device and simulation system of robot

Abstract

The invention provides a simulation method and device of a robot and a simulation system of the robot, and the method comprises the steps: obtaining preset fault information; and according to the preset fault information, the hardware-in-loop module simulates operation of the robot under the condition of a preset fault indicated by the preset fault information so as to obtain operation parameters of the robot under the condition of the preset fault.

Description

Technical Field

[0001] The present invention relates to the technical field of household appliances, and in particular to a robot simulation method, a robot simulation device and a robot simulation system. Background Art

[0002] In the related art, during the fault rehearsal process for the robot, the fault parameters of the robot's related equipment are set, but the setting process is inefficient, and a fault occurs during the operation of the robot, which can easily cause damage to the robot, thereby resulting in a high cost for the fault rehearsal. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art.

[0004] To this end, a first aspect of the present invention provides a robot simulation method.

[0005] A second aspect of the present invention provides a robot simulation device.

[0006] A third aspect of the present invention provides a robot simulation device.

[0007] A fourth aspect of the present invention provides a robot simulation system.

[0008] A fifth aspect of the present invention provides a readable storage medium.

[0009] The first aspect of the present invention provides a robot simulation method, comprising: obtaining preset fault information; based on the preset fault information, simulating the operation of the robot under a preset fault condition indicated by the preset fault information through a hardware-in-the-loop module to obtain the operating parameters of the robot under the preset fault condition.

[0010] The robot simulation method provided by the present invention can simulate the operation of the robot. At the same time, in the process of simulating the operation of the robot, by obtaining preset fault information, the robot can operate under the preset fault indicated by the preset fault information, thereby realizing a preview of the operation of the robot when the preset fault occurs, and then obtaining the operation data of the robot when the preset fault occurs, so that the staff can adjust the relevant parts of the robot according to the situation where the preset fault occurs, to ensure the normal operation of the robot.

[0011] Specifically, first, preset fault information is obtained, and the preset fault information is used to indicate the corresponding preset fault. That is, in the process of simulating the operation of the robot, the operation of the simulated robot is performed when a preset fault occurs, so as to obtain the operating parameters of the robot when a preset fault occurs.

[0012] Furthermore, after obtaining the preset fault information, the hardware-in-the-loop module can be used to simulate the robot running under the preset fault indicated by the preset fault information. At the same time, in the process of simulating the operation of the robot, the operation parameters of the robot under the preset fault are obtained.

[0013] Specifically, the operation of the robot is simulated by the hardware-in-the-loop module, so that the operation parameters of the robot during operation can be obtained only through data simulation without operating the physical robot. At the same time, in the process of simulating the operation of the robot by the hardware-in-the-loop module, the acquired preset fault information is injected into the hardware-in-the-loop module, so that the hardware-in-the-loop module can simulate the operation of the robot under the preset fault indicated by the preset fault information.

[0014] Compared with using a physical robot for fault rehearsal, the simulation operation of the robot through the hardware-in-the-loop module can, on the one hand, effectively reduce the difficulty of setting the fault. That is, the preset fault information can be directly injected into the hardware-in-the-loop module, without the need to set parameters for the corresponding positions of the physical robot, thereby improving the efficiency of the robot's fault rehearsal. On the other hand, during the fault rehearsal process, there is no need for the physical robot to participate, that is, the physical robot will not actually fail during operation, so the cost of the robot's fault rehearsal can be effectively reduced.

[0015] It can be understood that, through the hardware-in-the-loop module, the operating parameters of different devices of the robot can be simulated, such as the robot's cable equipment, drive equipment, and transmission equipment.

[0016] The robot simulation method provided by the present invention simulates the operation of the robot through a hardware-in-the-loop module. In the process of setting the fault, the preset fault information can be directly injected into the hardware-in-the-loop module without setting the fault parameters on the physical robot, so that different types of fault languages ​​can be performed multiple times in a short period of time, thereby effectively improving the efficiency of the robot's fault rehearsal. At the same time, since the physical robot does not need to participate in the fault language process, the robot will not fail in the actual operation process, and the robot will not be damaged due to the failure, thereby effectively reducing the cost of the robot's fault rehearsal.

[0017] In addition, the robot simulation method in the above technical solution provided by the present invention may also have the following additional technical features:

[0018] In the above technical scheme, further, the hardware-in-the-loop module includes a fault injection model and multiple functional models, at least two of the multiple functional models are communicatively connected, and according to the preset fault information, the hardware-in-the-loop module simulates the operation of the robot under the preset fault indicated by the preset fault information to obtain the operating parameters of the robot under the preset fault, including: according to the preset fault information, generating fault data corresponding to the preset fault information through the fault injection model, and determining the target functional model among the multiple functional models; simulating the operation according to the fault data through the target functional model to obtain the first operating parameter; simulating the operation according to the first operating parameter through the functional model that is communicatively connected to the target functional model to obtain the second operating parameter of the functional model operation.

