CN112199833B - Joint dynamics model optimization method, system, terminal equipment and storage medium - Google Patents
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Abstract
The application provides a joint dynamics model optimization method, a system, terminal equipment and a storage medium, wherein the method comprises the following steps: indicating the joint dynamics model to drive and control the joint according to the expected parameter value; acquiring a detection parameter value of the joint under the drive control of the joint dynamics model, and carrying out error operation according to the detection parameter value and an expected parameter value to obtain a dynamics error parameter value; and carrying out parameter optimization on the dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic error parameter values. According to the method and the device, the dynamic error parameter value is obtained through error operation according to the detection parameter value and the expected parameter value, the control error of the joint dynamic model on the joint can be calculated, the parameters of the dynamic equation in the joint dynamic model can be updated through parameter optimization according to the dynamic operation parameter value of the motor and the moment compensation equipment, and the accuracy of the dynamic control of the joint dynamic model is improved.
Description
Technical Field
The application belongs to the technical field of robots, and particularly relates to a joint dynamics model optimization method, a system, terminal equipment and a storage medium.
Background
One key problem in humanoid robot research is to increase walking speed. With the increase of the pace speed, the acceleration of the robot increases, so that the motor on the joint of the robot lacks sufficient driving capability (limitation of available power), and the movement capability of the robot is restricted. The moment compensation device is added under the driving mechanism of the original joint of the robot, so that the moment required by the motion of the bipedal robot can be compensated, for example, when the expected moment required by certain expected motions on the joint of the robot exceeds the moment limit of a motor, the required moment is supplemented by the moment compensation device, and the driving constraint of the joint of the robot is overcome.
In the existing robot joint control process, the driving control is carried out in a joint dynamics model mode, and after expected parameters of a robot joint are input into the joint dynamics model by a user, the joint dynamics model automatically carries out the driving control of the joint based on the expected parameters and a dynamics equation.
However, in the use process of the existing joint dynamics model, the corresponding dynamics operation parameter values of the motor and the moment compensation equipment on the robot joint in the dynamics equation of the joint dynamics model are set in a manner based on artificial experience, so that the parameter setting of the joint dynamics model is inaccurate, and the accuracy of the robot joint dynamics control is reduced.
Disclosure of Invention
The embodiment of the application provides a joint dynamics model optimization method, a system, terminal equipment and a storage medium, and aims to solve the problem that in the use process of an existing joint dynamics model, parameter setting of the joint dynamics model is inaccurate because corresponding dynamics operation parameter values of a motor and torque compensation equipment in the joint dynamics model are all set through manual experience.
In a first aspect, embodiments of the present application provide a method for optimizing a joint dynamics model, the method comprising:
inputting expected parameter values for joints into a joint dynamics model, and indicating the joint dynamics model to carry out driving control on the joints according to the expected parameter values;
acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and performing error operation according to the detection parameter value and the expected parameter value to obtain a dynamics error parameter value;
And carrying out parameter optimization on the dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic error parameter values, wherein the motor is used for driving the joint to rotate under the driving control of the joint dynamic model, and the moment compensation equipment is used for carrying out moment compensation on the motor.
Compared with the prior art, the embodiment of the application has the beneficial effects that: the control error of the joint dynamics model to the joint can be effectively calculated by carrying out error operation according to the detection parameter value and the expected parameter value to obtain the design of the dynamic error parameter value, and the parameter of the dynamics equation in the joint dynamics model can be effectively updated by carrying out parameter optimization design according to the dynamic operation parameter value of the motor and the moment compensation equipment on the joint in the joint dynamics model and further improving the accuracy of dynamic control of the joint dynamics model and preventing the phenomenon of inaccurate joint dynamics model caused by dynamic parameter setting by artificial experience.
