Torque correction method, torque correction device, robot and storage medium

Abstract

The present application discloses a torque correction method, a torque correction device, a robot, and a storage medium. The torque correction method includes: obtaining a zero-bias error of a torque sensor; collecting a sampled voltage of the torque sensor under an external force using a sampling module; calculating a first torque based on the bias voltage, amplification factor, sensitivity, range, and sampling voltage of the sampling module; correcting the first torque based on the zero-bias error to obtain a second torque; determining a target correction coefficient of the torque sensor based on the second torque; and correcting the second torque based on the target correction coefficient to obtain a third torque. This method implements linear error correction of the first torque based on zero-bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor.

Description

Technical Field

[0001] The present application belongs to the field of robotics technology, and in particular relates to a torque correction method, a torque correction device, a robot, and a storage medium. Background Art

[0002] As a key device of the robot, the torque sensor is usually installed at the joint of the robot. The torque sensor is used to measure the torque borne by the robot joint. The accuracy range of the torque sensor determines the final operating effect of the robot.

[0003] At present, torque sensors have zero bias errors due to the influence of structure and external forces, and torque sensors have linear errors due to different sensitivities during mass production, resulting in low accuracy in measuring torque. Summary of the Invention

[0004] In view of this, embodiments of the present application provide a torque correction method, a torque correction device, a robot, and a storage medium to overcome the above problems of the prior art.

[0005] In a first aspect, an embodiment of the present application provides a torque correction method, including: obtaining a zero bias error of a torque sensor; collecting a sampling voltage of the torque sensor under an external force based on a sampling module; calculating a first torque based on the bias voltage, amplification factor, sensitivity, range and the sampling voltage of the acquisition circuit; correcting the first torque according to the zero bias error to obtain a second torque; determining a target correction coefficient of the torque sensor according to the second torque; and correcting the second torque according to the target correction coefficient to obtain a third torque.

[0006] Among them, in some optional embodiments, determining the target correction coefficient of the torque sensor based on the second torque includes: determining a torque correction interval based on the second torque; searching a correction coefficient table based on the torque correction interval to obtain the target correction coefficient, and the correction coefficient table is used to characterize the correspondence between the preset torque correction interval and the correction coefficient of the torque sensor.

[0007] Among them, in some optional embodiments, before the sampling module collects the collected voltage of the torque sensor under the action of external force, the torque correction method also includes: obtaining multiple test torques of the torque sensor under the action of multiple preset torques, the multiple preset torques respectively corresponding to the multiple test torques, one test torque corresponds to a preset torque, and each preset torque corresponds to a preset torque correction interval; constructing the correction coefficient table according to the multiple preset torque correction intervals, the multiple preset torques and the multiple test torques.

[0008] Among them, in some optional embodiments, the correction coefficient table is constructed according to multiple preset torque correction intervals, the multiple preset torques and the multiple test torques, including: determining a correction coefficient according to each preset torque and the test torque corresponding to each preset torque to obtain multiple correction coefficients; constructing the correction coefficient table according to each correction coefficient and the preset torque correction interval corresponding to each correction coefficient.

[0009] Among them, in some optional embodiments, the sampling module is used to collect the sampled voltage of the torque sensor under the action of external force, including: collecting the sampled digital value of the torque sensor under the action of external force based on the sampling module; and calculating the sampled voltage according to the sampling resolution of the sampling module and the sampled digital value.

[0010] Among them, in some optional embodiments, the calculation of the first torque based on the bias voltage, amplification factor, sensitivity, range and the sampling voltage of the sampling module includes: calculating the true voltage value based on the bias voltage and the sampling voltage; calculating the first torque according to the true voltage value, the amplification factor, the sensitivity and the range.

[0011] In some optional embodiments, obtaining the zero bias error of the torque sensor includes: obtaining a torque reading of the torque sensor in the absence of an external force; and determining the torque reading as the zero bias error.

[0012] In a second aspect, an embodiment of the present application provides a torque correction device, wherein the torque sensor correction device includes an error acquisition module, an acquisition module, a calculation module, a zero bias correction module, a determination module, and a coefficient correction module. The error acquisition module is used to acquire the zero bias error of the torque sensor; the acquisition module is used to acquire the sampled voltage of the torque sensor under the action of an external force based on the sampling module; the calculation module is used to calculate the first torque based on the bias voltage, amplification factor, sensitivity, range, and the sampled voltage of the sampling module; the zero bias correction module is used to correct the first torque according to the zero bias error to obtain a second torque; the determination module is used to determine the target correction coefficient of the torque sensor according to the second torque; and the coefficient correction module is used to correct the second torque according to the target correction coefficient to obtain a third torque.

[0013] In a third aspect, an embodiment of the present application provides a robot comprising a memory; one or more processors coupled to the memory; and one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, and the one or more applications are configured to execute the torque correction method provided in the first aspect above.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which a program code is stored. The program code can be called by a processor to execute the torque correction method provided in the first aspect above.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when running on a computer device, enables the computer device to execute the torque correction method provided in the first aspect above.