[0019] In this technical solution, the hardware-in-the-loop module may include a fault injection model and multiple functional models. Among them, the multiple functional models are used to simulate the operation of devices at different positions of the robot. For example, through different functional models, the operation of the robot's cable equipment, the operation of the robot's drive equipment, or the operation of the robot's transmission equipment are simulated respectively. At the same time, at least two of the multiple functional models are communicatively connected to simulate the communication connection between different devices of the robot. For example, the communication connection between the robot's cable equipment and the drive equipment, the communication connection between the robot's drive equipment and the transmission equipment, etc.

[0020] Furthermore, the fault injection model can generate fault data corresponding to the preset fault information according to the acquired preset fault information, and then the fault injection model can also inject the fault data corresponding to the preset fault information into the corresponding functional model. That is, the fault injection model is respectively connected to the communication between the multiple functional models to ensure that the fault injection model can inject the preset fault information into the corresponding functional model, so as to ensure that the functional model can simulate the operation of the robot under the preset fault.

[0021] Specifically, during the robot simulation process, the preset fault information is first obtained. After the preset fault information is obtained, the fault injection model generates fault data corresponding to the preset fault information according to the preset fault information, and can also determine the target functional model corresponding to the preset fault information in multiple functional models. That is, the location where the preset fault indicated by the preset fault information occurs.

[0022] Further, after determining the target function model and the fault data, the fault injection model injects the fault data into the target function model so that the target function model can simulate operation according to the fault data. That is, the corresponding equipment of the simulated robot operates under the condition of a preset fault. At the same time, the first operation parameter is obtained. That is, the first operation parameter of the corresponding equipment of the robot during operation under the condition of a preset fault.

[0023] Furthermore, the functional model that is communicatively connected to the target functional model can also simulate operation according to the first operating parameters generated during the simulated operation of the target functional model, that is, simulate the operating parameters of the relevant equipment in the robot when other equipment has a preset fault, so as to obtain the second operating parameters of other functional models that are communicatively connected to the target functional model.

[0024] It is understandable that when one of the devices of the robot fails, not only the operating parameters of the failed device will change under the influence of the failure, but also the operating parameters of other devices connected to the device will also change due to the change of the operating parameters of the device. Through the communication connection between multiple functional models of the hardware-in-the-loop module, the operating parameters of other devices in the case of a preset failure of one of the devices of the robot can be effectively simulated, so that the simulation process of the robot is close to the actual operation of the robot, thereby improving the effect of the robot's fault rehearsal.

[0025] In any of the above technical solutions, further, the multiple functional models include: a cable model, a driver model, a transmission model and a load model.

[0026] In this technical solution, the functional model of the hardware-in-the-loop module may include at least a cable model, a driver model, a transmission model and a load model. The cable model is communicatively connected to the driver model, the transmission model is communicatively connected to the driver model, and the load model is communicatively connected to the transmission model.

[0027] Specifically, during the fault rehearsal process, when a cable device fails, the driver model receives the parameters of the cable model to simulate the operation of the robot's driver. When a driver fails, the transmission model receives the parameters of the driver model to simulate the operation of the robot's transmission. At the same time, the cable model also receives the parameters of the driver model to simulate the operation of the robot's cable device. When a transmission fails, the load model receives the parameters of the transmission model to simulate the operation of the robot's load. At the same time, the driver model also receives the parameters of the transmission model to simulate the operation of the robot's driver.

[0028] In any of the above technical solutions, further, the hardware-in-the-loop module also includes a fault storage model. Before obtaining the preset fault information, the simulation method also includes: generating a plurality of different types of preset fault information; and storing the preset fault information in the fault storage model.

[0029] In this technical solution, the hardware-in-the-loop module may also include a fault storage model, through which a variety of preset fault information can be stored, so that the preset fault information can be retrieved through the fault injection model during the robot's fault language process. It can be understood that the fault storage model is communicatively connected with the fault injection model to ensure that the fault injection model can retrieve the corresponding preset fault information from the fault storage model.

[0030] Furthermore, before the fault injection model obtains the preset fault information from the fault storage model, a plurality of preset fault information may be generated by the host device, and then the plurality of preset fault information is stored in the fault storage model for acquisition by the fault injection model.

[0031] In any of the above technical solutions, the simulation method further includes: developing a fault prediction algorithm based on operating parameters; when receiving an operating instruction of the robot, simulating the operation of the robot through a hardware-in-the-loop module to verify the fault prediction algorithm.

[0032] In this technical solution, after the robot's fault rehearsal is completed and the robot's operating parameters under the preset fault are obtained, a fault prediction algorithm can be developed based on the operating parameters. It can be understood that the fault prediction algorithm is used to predict the robot's impending fault during the robot's operation, so that the robot can be adjusted in time before the robot fails, avoiding the robot's failure, avoiding robot damage, and reducing losses.