Further, the kinetic equation in the joint kinetic model is:
τ＝Yp
Where τ is the torque loss value, τ o Is the output torque of the motor, tau i Is the input torque of the motor, p is the dynamic operation parameter value of the motor and the torque compensation device on the joint in the joint dynamic model, and k c Is the coulomb friction, k, of the joint v Is the coefficient of viscous friction of the joint, c 0 Is the coulomb frictional force fixed offset value of the joint,is the inertia of the motor and,θ、/>and->The detected value of the angular position, the detected value of the angular velocity and the detected value of the angular acceleration of the joint, k, are respectively among the detected parameter values p Is the compensation coefficient, theta, of the moment compensation device 0 Is a constant coefficient of the installation angle between the torque compensation device and the motor, and Y is the detection parameter value.
Further, the calculation formula adopted for performing error operation according to the detected parameter value and the expected parameter value is as follows:
wherein,is the dynamic error parameter value, theta d 、/>And->Respectively, the expected parameter values are for the expected value of the angular position, the expected value of the angular velocity and the expected value of the angular acceleration of the joint, Γ is a preset constant, +.>Comprises inertia optimized value, coulomb friction optimized value, viscosity friction optimized coefficient, compensation coefficient optimized value, coulomb friction fixed bias optimized value and constant coefficient optimized value And (5) value conversion.
Further, the parameter optimizing the dynamic operation parameter values of the motor and the moment compensation device on the joint in the joint dynamic model according to the dynamic error parameter values comprises the following steps:
and respectively carrying out parameter updating on inertia of the motor, coulomb friction of the joint, a coefficient of viscous friction of the joint, a compensation coefficient of the moment compensation device and a constant coefficient of an installation angle between the moment compensation device and the motor in the coulomb friction fixed offset value of the joint in the dynamic model of the joint according to the inertia optimized value, the coulomb friction optimized value, the viscous friction optimized coefficient, the compensation coefficient optimized value, the coulomb friction fixed offset optimized value and the constant coefficient optimized value in the dynamic error parameter value of the dynamic error.
Further, after the parameter optimization is performed on the dynamic operation parameter values of the motor and the moment compensation device on the joint in the joint dynamic model according to the dynamic error parameter values, the method further includes:
respectively obtaining parameter differences of different parameters between the dynamic operation parameter value and the dynamic error parameter value;
If the parameter difference value of any parameter between the dynamics error parameter value and the dynamics operation parameter value is larger than a difference threshold value, updating the expected parameter value, and inputting the updated expected parameter value into the joint dynamics model;
instructing the joint dynamics model to drive and control the joint according to the updated expected parameter value;
acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and performing error operation according to the detection parameter value and the updated expected parameter value to obtain a dynamic iteration parameter;
and carrying out parameter iteration on dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic iteration parameters.
Further, after the parameter differences of the different parameters between the kinetic operation parameter value and the kinetic error parameter value are obtained, the method further includes:
and if the parameter difference value of all the parameters between the dynamic error parameter value and the dynamic operation parameter value is smaller than or equal to the difference threshold value, stopping parameter optimization of the joint dynamic model.
In a second aspect, embodiments of the present application provide a joint dynamics model optimization system, including:
the system comprises an expected parameter value input module, a joint dynamic model and a control module, wherein the expected parameter value input module is used for inputting an expected parameter value for a joint into the joint dynamic model and indicating the joint dynamic model to carry out driving control on the joint according to the expected parameter value;
the error operation module is used for acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and carrying out error operation according to the detection parameter value and the expected parameter value to obtain a dynamics error parameter value;
the parameter optimization module is used for carrying out parameter optimization on the dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic error parameter values, the motor is used for driving the joint to rotate under the driving control of the joint dynamic model, and the moment compensation equipment is used for carrying out moment compensation on the motor.
Further, the joint dynamics model optimization system further comprises:
the optimization iteration module is used for respectively acquiring parameter differences of different parameters between the dynamic operation parameter value and the dynamic error parameter value;
If the parameter difference value of any parameter between the dynamics error parameter value and the dynamics operation parameter value is larger than a difference threshold value, updating the expected parameter value, and inputting the updated expected parameter value into the joint dynamics model;
instructing the joint dynamics model to drive and control the joint according to the updated expected parameter value;
acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and performing error operation according to the detection parameter value and the updated expected parameter value to obtain a dynamic iteration parameter;
and carrying out parameter iteration on dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic iteration parameters.