[0016] The solution provided by the present application obtains the zero bias error of the torque sensor, collects the sampled voltage of the torque sensor under the action of an external force based on a sampling module, calculates a first torque based on the bias voltage, amplification factor, sensitivity, range and sampling voltage of the sampling module, corrects the first torque based on the zero bias error to obtain a second torque, determines a target correction coefficient of the torque sensor based on the second torque, and corrects the second torque based on the target correction coefficient to obtain a third torque. This achieves linear error correction of the first torque based on zero bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor. Since the correction coefficient of the torque sensor is different under different torques, the target correction coefficient of the linear error correction is obtained based on the torque collected by the torque sensor, so that the target correction coefficient can be dynamically adjusted as the torque collected by the torque sensor changes, so that the torque collected by the torque sensor each time can be corrected by the matching target correction coefficient, which is conducive to further improving the measurement accuracy of the torque measured by the torque sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 A schematic diagram of a scenario of a torque correction system provided in an embodiment of the present application is shown.

[0019] Figure 2A flow chart of a torque correction method provided in an embodiment of the present application is shown.

[0020] Figure 3 Another flow chart of the torque correction method provided in an embodiment of the present application is shown.

[0021] Figure 4 A schematic diagram of a scenario flow of the torque correction method provided in an embodiment of the present application is shown.

[0022] Figure 5 A structural block diagram of the torque correction device provided in an embodiment of the present application is shown.

[0023] Figure 6 A functional block diagram of the robot provided in an embodiment of the present application is shown.

[0024] Figure 7 A computer-readable storage medium provided in an embodiment of the present application is shown for storing or carrying program code for implementing the torque correction method provided in an embodiment of the present application.

[0025] Figure 8 A computer program product provided in an embodiment of the present application is shown for storing or carrying program codes for implementing the torque correction method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the purpose, features, and advantages of the invention of this application more obvious and easy to understand, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the embodiments described below are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0027] It will be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0028] It should also be understood that the terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0029] It should be further understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0030] In addition, in the description of the present application, the terms "first", "second", "third", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0031] As a key device of the robot, the torque sensor is usually installed at the joint of the robot. The torque sensor is used to measure the torque borne by the robot joint. The accuracy range of the torque sensor determines the final operating effect of the robot.

[0032] At present, torque sensors have zero bias errors due to the influence of structure and external forces, and torque sensors have linear errors due to different sensitivities during mass production, resulting in low accuracy in measuring torque.

[0033] In response to the above problems, the torque correction method, torque correction device, robot and storage medium provided in the embodiments of the present application obtain the zero bias error of the torque sensor, and based on the sampling module, collect the sampled voltage of the torque sensor under the action of an external force, and calculate the first torque based on the bias voltage, amplification factor, sensitivity, range and the sampled voltage of the sampling module, and correct the first torque according to the zero bias error to obtain a second torque, and determine the target correction coefficient of the torque sensor according to the second torque, and correct the second torque according to the target correction coefficient to obtain a third torque, thereby achieving linear error correction of the first torque based on the zero bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor. Since the correction coefficient of the torque sensor is different under different torques, the target correction coefficient of the linear error correction is obtained based on the torque collected by the torque sensor, so that the target correction coefficient can be dynamically adjusted as the torque collected by the torque sensor changes, so that the torque collected by the torque sensor each time can be corrected by the matching target correction coefficient, which is conducive to further improving the measurement accuracy of the torque measured by the torque sensor.

[0034] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application.

[0035] See also Figure 1 , which shows a schematic diagram of an application scenario of the torque correction system provided in an embodiment of the present application, which may include a robot 100 and a processing device 200. The robot 100 is communicatively connected to the processing device 200 and exchanges data with the processing device 200.

[0036] Among them, the robot 100 can include a robot shell 110, a drive component 120 and a torque sensor 130. The drive component 120 and the torque sensor 130 are installed on the robot shell 110, and the robot shell 110 provides installation support and physical protection for the drive component 120 and the torque sensor 130.

[0037] The driving assembly 120 and the torque sensor 130 are communicatively connected to the processing device 200 and perform data exchange with the processing device 200 .

[0038] The robot 100 can be any one of a logistics robot, a warehousing robot, a delivery robot, an auxiliary walking robot, a companion robot, an intelligent mobility robot, a guide robot or a cleaning robot, etc. The type of the robot 100 is not limited here and can be set according to actual needs.

[0039] The processing device 200 may be a terminal device or a server, etc. The type of the processing device 200 is not limited here and can be specifically configured according to actual needs.

[0040] The terminal device can be a mobile terminal device (for example, any one of a mobile phone, a personal digital assistant (PDA), a tablet personal computer (Tablet PC), a laptop computer, a smart watch, a smart bracelet or a wearable device, etc.), or a fixed terminal device (desktop computer, smart panel, etc.).

[0041] The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or any cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), big data or artificial intelligence platforms, etc.

[0042] In some embodiments, the robot 100 can be integrated with the processing device 200 to form an integrated device. For example, the processing device 200 can be embedded in the robot 100 and form an integrated device together with the robot 100. In addition, the robot 100 can also be independently provided as a separate body from the processing device 200, which is not limited here.

[0043] See also Figure 2 , which shows a flow chart of a torque correction method provided by an embodiment of the present application. In a specific embodiment, the torque correction method can be applied to Figure 1The processing device 200 in the torque correction system shown in FIG. 2 is taken as an example below. Figure 2 The process shown in FIG. 1 is described in detail. The torque correction method may include the following steps S110 to S160.

[0044] Step S110: Obtain the zero bias error of the torque sensor.

[0045] In an embodiment of the present application, when a user needs to calibrate the measured torque of the torque sensor, a correction instruction can be sent to a processing device. The processing device receives and responds to the correction instruction to obtain the zero bias error of the torque sensor.