[0033] Furthermore, the developed fault prediction algorithm can also be verified through the hardware-in-the-loop module to determine whether the fault prediction algorithm is effective. Specifically, the fault prediction algorithm can be injected into the hardware-in-the-loop module, and according to the robot's operating instructions, the robot operation can be simulated through the hardware-in-the-loop module. During the robot simulation operation, the fault prediction algorithm is verified to determine whether the fault prediction algorithm can effectively predict the upcoming fault. Moreover, in the case that the fault prediction algorithm is invalid, the robot's fault rehearsal can be performed again through the hardware-in-the-loop module, the robot's operating parameters under the preset fault are re-obtained, and the fault prediction algorithm is developed according to the operating parameters. Until the fault prediction algorithm can effectively predict the robot's fault.

[0034] In any of the above technical solutions, further, before obtaining the preset fault information, the simulation method also includes: obtaining the operation instructions of the robot; and simulating the operation of the robot through a hardware-in-the-loop module according to the operation instructions.

[0035] In this technical solution, before obtaining the preset fault information, the normal operation of the robot can be simulated by the hardware-in-the-loop module. After the simulation of the normal operation of the robot begins, the preset fault information is obtained, and the fault information is injected through the fault injection model to simulate the operation of the robot under the preset fault.

[0036] Specifically, the operation instructions of the robot can be set by the host computer, and the operation instructions can indicate parameters such as the robot's operation trajectory, operation speed, and load during operation.

[0037] According to a second aspect of the present invention, a simulation device for a robot is proposed, comprising: an acquisition module for acquiring preset fault information; a hardware-in-the-loop module for simulating the operation of the robot under a preset fault indicated by the preset fault information according to the preset fault information, so as to obtain the operating parameters of the robot under the preset fault information.

[0038] The robot simulation method provided by the present invention simulates the operation of the robot through a hardware-in-the-loop module. In the process of setting the fault, the preset fault information can be directly injected into the hardware-in-the-loop module without setting the fault parameters on the physical robot, so that different types of fault languages ​​can be performed multiple times in a short period of time, thereby effectively improving the efficiency of the robot's fault rehearsal. At the same time, since the physical robot does not need to participate in the fault language process, the robot will not fail in the actual operation process, and the robot will not be damaged due to the failure, thereby effectively reducing the cost of the robot's fault rehearsal.

[0039] Furthermore, the hardware-in-the-loop module includes a fault injection model and multiple functional models, and at least two of the multiple functional models are communicatively connected. The fault injection model is used to generate fault data corresponding to the preset fault information according to the preset fault information, and to determine the target functional model among the multiple functional models; the target functional model is used to simulate operation according to the fault data to obtain a first operating parameter; and the functional model communicatively connected to the target functional model is also used to simulate operation according to the first operating parameter to obtain a second operating parameter for the functional model operation.

[0040] Among them, the functional model includes cable model, driver model, transmission model and load model.

[0041] Furthermore, the simulation device may further include a fault information generation module, which is used to generate preset fault information. The hardware-in-the-loop module also includes a fault storage model, which is used to store preset fault information.

[0042] Furthermore, the simulation device may also include a development module for developing a fault prediction algorithm according to the operation parameters. The hardware-in-the-loop module is also used to simulate the operation of the robot when receiving the operation instruction of the robot to verify the fault prediction algorithm.

[0043] Furthermore, before obtaining the preset fault information, the hardware-in-the-loop module is also used to obtain the operation instructions of the robot; and simulate the operation of the robot according to the operation instructions.

[0044] According to a third aspect of the present invention, a robot simulation device is proposed, comprising: a processor and a memory, the memory storing programs or instructions that can be run on the processor, and the programs or instructions, when executed by the processor, implement the steps of the robot simulation method provided in the first aspect.

[0045] The robot simulation device provided by the present invention includes a memory and a processor, and also includes a program or instruction stored in the memory. When the program or instruction is executed by the processor, it can implement the steps of the robot simulation method of the first aspect mentioned above. Therefore, the robot simulation device has all the beneficial effects of the robot simulation method mentioned above, which will not be repeated here.

[0046] According to a fourth aspect of the present invention, there is provided a robot simulation system, comprising the robot simulation device as described in the second aspect above.

[0047] The robot simulation system provided by the present invention comprises the robot simulation device of the second aspect mentioned above, so the robot simulation system has all the beneficial effects of the robot simulation device mentioned above, which will not be elaborated here.

[0048] Furthermore, the robot simulation system also includes a control device, which is connected to the hardware-in-the-loop module in communication to control the operation of the hardware-in-the-loop module. The robot simulation system also includes a host computer, which is connected to the control device and the hardware-in-the-loop module in communication, and is used to generate preset fault information and control instructions for the robot, and send them to the hardware-in-the-loop module or the control device.

[0049] In the above technical scheme, further, the control device includes: an operation control module, which is communicatively connected to the host computer and is used to receive the operation instructions of the robot issued by the host computer; a servo control module, which is communicatively connected to the operation control module and the hardware-in-the-loop module respectively, and is used to convert the operation instructions of the robot into control data and transmit the control data to the hardware-in-the-loop module.