In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements a method as described above when executing the computer program.
In a fourth aspect, embodiments of the present application provide a storage medium storing a computer program that when executed by a processor implements a method as described above.
In a fifth aspect, embodiments of the present application provide a computer program product, which when run on a terminal device, causes the terminal device to perform the joint dynamics model optimization method according to any one of the first aspects above.
It will be appreciated that the advantages of the second to fifth aspects may be found in the relevant description of the first aspect, and are not described here again.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings used in the description of the embodiments or the prior art will be briefly described below.
FIG. 1 is a flow chart of a joint dynamics model optimization method provided in a first embodiment of the present application;
FIG. 2 is a schematic illustration of the structure between a motor, a joint and a torque compensation device provided in a first embodiment of the present application;
FIG. 3 is a schematic diagram of the information transfer structure between the speed feedback controller and the feedforward controller according to the first embodiment of the present application;
FIG. 4 is a flow chart of a joint dynamics model optimization method provided in a second embodiment of the present application;
FIG. 5 is a schematic structural view of an joint dynamics model optimization system provided in a third embodiment of the present application;
Fig. 6 is a schematic structural diagram of a terminal device according to a fourth embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
Example 1
Referring to fig. 1, a flowchart of a joint dynamics model optimization method according to a first embodiment of the present application includes the steps of:
and step S10, inputting expected parameter values aiming at joints into a joint dynamics model, and indicating the joint dynamics model to carry out driving control on the joints according to the expected parameter values.
Please refer to fig. 2, wherein the kinetic equation in the joint kinetic model is:
τ＝Yp
where τ is the torque loss value, τ o Is the output torque of the motor, tau i Is the input torque of the motor, p is the dynamic operation parameter value of the motor and the torque compensation device on the joint in the joint dynamic model, and k c Is the coulomb friction, k, of the joint v Is the coefficient of viscous friction of the joint, c 0 Is the coulomb frictional force fixed offset value of the joint,is the inertia, θ, & gt of the motor>And->The detected value of the angular position, the detected value of the angular velocity and the detected value of the angular acceleration of the joint, k, are respectively among the detected parameter values p Is the compensation coefficient, theta, of the moment compensation device 0 Is a constant coefficient of the installation angle between the torque compensation device and the motor, and Y is the detection parameter value.
Alternatively, in this embodiment, the torque compensation device may employ a parallel spring mechanism (Parallel Elastic Actuators, PEA), such as a parallel spring, then k p Is the elastic coefficient of parallel springs, theta 0 Is a constant related to the parallel spring mounting angle.
In equation 1, the inertia of the motor in pCoulomb friction force k of joint c Coefficient of viscous friction of joint, compensation coefficient k of moment compensation device p Coulomb friction fixed offset value c of joint 0 Compensation coefficient k of torque compensation device p And a constant coefficient theta of the installation angle between the torque compensation device and the motor 0 Are all estimated values, and the joint dynamics model optimization method is used for carrying out parameter aiming at each parameter in pAnd optimizing the number to improve the accuracy of the control and adjustment of the output torque and the input torque of the motor in the joint dynamics model.
In this step, the desired parameter values for the joint include an angular position desired value θ for the joint d Expected value of angular velocityAnd angular acceleration desired value +>Will angular position expectation value theta d Desired value of angular velocity->And angular acceleration desired value +>The expected parameter value of the joint is the angle state expected to be achieved by the user aiming at the joint angle, and the joint is driven and controlled according to the expected parameter value through the indication joint dynamics model, so that the subsequent detection of the real angle state of the joint is facilitated.
Step S20, obtaining a detection parameter value of the joint under the driving control of the joint dynamics model, and carrying out error operation according to the detection parameter value and the expected parameter value to obtain a dynamics error parameter value.