[0046] The zero bias error may be caused by the structure of the torque sensor and / or the external force applied to the torque sensor. For example, the zero bias error may be caused by an installation error of the torque sensor.

[0047] In some embodiments, when the user needs to correct the measured torque of the torque sensor, a correction instruction can be sent to the processing device. The processing device receives and responds to the correction instruction, obtains the torque reading of the torque sensor in the absence of external force, and determines the torque reading as the zero bias error. The zero bias error of the torque sensor is determined based on the real-time torque reading of the torque sensor in the absence of external force, thereby ensuring that the accuracy of the obtained zero bias error is high.

[0048] As an embodiment, the robot may include a camera, which is communicatively connected to the processing device and exchanges data with the processing device.

[0049] When the user needs to calibrate the measured torque of the torque sensor, a correction instruction can be sent to the processing device. The processing device receives and responds to the correction instruction and sends an acquisition instruction to the camera. The camera receives and responds to the acquisition instruction, acquires an image of the torque sensor without external force, obtains a torque sensor image, and sends the torque sensor image to the processing device. The processing device receives the torque sensor image returned by the camera, performs image recognition on the torque sensor image, obtains the torque reading of the torque sensor without external force, and determines the torque reading as the zero bias error.

[0050] Among them, the camera can be any one of a wide-angle camera, a macro camera, an ultra-wide-angle camera or a panoramic camera, etc. The type of camera is not limited here and can be set according to actual needs.

[0051] As an implementation method, when the user needs to correct the measured torque of the torque sensor, a correction instruction can be sent to the processing device. The processing device receives and responds to the correction instruction, generates a first prompt message, and receives the torque reading of the torque sensor in the absence of external force uploaded by the user according to the first prompt message, and determines the torque reading as the zero bias error.

[0052] Among them, the first prompt information is used to prompt the user to upload the torque reading of the torque sensor in the absence of external force to the processing device. The first prompt information can be at least any one of text prompt information, sound prompt information or light prompt information, etc., which is not limited here.

[0053] In some embodiments, the processing device pre-stores the zero bias error of the torque sensor. When the user needs to correct the measured torque of the torque sensor, a correction instruction can be sent to the processing device. The processing device receives and responds to the correction instruction and reads the pre-stored zero bias error.

[0054] In some embodiments, the torque sensor pre-stores a zero bias error of the torque sensor. When the user needs to correct the measured torque of the torque sensor, a correction instruction can be sent to the processing device. The processing device receives and responds to the correction instruction, and sends an acquisition instruction to the torque sensor. The torque sensor receives and responds to the acquisition instruction, and sends the pre-stored zero bias error to the processing device. The processing device receives the zero bias error returned by the torque sensor.

[0055] In some embodiments, the processing device may be provided with an input panel. When a user needs to calibrate the measured torque of the torque sensor, the user may input a correction instruction on the input panel of the processing device, for example, by handwriting the correction instruction on the input panel of the processing device, or by pressing a button on the input panel of the processing device to input the correction instruction. The processing device receives the correction instruction through the input panel.

[0056] In some embodiments, the processing device may be provided with a voice recognition module. When a user needs to correct the measured torque of the torque sensor, the user may send voice information within the voice collection range of the voice recognition module. The voice recognition module collects the voice information sent by the user and performs voice recognition on the collected voice information to obtain a voice recognition result. When it is determined that the voice recognition result contains keywords for instructing the processing device to correct the measured torque of the torque sensor, for example, the keyword is "measured torque correction", or for another example, the keywords are "measured torque" and "correction", etc., it is determined that the correction instruction has been received.

[0057] As an example, the voice message sent by the user is: calibrate the measured torque of the torque sensor, and the voice recognition result of the voice recognition contains the keywords "measured torque" and "correction", then it is determined that the correction instruction is received.

[0058] In some embodiments, when a user needs to calibrate the measured torque of the torque sensor, a correction instruction can be sent to the client. The client receives and responds to the correction instruction, forwards the correction instruction to the processing device through the network, and the processing device receives the correction instruction forwarded by the client.

[0059] The client is connected to the processing device via a network and exchanges data with the processing device via the network. The client can be any of a mobile client (e.g., a mobile phone client, a PDA client, a tablet PC client, a laptop client, a smart watch client, a smart bracelet client, or a wearable client) or a fixed client (e.g., a desktop computer client, a smart panel client, etc.). The type of learning client is not limited here and can be set according to actual needs.

[0060] The network can be any one of a ZigBee network, a Bluetooth (BT) network, a Wireless Fidelity (Wi-Fi) network, a Thread network, a Long Range Radio (LoRa) network, a Low-Power Wide-Area Network (LPWAN), an infrared network, a Narrow Band Internet of Things (NB-IoT), a Controller Area Network (CAN), a Digital Living Network Alliance (DLNA) network, a Wide Area Network (WAN), a Local Area Network (LAN), a Metropolitan Area Network (MAN) or a Wireless Personal Area Network (WPAN), etc. The type of network is not limited here and can be set according to actual needs.

[0061] In one application scenario, the torque reading of the torque sensor without external force is T0, and the torque reading T0 can be determined as the zero bias error T of the torque sensor. err .

[0062] The torque reading T0 may be 0 or may not be 0. The value of the torque reading T0 is not limited here and may be set according to actual needs.

[0063] Step S120: collecting a sampled voltage of the torque sensor under the action of an external force based on the sampling module.