[0050] In the above technical solution, further, the host computer is communicatively connected with the fault storage model of the hardware-in-the-loop module to generate a plurality of different types of preset fault information and store them in the fault storage model.

[0051] According to a fifth aspect of the present invention, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, a simulation method of a robot as described in any one of the above technical solutions is implemented.

[0052] The readable storage medium provided by the present invention stores a program or instruction thereon. When the program or instruction is executed by the processor, it can implement a robot simulation method such as any one of the above-mentioned technical solutions. Therefore, the storage medium has all the beneficial effects of the above-mentioned robot simulation method, which will not be repeated here.

[0053] Additional aspects and advantages of the present invention will become apparent from the following description or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0055] Figure 1 A schematic flow chart of a robot simulation method according to an embodiment of the present invention is shown;

[0056] Figure 2 A schematic flow chart of a robot simulation method according to another embodiment of the present invention is shown;

[0057] Figure 3 A schematic flow chart of a robot simulation method according to another embodiment of the present invention is shown;

[0058] Figure 4 A schematic flow chart of a robot simulation method according to another embodiment of the present invention is shown;

[0059] Figure 5 A schematic flow chart of a robot simulation method according to another embodiment of the present invention is shown;

[0060] Figure 6 A structural block diagram of a robot simulation system provided according to an embodiment of the present invention is shown;

[0061] Figure 7 A flowchart of the operation process of a robot simulation system provided according to an embodiment of the present invention is shown;

[0062] Figure 8 A flowchart of a control process of a robot simulation system provided according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0063] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict.

[0064] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0065] Refer to the following Figures 1 to 8 To describe a robot simulation method, a simulation device, and a robot simulation system provided according to some embodiments of the present invention.

[0066] like Figure 1 As shown, according to one embodiment of the present invention, a robot simulation method is proposed, comprising:

[0067] S102, obtaining preset fault information;

[0068] S104, according to the preset fault information, simulating the operation of the robot under the preset fault indicated by the preset fault information through the hardware-in-the-loop module to obtain the operation parameters of the robot under the preset fault.

[0069] The robot simulation method provided by the present invention can simulate the operation of the robot. At the same time, in the process of simulating the operation of the robot, by obtaining preset fault information, the robot can operate under the preset fault indicated by the preset fault information, thereby realizing a preview of the operation of the robot when the preset fault occurs, and then obtaining the operation data of the robot when the preset fault occurs, so that the staff can adjust the relevant parts of the robot according to the situation where the preset fault occurs, to ensure the normal operation of the robot.

[0070] Specifically, first, preset fault information is obtained, and the preset fault information is used to indicate the corresponding preset fault. That is, in the process of simulating the operation of the robot, the operation of the simulated robot is performed when a preset fault occurs, so as to obtain the operating parameters of the robot when a preset fault occurs.

[0071] Furthermore, after obtaining the preset fault information, the hardware-in-the-loop module can be used to simulate the robot running under the preset fault indicated by the preset fault information. At the same time, in the process of simulating the operation of the robot, the operation parameters of the robot under the preset fault are obtained.

[0072] Specifically, the operation of the robot is simulated by the hardware-in-the-loop module, so that the operation parameters of the robot during operation can be obtained only through data simulation without operating the physical robot. At the same time, in the process of simulating the operation of the robot by the hardware-in-the-loop module, the acquired preset fault information is injected into the hardware-in-the-loop module, so that the hardware-in-the-loop module can simulate the operation of the robot under the preset fault indicated by the preset fault information.

[0073] Compared with using a physical robot for fault rehearsal, the simulation operation of the robot through the hardware-in-the-loop module can, on the one hand, effectively reduce the difficulty of setting the fault. That is, the preset fault information can be directly injected into the hardware-in-the-loop module, without the need to set parameters for the corresponding positions of the physical robot, thereby improving the efficiency of the robot's fault rehearsal. On the other hand, during the fault rehearsal process, there is no need for the physical robot to participate, that is, the physical robot will not actually fail during operation, so the cost of the robot's fault rehearsal can be effectively reduced.

[0074] It can be understood that, through the hardware-in-the-loop module, the operating parameters of different devices of the robot can be simulated, such as the robot's cable equipment, drive equipment, and transmission equipment.

[0075] The robot simulation method provided by the present invention simulates the operation of the robot through a hardware-in-the-loop module. In the process of setting the fault, the preset fault information can be directly injected into the hardware-in-the-loop module without setting the fault parameters on the physical robot, so that different types of fault languages ​​can be performed multiple times in a short period of time, thereby effectively improving the efficiency of the robot's fault rehearsal. At the same time, since the physical robot does not need to participate in the fault language process, the robot will not fail in the actual operation process, and the robot will not be damaged due to the failure, thereby effectively reducing the cost of the robot's fault rehearsal.