The calculation formula adopted for performing error operation according to the detection parameter value and the expected parameter value is as follows:
wherein,is the dynamic error parameter value, theta d 、/>And->Respectively, the expected parameter values are for the expected value of the angular position, the expected value of the angular velocity and the expected value of the angular acceleration of the joint, Γ is a preset constant, +.>Including inertia optimization valuesCoulomb friction optimized value k cd Optimizing coefficient k of viscous friction vd Optimized value k of compensation coefficient pd Coulomb friction force fixed bias optimization value c 0d Sum constant coefficient optimization value θ 0d ，Y r Is the desired value of the joint angular rotation for the desired parameter value.
Optionally, in this embodiment, p is a true value, which cannot be measured accurately;
an estimated value that is a true value, i.e., a value that is brought into calculation (updated value);
update law:
is the derivative of the estimated value and also of the error value (since the true value is a constant, the derivative is 0).
And step S30, carrying out parameter optimization on the dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic error parameter values.
The motor is used for driving the joint to rotate under the driving control of the joint dynamics model, the moment compensation equipment is used for compensating the moment of the motor, and in the step, parameters of a dynamics equation in the joint dynamics model can be effectively updated by carrying out parameter optimization design on the dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamics model according to the dynamic error parameter values, so that the accuracy of the joint dynamics model is improved.
Specifically, in the step, the parameter optimization is performed on the dynamic operation parameter values of the motor and the moment compensation device on the joint in the joint dynamic model according to the dynamic error parameter values, including:
and respectively carrying out parameter updating on inertia of the motor, coulomb friction of the joint, a coefficient of viscous friction of the joint, a compensation coefficient of the moment compensation device and a constant coefficient of an installation angle between the moment compensation device and the motor in the coulomb friction fixed offset value of the joint in the dynamic model of the joint according to the inertia optimized value, the coulomb friction optimized value, the viscous friction optimized coefficient, the compensation coefficient optimized value, the coulomb friction fixed offset optimized value and the constant coefficient optimized value in the dynamic error parameter value of the dynamic error.
Specifically, in the step, according to the inertia optimized value, the coulomb friction optimized value, the optimization coefficient of the viscous friction, the compensation coefficient optimized value, the coulomb friction fixed offset optimized value and the constant coefficient optimized value in the dynamic error parameter value, the updating formulas adopted for updating parameters of the inertia of the motor, the coulomb friction of the joint, the coefficient of the viscous friction of the joint, the compensation coefficient of the moment compensation device and the constant coefficient of the installation angle between the moment compensation device and the motor in the coulomb friction fixed offset value of the joint are respectively:
wherein,is the dynamic operation parameter value of the moment, +.>The value of the dynamic operation parameter at the upper time is an upper limit value and a lower limit value for each component of the vector, and if the value is not between the upper limit value and the lower limit value, the value is calculated according to the upper limit value and the lower limit value.
Optionally, referring to fig. 3, in this embodiment, a detection parameter value of a joint under driving control of a joint dynamics model may be obtained based on a speed feedback controller, and an error operation between the detection parameter value and an expected parameter value may be performed based on a feedforward controller to obtain a dynamics error parameter value, where the feedforward controller may optimize the joint dynamics model by adopting an adaptive learning manner, so as to improve convenience of joint dynamics model optimization.
In this embodiment, the design of the dynamic error parameter value is obtained by performing error operation according to the detected parameter value and the expected parameter value, so that the control error of the joint dynamic model on the joint can be effectively calculated, and the parameter of the dynamic equation in the joint dynamic model can be effectively updated by performing parameter optimization design on the dynamic operation parameter values of the motor and the torque compensation device on the joint in the joint dynamic model according to the dynamic error parameter value, thereby improving the accuracy of dynamic control of the joint dynamic model and preventing the phenomenon of inaccurate joint dynamic model caused by dynamic parameter setting by artificial experience.
Example two
Referring to fig. 4, a flowchart of a joint dynamics model optimization method according to a second embodiment of the present application, with respect to the embodiment corresponding to fig. 1, the joint dynamics model optimization method according to the present embodiment further includes, after step S30:
and S50, respectively acquiring parameter differences of different parameters between the dynamics operation parameter value and the dynamics error parameter value.