[0064] In an embodiment of the present application, the torque sensor deforms under the action of an external force, and the torque sensor converts the strain caused by the deformation into a voltage signal. The processing device can collect the sampling voltage of the torque sensor under the action of the external force based on the sampling module, so as to calculate the measured torque of the torque sensor based on the sampling voltage.

[0065] The external force is the force applied to the torque sensor from the outside, and the external force is within the force range corresponding to the measuring range of the torque sensor.

[0066] Specifically, the processing device may collect the sampled digital value of the torque sensor under the action of the external force based on the sampling module, and calculate the sampled voltage according to the sampling resolution of the sampling module and the sampled digital value.

[0067] In one application scenario, the sampling module is a single-chip ADC, the sampling resolution of the single-chip ADC is P, and the maximum sampling voltage of the single-chip ADC is U max The processing device can sample the voltage signal of the torque sensor under the action of external force based on the MCU ADC. When the MCU ADC collects the sampling digital value A of the torque sensor under the action of external force, the sampling digital value A, the sampling resolution P and the maximum sampling voltage U can be used to calculate the value. max , according to formula 1, calculate the sampling voltage U0 of the torque sensor under the action of external force.

[0068] Formula 1: U0=A / P·U max .

[0069] Among them, the maximum sampling voltage U max It is generally 3.3V, and the sampling resolution P can be 4096 (12 bits), 1024 (10 bits), or 16384 (14 bits), etc., which are not limited here.

[0070] It should be noted that, in the embodiment of the present application, there is no order between step S110 and step S120. The zero bias error of the torque sensor can also be obtained after the sampling voltage of the torque sensor under the action of external force is collected based on the sampling module.

[0071] Step S130: Calculating a first torque based on the bias voltage, amplification factor, sensitivity, range, and sampling voltage of the sampling module.

[0072] In an embodiment of the present application, the processing device can calculate the true voltage value based on the bias voltage and sampling voltage of the sampling module, and calculate the first torque based on the true voltage value, amplification factor, sensitivity and range, and calculate the measured torque of the torque sensor based on the sampling voltage, thereby ensuring the calculation accuracy of the measured torque of the torque sensor.

[0073] Specifically, the range includes a voltage range and a torque range, the bias voltage of the sampling module is Vref, the amplification factor is M, the sensitivity is S, the voltage range is U1, and the torque range is Range.

[0074] The sampling module collects the sampling voltage U0 of the torque sensor under the action of external force. The processing device can calculate the actual voltage value U2 of the torque sensor under the action of external force collected by the sampling module according to the bias voltage Vref and the sampling voltage U0 according to Formula 2.

[0075] Formula 2: U2 = U0 - Vref = A / P·U max -Vref.

[0076] The processing device can calculate the first torque T1 according to Formula 3 based on the actual voltage value U2, the magnification M, the sensitivity S, the voltage range U1 and the torque range Range.

[0077] Formula 3: T1=U2·Range / (U1·M·S)=(A / P·U max -Vref)·Range / (U1·M·S).

[0078] In one application scenario, the sampling module is a single-chip ADC, the bias voltage of the single-chip ADC is Vref, the magnification is M, the sensitivity is S, the voltage range is U1, the torque range is Range, the sampling resolution is P, and the maximum sampling voltage is U max When the ADC of the single chip microcomputer collects the sampled digital value A of the torque sensor under the action of the external force, the first torque T1 can be calculated according to formula 3.

[0079] T1=(A / P·U max -Vref)·Range / (U1·M·S).

[0080] Step S140: Correcting the first torque according to the zero bias error to obtain a second torque.

[0081] In an embodiment of the present application, the processing device can correct the first torque according to the zero bias error to obtain the second torque, thereby realizing the correction of the first torque collected by the torque sensor based on the zero bias error of the torque sensor, which is beneficial to improving the measurement accuracy of the torque measured by the torque sensor.

[0082] Regarding the process in which the processing device corrects the first torque according to the zero bias error to obtain the second torque, in some embodiments, the processing device may calculate the torque difference between the first torque and the zero bias error to obtain the second torque.

[0083] In one application scenario, the zero bias error of the torque sensor is T err , the first moment is T1, which can be calculated based on the zero bias error T err And the first moment T1, according to formula 4, calculate the second moment T2.

[0084] Formula 4: T2 = T1 - T err .

[0085] Step S150: Determine a target correction coefficient of the torque sensor according to the second torque.

[0086] In the embodiment of the present application, the processing device corrects the first torque according to the zero bias error to obtain the second torque, and then determines the target correction coefficient of the torque sensor according to the second torque.

[0087] Specifically, the processing device corrects the first torque according to the zero bias error to obtain the second torque, and then determines the torque correction interval according to the second torque, and searches the correction coefficient table according to the torque correction interval to obtain the target correction coefficient.

[0088] The correction coefficient table can be used to characterize the correspondence between the preset torque correction intervals and the correction coefficients of the torque sensor. For example, the preset torque correction intervals of the torque sensor may be (0-4]NM, (4-8]NM, (8-12]NM, (12-16]NM, and (16-20]NM), and the correction coefficients may be K1, K2, K3, K4, and K5. The correspondence between the preset torque correction intervals and the correction coefficients can be shown in Table 1, i.e., the correction coefficient table. Based on this correspondence, the target correction coefficient corresponding to the second torque can be obtained.