[0076] According to one embodiment of the present invention, Figure 2 As shown, a robot simulation method is proposed, including:

[0077] S202, obtaining preset fault information;

[0078] S204, generating fault data corresponding to the preset fault information through a fault injection model according to the preset fault information, and determining a target functional model among multiple functional models;

[0079] S206, simulating operation according to the fault data through the target function model to obtain a first operation parameter;

[0080] S208, simulating the operation of the function model in communication connection with the target function model according to the first operation parameter to obtain the second operation parameter of the function model operation.

[0081] The hardware-in-the-loop module includes a fault injection model and multiple functional models, at least two of the multiple functional models are communicatively connected,

[0082] In this embodiment, the hardware-in-the-loop module may include a fault injection model and multiple functional models. Among them, the multiple functional models are used to simulate the operation of devices at different positions of the robot. For example, through different functional models, the operation of the robot's cable equipment, the operation of the robot's drive equipment, or the operation of the robot's transmission equipment are simulated respectively. At the same time, at least two of the multiple functional models are communicatively connected to simulate the communication connection between different devices of the robot. For example, the communication connection between the robot's cable equipment and the drive equipment, the communication connection between the robot's drive equipment and the transmission equipment, etc.

[0083] Furthermore, the fault injection model can generate fault data corresponding to the preset fault information according to the acquired preset fault information, and then the fault injection model can also inject the fault data corresponding to the preset fault information into the corresponding functional model. That is, the fault injection model is respectively connected to the communication between the multiple functional models to ensure that the fault injection model can inject the preset fault information into the corresponding functional model, so as to ensure that the functional model can simulate the operation of the robot under the preset fault.

[0084] Specifically, during the robot simulation process, the preset fault information is first obtained. After the preset fault information is obtained, the fault injection model generates fault data corresponding to the preset fault information according to the preset fault information, and can also determine the target functional model corresponding to the preset fault information in multiple functional models. That is, the location where the preset fault indicated by the preset fault information occurs.

[0085] Further, after determining the target function model and the fault data, the fault injection model injects the fault data into the target function model so that the target function model can simulate operation according to the fault data. That is, the corresponding equipment of the simulated robot operates under the condition of a preset fault. At the same time, the first operation parameter is obtained. That is, the first operation parameter of the corresponding equipment of the robot during operation under the condition of a preset fault.

[0086] Furthermore, the functional model that is communicatively connected to the target functional model can also simulate operation according to the first operating parameters generated during the simulated operation of the target functional model, that is, simulate the operating parameters of the relevant equipment in the robot when other equipment has a preset fault, so as to obtain the second operating parameters of other functional models that are communicatively connected to the target functional model.

[0087] It is understandable that when one of the devices of the robot fails, not only the operating parameters of the failed device will change under the influence of the failure, but also the operating parameters of other devices connected to the device will also change due to the change of the operating parameters of the device. Through the communication connection between multiple functional models of the hardware-in-the-loop module, the operating parameters of other devices in the case of a preset failure of one of the devices of the robot can be effectively simulated, so that the simulation process of the robot is close to the actual operation of the robot, thereby improving the effect of the robot's fault rehearsal.

[0088] Furthermore, the multiple functional models include: a cable model, a driver model, a transmission model and a load model.

[0089] Specifically, the functional model of the hardware-in-the-loop module may include at least a cable model, a driver model, a transmission model and a load model, wherein the cable model is communicatively connected to the driver model, the transmission model is communicatively connected to the driver model, and the load model is communicatively connected to the transmission model.

[0090] Specifically, during the fault rehearsal process, when a cable device fails, the driver model receives the parameters of the cable model to simulate the operation of the robot's driver. When a driver fails, the transmission model receives the parameters of the driver model to simulate the operation of the robot's transmission. At the same time, the cable model also receives the parameters of the driver model to simulate the operation of the robot's cable device. When a transmission fails, the load model receives the parameters of the transmission model to simulate the operation of the robot's load. At the same time, the driver model also receives the parameters of the transmission model to simulate the operation of the robot's driver.

[0091] According to one embodiment of the present invention, Figure 3 As shown, a robot simulation method is proposed, including:

[0092] S302, generating multiple different types of preset fault information;

[0093] S304, storing the preset fault information in the fault storage model;

[0094] S306, obtaining preset fault information;

[0095] S308, according to the preset fault information, simulating the operation of the robot under the preset fault indicated by the preset fault information through the hardware-in-the-loop module to obtain the operation parameters of the robot under the preset fault.

[0096] In this embodiment, the hardware-in-the-loop module may also include a fault storage model, through which a variety of preset fault information can be stored, so that the preset fault information can be retrieved through the fault injection model during the robot's fault language process. It can be understood that the fault storage model is communicatively connected with the fault injection model to ensure that the fault injection model can retrieve the corresponding preset fault information from the fault storage model.

[0097] Furthermore, before the fault injection model obtains the preset fault information from the fault storage model, a plurality of preset fault information may be generated by the host device, and then the plurality of preset fault information is stored in the fault storage model for acquisition by the fault injection model.

[0098] According to one embodiment of the present invention, Figure 4 As shown, a robot simulation method is proposed, including:

[0099] S402, generating multiple different types of preset fault information;

[0100] S404, storing the preset fault information in the fault storage model;

[0101] S406, obtaining preset fault information;

[0102] S408, according to the preset fault information, simulating the operation of the robot under the preset fault indicated by the preset fault information through the hardware-in-the-loop module to obtain the operation parameters of the robot under the preset fault;

[0103] S410, develop a fault prediction algorithm based on the operating parameters;

[0104] S412, when receiving the operation instruction of the robot, simulating the operation of the robot through the hardware-in-the-loop module to verify the fault prediction algorithm.

[0105] In this embodiment, after the robot's fault rehearsal is completed and the robot's operating parameters under the preset fault are obtained, a fault prediction algorithm can be developed based on the operating parameters. It can be understood that the fault prediction algorithm is used to predict the robot's impending fault during the robot's operation, so that the robot can be adjusted in time before the robot fails, avoiding the robot's failure, avoiding robot damage, and reducing losses.

[0106] Furthermore, the developed fault prediction algorithm can also be verified through the hardware-in-the-loop module to determine whether the fault prediction algorithm is effective. Specifically, the fault prediction algorithm can be injected into the hardware-in-the-loop module, and according to the robot's operating instructions, the robot operation can be simulated through the hardware-in-the-loop module. During the robot simulation operation, the fault prediction algorithm is verified to determine whether the fault prediction algorithm can effectively predict the upcoming fault. Moreover, in the case that the fault prediction algorithm is invalid, the robot's fault rehearsal can be performed again through the hardware-in-the-loop module, the robot's operating parameters under the preset fault are re-obtained, and the fault prediction algorithm is developed according to the operating parameters. Until the fault prediction algorithm can effectively predict the robot's fault.

[0107] According to one embodiment of the present invention, Figure 5 As shown, a robot simulation method is proposed, including:

[0108] S502, generating multiple different types of preset fault information;

[0109] S504, storing the preset fault information in the fault storage model;

[0110] S506, obtaining the operation instruction of the robot;

[0111] S508, simulating the robot operation through the hardware-in-the-loop module according to the operation instruction;

[0112] S510, obtaining preset fault information;

[0113] S512, according to the preset fault information, simulating, through the hardware-in-the-loop module, the operation of the robot under the preset fault indicated by the preset fault information, so as to obtain the operation parameters of the robot under the preset fault;

[0114] S514, develop a fault prediction algorithm based on the operating parameters;

[0115] S516, when receiving the operation instruction of the robot, simulating the operation of the robot through the hardware-in-the-loop module to verify the fault prediction algorithm.

[0116] In this embodiment, before obtaining the preset fault information, the normal operation of the robot can be simulated by the hardware-in-the-loop module. After the simulation of the normal operation of the robot begins, the preset fault information is obtained, and the fault information is injected through the fault injection model to simulate the operation of the robot under the preset fault.

[0117] Specifically, the operation instructions of the robot can be set by the host computer, and the operation instructions can indicate parameters such as the robot's operation trajectory, operation speed, and load during operation.

[0118] According to a second aspect of the present invention, a simulation device for a robot is proposed, comprising: an acquisition module for acquiring preset fault information; a hardware-in-the-loop module for simulating the operation of the robot under a preset fault indicated by the preset fault information according to the preset fault information, so as to obtain the operating parameters of the robot under the preset fault information.

[0119] The robot simulation method provided by the present invention simulates the operation of the robot through a hardware-in-the-loop module. In the process of setting the fault, the preset fault information can be directly injected into the hardware-in-the-loop module without setting the fault parameters on the physical robot, so that different types of fault languages ​​can be performed multiple times in a short period of time, thereby effectively improving the efficiency of the robot's fault rehearsal. At the same time, since the physical robot does not need to participate in the fault language process, the robot will not fail in the actual operation process, and the robot will not be damaged due to the failure, thereby effectively reducing the cost of the robot's fault rehearsal.

[0120] Furthermore, the hardware-in-the-loop module includes a fault injection model and multiple functional models, and at least two of the multiple functional models are communicatively connected. The fault injection model is used to generate fault data corresponding to the preset fault information according to the preset fault information, and to determine the target functional model among the multiple functional models; the target functional model is used to simulate operation according to the fault data to obtain a first operating parameter; and the functional model communicatively connected to the target functional model is also used to simulate operation according to the first operating parameter to obtain a second operating parameter for the functional model operation.

[0121] Among them, the functional model includes cable model, driver model, transmission model and load model.

[0122] Furthermore, the simulation device may further include a fault information generation module, which is used to generate preset fault information. The hardware-in-the-loop module also includes a fault storage model, which is used to store preset fault information.

[0123] Furthermore, the simulation device may also include a development module for developing a fault prediction algorithm according to the operation parameters. The hardware-in-the-loop module is also used to simulate the operation of the robot when receiving the operation instruction of the robot to verify the fault prediction algorithm.