[0089] Table 1

[0090] Preset torque correction range (NM) Correction factor (0-4] K1 (4-8] K2 (8-12] K3 (12-16] K4 (16-20] K5

[0091] It should be noted that the correspondence between the preset torque correction interval and the correction coefficient of the torque sensor is not limited to that shown in Table 1, and can be set according to actual needs.

[0092] Step S160: Correct the second torque according to the target correction coefficient to obtain a third torque.

[0093] In an embodiment of the present application, after the processing device determines the target correction coefficient of the torque sensor based on the second torque, the second torque can be corrected according to the target correction coefficient to obtain a third torque, thereby realizing linear error correction of the first torque based on zero bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor.

[0094] Regarding the process in which the processing device corrects the second torque according to the target correction coefficient to obtain the third torque, in some embodiments, the processing device may calculate the product of the second torque and the target correction coefficient to obtain the third torque.

[0095] In an application scenario, the second torque is T2, and the target correction coefficient corresponding to the second torque T2 is K. The third torque T3 can be calculated according to the second torque T2 and the target correction coefficient K according to Formula 5.

[0096] Formula 5 is:

[0097] T3=T2·K=(T1-T err )·K=((A / P·U1-Vref)·Range / (U1·M·S)-T err )

[0098] *K.

[0099] In some embodiments, after the processing device obtains the zero bias error of the torque sensor, it can obtain multiple test torques of the torque sensor under multiple preset torques, and the multiple preset torques correspond one-to-one to the multiple test torques, one test torque corresponds to one preset torque, and each preset torque corresponds to a preset torque correction interval. A correction coefficient table is constructed based on the multiple preset torque correction intervals, the multiple preset torques and the multiple test torques, and the sampling voltage of the torque sensor under the action of external force is collected based on the sampling module, and the first torque is corrected according to the zero bias error to obtain the second torque, and the correction coefficient table is searched according to the second torque to obtain the target correction coefficient, and the second torque is corrected according to the target correction coefficient to obtain the third torque. The correction coefficient table is constructed based on the multiple preset torques and the multiple test torques, thereby improving the accuracy of constructing the correction coefficient table.

[0100] Each test torque is a torque measured by the torque sensor under the action of a preset torque.

[0101] The processing device can determine a correction coefficient according to each preset torque and a test torque corresponding to each preset torque to obtain multiple correction coefficients, and construct a correction coefficient table according to each correction coefficient and a preset torque correction interval corresponding to each correction coefficient.

[0102] In one application scenario, the plurality of preset torques may include a first preset torque of 4 NM, a second preset torque of 8 NM, a third preset torque of 12 NM, a fourth preset torque of 16 NM, and a fifth preset torque of 20 NM.

[0103] A first preset torque of 4 NM is applied to the torque sensor, and a first test torque Ta1 of the torque sensor under the first preset torque of 4 NM is recorded. A second preset torque of 8 NM is applied to the torque sensor, and a second test torque Ta2 of the torque sensor under the second preset torque of 8 NM is recorded. A third preset torque of 12 NM is applied to the torque sensor, and a third test torque Ta3 of the torque sensor under the third preset torque of 12 NM is recorded. A fourth preset torque of 16 NM is applied to the torque sensor, and a fourth test torque Ta4 of the torque sensor under the fourth preset torque of 16 NM is recorded. A fifth preset torque of 20 NM is applied to the torque sensor, and a fifth test torque Ta5 of the torque sensor under the fifth preset torque of 20 NM is recorded.

[0104] According to the first preset torque 4 NM and the first test torque Ta1 , the first correction coefficient K1 is calculated according to Formula 6.

[0105] Formula six is: K1=4 / Ta1.

[0106] According to the second preset torque 8 NM and the second test torque Ta2, the second correction coefficient K2 is calculated according to Formula 7.

[0107] Formula seven is: K2=8 / Ta2.

[0108] According to the third preset torque 12 NM and the third test torque Ta3, the third correction coefficient K3 is calculated according to Formula 8.

[0109] Formula eight is: K3=12 / Ta3.

[0110] According to the fourth preset torque 16 NM and the fourth test torque Ta4, the fourth correction coefficient K4 is calculated according to Formula 9.

[0111] Formula nine is: K4=16 / Ta4.

[0112] According to the fifth preset torque 20 NM and the fifth test torque Ta5, the fifth correction coefficient K5 is calculated according to Formula 10.

[0113] Formula 10 is: K5=20 / Ta5.

[0114] In one application scenario, such as Figure 3 As shown, the calibration method of the torque sensor may include steps S210 to S250.

[0115] Step S210: Collect the sampled digital value of the torque sensor.

[0116] Among them, the analog signal of the torque sensor under the action of external force can be collected based on the sampling module. The analog signal is a voltage signal, and the voltage signal is amplified based on the amplification circuit to obtain an amplified voltage signal, and the amplified signal is converted into a digital signal with a period of 1ms to obtain a sampling voltage.

[0117] Step S220: Calculating a first torque based on the sampled voltage.

[0118] Step S230: Correct the first torque according to the zero bias error to obtain a second torque.

[0119] Step S240: Correct the second torque according to the target correction coefficient to obtain a third torque.

[0120] Step S250: output the third torque.