[0124] Furthermore, before obtaining the preset fault information, the hardware-in-the-loop module is also used to obtain the operation instructions of the robot; and simulate the operation of the robot according to the operation instructions.

[0125] According to a third aspect of the present invention, a robot simulation device is proposed, comprising: a processor and a memory, the memory storing programs or instructions that can be run on the processor, and the programs or instructions, when executed by the processor, implement the steps of the robot simulation method provided in the first aspect.

[0126] The robot simulation device provided by the present invention includes a memory and a processor, and also includes a program or instruction stored in the memory. When the program or instruction is executed by the processor, it can implement the steps of the robot simulation method of the first aspect mentioned above. Therefore, the robot simulation device has all the beneficial effects of the robot simulation method mentioned above, which will not be repeated here.

[0127] According to a fourth aspect of the present invention, Figure 6 As shown, a robot simulation system is provided, comprising the robot simulation device as described in the second aspect above.

[0128] The robot simulation system provided by the present invention comprises the robot simulation device of the second aspect mentioned above, so the robot simulation system has all the beneficial effects of the robot simulation device mentioned above, which will not be elaborated here.

[0129] Furthermore, the robot simulation system also includes a control device, which is connected to the hardware-in-the-loop module in communication to control the operation of the hardware-in-the-loop module. The robot simulation system also includes a host computer, which is connected to the control device and the hardware-in-the-loop module in communication, and is used to generate preset fault information and control instructions for the robot, and send them to the hardware-in-the-loop module or the control device.

[0130] In the above technical scheme, further, the control device includes: an operation control module, which is communicatively connected to the host computer and is used to receive the operation instructions of the robot issued by the host computer; a servo control module, which is communicatively connected to the operation control module and the hardware-in-the-loop module respectively, and is used to convert the operation instructions of the robot into control data and transmit the control data to the hardware-in-the-loop module.

[0131] In the above technical solution, further, the host computer is communicatively connected with the fault storage model of the hardware-in-the-loop module to generate a plurality of different types of preset fault information and store them in the fault storage model.

[0132] In a specific embodiment, the simulation system of the robot may include: including a PC (i.e., the host computer of the present application), a robot control cabinet motion control module (i.e., the operation control module of the present application), a robot control cabinet servo control module (i.e., the servo control module of the present application), and a hardware-in-the-loop device (i.e., the hardware-in-the-loop module of the present application). Among them, the PC is connected to the hardware-in-the-loop module, the PC is connected to the robot control cabinet motion control module, the robot control cabinet motion control module is connected to the robot control cabinet servo control module; the robot control cabinet servo control module is connected to the hardware-in-the-loop module. The hardware-in-the-loop module includes a failure matrix module (i.e., the fault storage model of the present application), a fault injection module (and the fault injection model of the present application), a cable model, a motor model (i.e., the drive component model of the present application), a transmission model, and a load model, wherein the failure matrix is ​​obtained during the early design, and is converted into parameter changes of the cable model, the motor model, the transmission model, and the load model through the fault injection module, the cable model is associated with the motor model variable, the motor model is associated with the transmission model variable, and the transmission model is associated with the load model variable. During robot development and application, the fault prediction module can be equipped in the robot control cabinet software, can be loaded in the PC, or can be a module independent of the control cabinet and PC.

[0133] Furthermore, if Figure 7 As shown in the figure, in the process of verifying the fault language and fault prediction algorithm of the robot simulation system, the specific operation process is as follows:

[0134] 1. PC sends failure matrix module, fault injection module, cable model, motor model, transmission model and load module to hardware-in-the-loop equipment;

[0135] 2. The failure matrix records all potential faults analyzed and transmits the fault type to the fault injection module;

[0136] 3. After receiving the fault selection instruction, the fault injection module outputs the fault point and fault parameters to the cable model, motor model, transmission model and load model;

[0137] 4. The cable model receives data information from the servo control module of the robot control cabinet through the hardware-in-the-loop device, and drives the motor model to generate motor information of each axis of the robot;

[0138] 5. The motors of each axis of the robot receive the transmission data of the transmission model and the cable data of the cable model, thereby providing motor data for the cable model and the transmission model;

[0139] 6. The transmission model receives the motor data of the motor model and the load data of the load model, thereby providing transmission data for the motor model and the load model;

[0140] 7. The robot control cabinet servo control module receives information from the robot control cabinet motion control module to drive the hardware-in-the-loop device simulating the robot body;

[0141] 8. PC sends the robot trajectory running program to the motion control module of the robot control cabinet;

[0142] 9. PC sends load information to the hardware-in-the-loop device;

[0143] 10. The fault prediction module (i.e., hardware-in-the-loop module) receives information from the motion control module of the robot control cabinet to develop and verify the fault prediction algorithm.

[0144] Furthermore, if Figure 8 As shown, the usage process of the robot simulation system is as follows:

[0145] 1. Select the robot control cabinet motion control module and robot control cabinet servo control module used in the project implementation plan;

[0146] 2. Connect the motion control module to the servo control module;

[0147] 3. Connect the PC to the motion control module;

[0148] 4. Connect the PC to the hardware-in-the-loop device;

[0149] 5. Connect the hardware-in-the-loop device to the servo control module;

[0150] 6. Turn on the hardware-in-the-loop device and set the failure matrix on the PC;

[0151] 7. Load the fault injection module, cable model, motor model, transmission model and load model modules to the hardware-in-the-loop device;

[0152] 8. Start and operate the robot control cabinet motion control module and the robot control cabinet servo control module;

[0153] 9. Access the fault prediction module;

[0154] 10. Run hardware-in-the-loop devices;

[0155] 11. Perform fault injection on the PC.

[0156] 12. Develop and verify the fault prediction module.

[0157] According to a fifth aspect of the present invention, a readable storage medium is provided, on which a program or instruction is stored. When the program or instruction is executed by a processor, a simulation method of a robot as described in any one of the above technical solutions is implemented.

[0158] The readable storage medium provided by the present invention stores a program or instruction thereon. When the program or instruction is executed by the processor, it can implement a robot simulation method such as any one of the above-mentioned technical solutions. Therefore, the storage medium has all the beneficial effects of the above-mentioned robot simulation method, which will not be repeated here.

[0159] In the description of the present invention, the term "plurality" refers to two or more than two. Unless otherwise clearly defined, the orientation or positional relationship indicated by the terms "upper" and "lower" is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention. The terms "connection", "installation", "fixation", etc. should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0160] In the description of this specification, the description of the terms "one embodiment", "some embodiments", "specific embodiments", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0161] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A robot simulation method, characterized in that: include: Get preset fault information; According to the preset fault information, the operation of the robot under the preset fault indicated by the preset fault information is simulated by a hardware-in-the-loop module to obtain the operation parameters of the robot under the preset fault.

2. The simulation method according to claim 1, characterized in that: The hardware-in-the-loop module includes a fault injection model and multiple function models, at least two of the multiple function models are communicatively connected, and according to the preset fault information, the hardware-in-the-loop module is used to simulate the operation of the robot under the preset fault indicated by the preset fault information to obtain the operation parameters of the robot under the preset fault, including: According to the preset fault information, generating fault data corresponding to the preset fault information through the fault injection model, and determining a target functional model among the multiple functional models; Simulating operation according to the fault data through the target function model to obtain a first operating parameter; The functional model that is communicatively connected to the target functional model simulates operation according to the first operating parameters to obtain second operating parameters for the functional model.

3. The simulation method according to claim 2, characterized in that: The multiple functional models include: Cable model, driver model, transmission model and load model.

4. The simulation method according to any one of claims 1 to 3, characterized in that: The hardware-in-the-loop module also includes a fault storage model. Before obtaining the preset fault information, the simulation method also includes: Generate a plurality of different types of preset fault information; The preset fault information is stored in the fault storage model.

5. The simulation method according to any one of claims 1 to 3, characterized in that: The simulation method further comprises: developing a fault prediction algorithm based on the operating parameters; When the operation instruction of the robot is received, the operation of the robot is simulated by the hardware-in-the-loop module to verify the fault prediction algorithm.

6. The simulation method according to any one of claims 1 to 3, characterized in that: Before obtaining the preset fault information, the simulation method further includes: Obtaining an operating instruction of the robot; According to the operation instruction, the operation of the robot is simulated through the hardware-in-the-loop module.

7. A robot simulation device, characterized in that: include: An acquisition module, used to acquire preset fault information; The hardware-in-the-loop module is used to simulate the operation of the robot under the preset fault indicated by the preset fault information according to the preset fault information, so as to obtain the operation parameters of the robot under the preset fault information.

8. A robot simulation device, characterized in that: include: A processor and a memory, wherein the memory stores a program or instruction that can be run on the processor, and when the program or instruction is executed by the processor, the steps of the robot simulation method according to any one of claims 1 to 6 are implemented.

9. A robot simulation system, characterized in that: include: The simulation device as claimed in claim 7; A control device, communicatively connected to the hardware-in-the-loop module; The host computer is connected to the control device and the hardware-in-the-loop module respectively.

10. The simulation system according to claim 9, characterized in that: The control device comprises: An operation control module, which is in communication with the host computer and is used to receive an operation instruction of the robot issued by the host computer; The servo control module is respectively connected to the operation control module and the hardware-in-the-loop module for communication, and is used for converting the operation instruction of the robot into control data and transmitting the control data to the hardware-in-the-loop module.

11. The simulation system according to claim 9, characterized in that: The host computer is communicatively connected to the fault storage model of the hardware-in-the-loop module, and is used to generate a plurality of different types of preset fault information and store them in the fault storage model.

12. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the robot simulation method according to any one of claims 1 to 6 are implemented.

Images