[0121] The solution provided in this embodiment obtains the zero bias error of the torque sensor, collects the sampled voltage of the torque sensor under the action of an external force based on a sampling module, calculates a first torque based on the bias voltage, amplification factor, sensitivity, range, and sampled voltage of the sampling module, corrects the first torque based on the zero bias error to obtain a second torque, determines a target correction coefficient for the torque sensor based on the second torque, and corrects the second torque based on the target correction coefficient to obtain a third torque. This achieves linear error correction of the first torque based on zero bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor. Because the correction coefficient of the torque sensor varies under different torques, the target correction coefficient for linear error correction is obtained based on the torque collected by the torque sensor. This allows the target correction coefficient to be dynamically adjusted as the torque collected by the torque sensor changes, so that each torque collected by the torque sensor can be corrected by the matching target correction coefficient, which is beneficial to further improving the measurement accuracy of the torque measured by the torque sensor.

[0122] See also Figure 4 , which shows a flow chart of a torque correction method provided by another embodiment of the present application. In a specific embodiment, the torque correction method can be applied to Figure 1 The processing device 200 in the torque correction system shown in FIG. 2 is taken as an example below. Figure 4 The process shown in FIG3 is described in detail. The torque correction method may include the following steps S310 to S380.

[0123] Step S310: Obtain the zero bias error of the torque sensor.

[0124] Step S320: collecting a sampled voltage of the torque sensor under the action of an external force based on the sampling module.

[0125] Step S330: Calculate the first torque based on the bias voltage, amplification factor, sensitivity, range and sampling voltage of the sampling module.

[0126] Step S340: Correct the first torque according to the zero bias error to obtain a second torque.

[0127] Step S350: Determine a target correction coefficient of the torque sensor according to the second torque.

[0128] Step S360: Correct the second torque according to the target correction coefficient to obtain a third torque.

[0129] In this embodiment, step S310 , step S320 , step S330 , step S340 , step S350 , and step S360 may refer to the contents of the corresponding steps in the aforementioned embodiments, and will not be repeated here.

[0130] Step S370: Generate a calibration record.

[0131] In this embodiment, the processing device corrects the second torque according to the target correction coefficient to obtain the third torque, and then generates a correction record.

[0132] The calibration record may include external force, zero bias error, first moment, second moment, target calibration coefficient, and third moment, etc., which are not limited here.

[0133] Step S380: Send the calibration record to the robot cloud platform so that the robot cloud platform stores the calibration record.

[0134] In this embodiment, the torque correction system may further include a robot cloud platform, which is connected to the processing device via a network and exchanges data with the processing device via the network.

[0135] After the processing device generates a calibration record, it can send the calibration record to the robot cloud platform via the network. The robot cloud platform receives and responds to the calibration record and stores the calibration record so that the user can trace the calibration process of the torque sensor according to the calibration record, thereby improving the user experience during the torque sensor calibration process.

[0136] Among them, the robot cloud platform can be an independent physical cloud platform, or a cloud platform cluster or distributed system composed of multiple physical cloud platforms. It can also be any one of the cloud platforms that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), big data or artificial intelligence platforms.

[0137] The solution provided in this embodiment obtains the zero bias error of the torque sensor, collects the sampled voltage of the torque sensor under the action of an external force based on a sampling module, calculates the first torque based on the bias voltage, amplification factor, sensitivity, range, and sampling voltage of the sampling module, corrects the first torque based on the zero bias error to obtain a second torque, determines the target correction coefficient of the torque sensor based on the second torque, corrects the second torque based on the target correction coefficient to obtain a third torque, generates a correction record, and sends the correction record to the robot cloud platform so that the robot cloud platform stores the correction record. This achieves linear error correction of the first torque based on zero bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor. Furthermore, the correction record is stored in the robot cloud platform so that users can trace the correction process of the torque measured by the torque sensor based on the correction record, thereby improving the user experience during the correction process of the torque measured by the torque sensor.

[0138] See also Figure 5 , which shows a torque correction device 300 provided by an embodiment of the present application. The torque correction device 300 can be applied to Figure 1 The processing device 200 in the torque correction system shown in FIG. 2 is taken as an example below. Figure 5 The torque correction device 300 shown is described in detail. The torque correction device 300 may include an error acquisition module 310 , an acquisition module 320 , a calculation module 330 , a zero bias correction module 340 , a determination module 350 and a coefficient correction module 360 ​​.

[0139] The error acquisition module 310 can be used to obtain the zero bias error of the torque sensor; the acquisition module 320 can be used to collect the sampling voltage of the torque sensor under the action of external force based on the sampling module; the calculation module 330 can be used to calculate the first torque based on the bias voltage, amplification factor, sensitivity, range and sampling voltage of the sampling module; the zero bias correction module 340 can be used to correct the first torque according to the zero bias error to obtain the second torque; the determination module 350 can be used to determine the target correction coefficient of the torque sensor according to the second torque; the coefficient correction module 360 ​​can be used to correct the second torque according to the target correction coefficient to obtain the third torque.

[0140] In some implementations, the determination module 350 may include a first determination unit and a search unit.

[0141] The first determination unit can be used to determine the torque correction interval based on the second torque; the search unit can be used to search the correction coefficient table based on the torque correction interval to obtain the target correction coefficient. The correction coefficient table can be used to characterize the correspondence between the preset torque correction interval and the correction coefficient of the torque sensor.

[0142] In some embodiments, the torque sensor calibration device 300 may further include a torque acquisition module and a construction module.

[0143] The torque acquisition module can be used to obtain multiple test torques of the torque sensor under multiple preset torques before the acquisition module 320 collects the sampling voltage of the torque sensor under the action of external force. The multiple preset torques can correspond one-to-one to multiple test torques, one test torque can correspond to a preset torque, and each preset torque can correspond to a preset torque correction interval; the construction module can be used to construct a correction coefficient table based on multiple preset torque correction intervals, multiple preset torques and multiple test torques.

[0144] In some embodiments, the building module may be used in the second determining unit as well as the building unit.

[0145] The second determination unit can be used to determine a correction coefficient based on each preset torque and a test torque corresponding to each preset torque to obtain multiple correction coefficients; the construction unit can be used to construct a correction coefficient table based on each correction coefficient and a preset torque correction interval corresponding to each correction coefficient.

[0146] In some implementations, the acquisition module 320 may include an acquisition unit and a first calculation unit.

[0147] The acquisition unit can be used to acquire the sampled digital value of the torque sensor under the action of external force based on the acquisition module; the first calculation unit can be used to calculate the sampled voltage according to the sampling resolution of the sampling module and the sampled digital value.

[0148] In some implementations, the calculation module 330 may include a second calculation unit and a third calculation unit.

[0149] The second calculation unit can be used to calculate the real voltage value based on the bias voltage and the sampled voltage; the third calculation unit can be used to calculate the first torque according to the real voltage value, amplification factor, sensitivity and range.

[0150] In some implementations, the error acquisition module 310 may include an acquisition unit and a third determination unit.

[0151] The acquiring unit may be used to acquire a torque reading of the torque sensor in the absence of an external force; and the third determining unit may be used to determine the torque reading as a zero bias error.

[0152] The solution provided in this embodiment obtains the zero bias error of the torque sensor, collects the sampled voltage of the torque sensor under the action of an external force based on a sampling module, calculates a first torque based on the bias voltage, amplification factor, sensitivity, range, and sampled voltage of the sampling module, corrects the first torque based on the zero bias error to obtain a second torque, determines a target correction coefficient for the torque sensor based on the second torque, and corrects the second torque based on the target correction coefficient to obtain a third torque. This achieves linear error correction of the first torque based on zero bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor. Because the correction coefficient of the torque sensor is different under different torques, the target correction coefficient for linear error correction is obtained based on the torque collected by the torque sensor, so that the target correction coefficient can be dynamically adjusted as the torque collected by the torque sensor changes, so that each torque collected by the torque sensor can be corrected by the matching target correction coefficient, which is conducive to further improving the measurement accuracy of the torque measured by the torque sensor.

[0153] It should be noted that the various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to in detail. For the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments. Any processing method described in the method embodiment can be implemented by the corresponding processing module in the device embodiment, and will not be repeated in detail in the device embodiment.

[0154] In addition, the functional modules in the various embodiments of the present application may be integrated into a processing module, or each module may exist physically separately, or two or more modules may be integrated into a single module. The above-mentioned integrated modules may be implemented in the form of hardware or software functional modules.

[0155] See also Figure 6 , which shows a functional block diagram of a robot 500 provided by an embodiment of the present application. The robot 500 may include one or more of the following components: a memory 510, a processor 520, and one or more applications, wherein the one or more applications may be stored in the memory 510 and configured to be executed by the one or more processors 520, and the one or more applications are configured to execute the method described in the aforementioned method embodiment.

[0156] The memory 510 may include a random access memory (RAM) or a read-only memory (ROM). The memory 510 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 510 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as obtaining a zero bias error, collecting a sampled voltage, calculating a first torque, correcting a first torque, obtaining a second torque, determining a target correction coefficient, correcting a second torque, obtaining a third torque, determining a torque correction interval, searching a correction coefficient table, obtaining a target correction coefficient, obtaining multiple test torques, constructing a correction coefficient table, determining a correction coefficient, obtaining multiple correction coefficients, collecting sampled digital values, calculating a true voltage value, obtaining a torque reading, and determining a zero bias error), instructions for implementing the following various method embodiments, etc. The storage data area can also store data created by the robot 500 during use (such as torque sensor, zero bias error, sampling module, sampling voltage, bias voltage, amplification factor, sensitivity, range, external force, first torque, second torque, target correction coefficient, third torque, torque correction interval, correction coefficient table, preset torque correction interval, correction coefficient, corresponding relationship, multiple preset torques, multiple test torques, sampling digital value, sampling resolution, true voltage value and torque reading), etc.

[0157] The processor 520 may include one or more processing cores. The processor 520 utilizes various interfaces and circuits to connect various components within the robot 500. It executes instructions, programs, code sets, or instruction sets stored in the memory 510, as well as accesses data stored in the memory 510, to perform various functions of the robot 500 and process data. Optionally, the processor 520 may be implemented using at least one hardware form factor selected from the group consisting of a digital signal processing (DSP), a field-programmable gate array (FPGA), and a programmable logic array (PLA). The processor 520 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing display content; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 520 and may instead be implemented via a separate communications chip.

[0158] Please refer to Figure 7 , which shows a block diagram of a computer-readable storage medium provided in an embodiment of the present application. The computer-readable storage medium 600 stores program code 610, which can be called by a processor to execute the method described in the above method embodiment.

[0159] The computer-readable storage medium 600 can be an electronic memory such as a flash memory, an EEPROM (Electrically Erasable Programmable Read-Only Memory), an EPROM, a hard disk, or a ROM. Alternatively, the computer-readable storage medium 600 includes a non-transitory computer-readable storage medium. The computer-readable storage medium 600 has storage space for program code 610 for executing any of the method steps in the above method. These program codes can be read from or written to one or more computer program products. The program code 610 can be compressed, for example, in a suitable form.

[0160] Please refer to Figure 8, which shows a block diagram of the structure of a computer program product 700 provided in an embodiment of the present application. Computer program product 700 includes a computer program / instructions 710, which is stored in a computer-readable storage medium of a computer device. When computer program product 700 is executed on a computer device, the computer device's processor reads computer program / instructions 710 from the computer-readable storage medium and executes computer program / instructions 710, causing the computer device to perform the method described in the above method embodiment.

[0161] The solution provided in this embodiment obtains the zero bias error of the torque sensor, collects the sampled voltage of the torque sensor under the action of an external force based on a sampling module, calculates a first torque based on the bias voltage, amplification factor, sensitivity, range, and sampled voltage of the sampling module, corrects the first torque based on the zero bias error to obtain a second torque, determines a target correction coefficient for the torque sensor based on the second torque, and corrects the second torque based on the target correction coefficient to obtain a third torque. This achieves linear error correction of the first torque based on zero bias correction of the first torque collected by the torque sensor, thereby improving the measurement accuracy of the torque measured by the torque sensor. Because the correction coefficient of the torque sensor is different under different torques, the target correction coefficient for linear error correction is obtained based on the torque collected by the torque sensor, so that the target correction coefficient can be dynamically adjusted as the torque collected by the torque sensor changes, so that each torque collected by the torque sensor can be corrected by the matching target correction coefficient, which is conducive to further improving the measurement accuracy of the torque measured by the torque sensor.

[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A torque correction method, characterized in that: include: Get the zero bias error of the torque sensor; Acquire multiple test torques of the torque sensor under multiple preset torques, wherein the multiple preset torques correspond one-to-one to the multiple test torques, one test torque corresponds to one preset torque, and each preset torque corresponds to a preset torque correction interval; Constructing a correction coefficient table according to the plurality of preset torque correction intervals, the plurality of preset torques, and the plurality of test torques, wherein the correction coefficient table is used to characterize a correspondence between the preset torque correction intervals and the correction coefficients of the torque sensor; Collecting a sampled voltage of the torque sensor under the action of an external force based on a sampling module; Calculating a first torque based on the bias voltage, amplification factor, sensitivity, range of the sampling module and the sampling voltage; Correcting the first torque according to the zero bias error to obtain a second torque; determining a torque correction interval according to the second torque; According to the torque correction interval, searching the correction coefficient table to obtain a target correction coefficient; The second torque is corrected according to the target correction coefficient to obtain a third torque.

2. The torque correction method according to claim 1, characterized in that: The constructing of a correction coefficient table according to the plurality of preset torque correction intervals, the plurality of preset torques, and the plurality of test torques comprises: Determining a correction coefficient according to each preset torque and the test torque corresponding to each preset torque to obtain a plurality of correction coefficients; The correction coefficient table is constructed according to each correction coefficient and the preset torque correction interval corresponding to each correction coefficient.

3. The torque correction method according to claim 1, characterized in that: The sampling module is used to collect the sampled voltage of the torque sensor under the action of the external force, including: Collecting a sampled digital value of the torque sensor under the action of an external force based on the sampling module; The sampled voltage is calculated according to the sampling resolution of the sampling module and the sampled digital value.

4. The torque correction method according to claim 1, characterized in that: The calculating of the first torque based on the bias voltage, amplification factor, sensitivity, range and the sampling voltage of the sampling module includes: Calculating a true voltage value based on the bias voltage and the sampled voltage; The first torque is calculated according to the real voltage value, the amplification factor, the sensitivity, and the range.

5. The torque correction method according to any one of claims 1 to 4, characterized in that: The obtaining of the zero bias error of the torque sensor includes: Obtaining a torque reading of the torque sensor in the absence of an external force; The torque reading is determined as the bias error.

6. A torque correction device, characterized in that: include: Error acquisition module, used to obtain the zero bias error of the torque sensor; a torque acquisition module, configured to acquire a plurality of test torques of the torque sensor under the action of a plurality of preset torques, wherein the plurality of preset torques respectively correspond one-to-one to the plurality of test torques, one test torque corresponds to one preset torque, and each preset torque corresponds to a preset torque correction interval; a construction module, configured to construct a correction coefficient table according to a plurality of preset torque correction intervals, the plurality of preset torques, and the plurality of test torques, wherein the correction coefficient table is configured to represent a correspondence between the preset torque correction intervals and the correction coefficients of the torque sensor; An acquisition module, configured to acquire a sampled voltage of the torque sensor under the action of an external force based on the sampling module; a calculation module, configured to calculate a first torque based on a bias voltage, a magnification, a sensitivity, a range of the sampling module and the sampling voltage; a zero bias correction module, configured to correct the first torque according to the zero bias error to obtain a second torque; a first determining unit, configured to determine a torque correction interval according to the second torque; a search unit, searching the correction coefficient table according to the torque correction interval to obtain a target correction coefficient; A coefficient correction module is used to correct the second torque according to the target correction coefficient to obtain a third torque.

7. A robot, characterized in that: include: Memory; one or more processors coupled to the memory; One or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, and the one or more application programs are configured to execute the torque correction method according to any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program codes, which can be called by a processor to execute the torque correction method according to any one of claims 1 to 5.

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