Wherein, respectively obtainAnd->Between, k cd And k is equal to c Between, k vd And k is equal to v Between k pd And k is equal to p Between, c 0d And c 0 Between, θ 0d And theta 0 The parameter difference value s is obtained 1 、s 2 、s 3 、s 4 、s 5 Sum s 6 。
And step S60, if the parameter difference value of all the parameters between the dynamic error parameter value and the dynamic operation parameter value is smaller than or equal to the difference threshold value, stopping parameter optimization of the joint dynamic model.
If the parameter differences of all the parameters between the dynamics error parameter value and the dynamics operation parameter value are smaller than or equal to the difference threshold, determining that the optimization of the joint dynamics model converges, wherein the difference threshold can be set according to the requirements, the difference thresholds corresponding to different parameters between the dynamics error parameter value and the dynamics operation parameter value can be different, and in the step, respectively determining the parameter difference s 1 、s 2 、s 3 、s 4 、s 5 Sum s 6 And the magnitude between the corresponding difference threshold value to judge whether to stop the parameter optimization of the joint dynamics model.
And step S70, if the parameter difference value of any parameter between the dynamic error parameter value and the dynamic operation parameter value is larger than a difference threshold value, updating the expected parameter value, and inputting the updated expected parameter value into the joint dynamic model.
Wherein if s 1 、s 2 、s 3 、s 4 、s 5 Sum s 6 If any parameter error is greater than or equal to the corresponding difference threshold, determining that the optimization for the joint dynamics model is not converged, and inputting the updated expected parameter value into the joint dynamics model to enable the joint dynamics model to be continuously optimized in an iteration mode until the optimization convergence for the joint dynamics model is determined.
Optionally, in this embodiment, a desired parameter value list is pre-stored, where a plurality of groups of different desired parameter values are stored, and when the desired parameter value is updated, different desired parameter values are randomly extracted from the desired parameter value list, and the extracted desired parameter value is updated to the current desired parameter value.
And step S80, indicating the joint dynamics model to carry out driving control on the joint according to the updated expected parameter value.
Step S90, obtaining a detection parameter value of the joint under the driving control of the joint dynamics model, and carrying out error operation according to the detection parameter value and the updated expected parameter value to obtain a dynamic iteration parameter.
It will be appreciated that this step is identical to the embodiment of step S20, and the dynamic iteration parameters in this step are used to perform a parametric iterative optimization of each parameter in p within the joint dynamics model until the optimization of the joint dynamics model converges.
And step S100, carrying out parameter iteration on the dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic iteration parameters.
In this embodiment, the parameter differences of different parameters between the dynamics calculation parameter value and the dynamics calculation parameter value are respectively obtained, and the parameter differences of different parameters are compared with the corresponding difference threshold values to determine whether the optimization for the joint dynamics model is converged, so as to improve the accuracy of the joint dynamics model optimization.
Example III
Corresponding to the joint dynamics model optimization method described in the above embodiments, fig. 5 shows a schematic structural diagram of the joint dynamics model optimization system 100 provided in the third embodiment of the present application, and for convenience of explanation, only the portions related to the embodiments of the present application are shown.
Referring to fig. 5, the system includes: a desired parameter value input module 10, an error operation module 11, and a parameter optimization module 12, wherein:
the expected parameter value input module 10 is configured to input an expected parameter value for a joint into a joint dynamics model, and instruct the joint dynamics model to perform driving control on the joint according to the expected parameter value.
Wherein, the dynamics equation in the joint dynamics model is:
τ＝Yp
where τ is the torque loss value,τ o is the output torque of the motor, tau i Is the input torque of the motor, p is the dynamic operation parameter value of the motor and the torque compensation device on the joint in the joint dynamic model, and k c Is the coulomb friction, k, of the joint v Is the coefficient of viscous friction of the joint, c 0 Is the coulomb frictional force fixed offset value of the joint,is the inertia, θ, & gt of the motor>And- >The detected value of the angular position, the detected value of the angular velocity and the detected value of the angular acceleration of the joint, k, are respectively among the detected parameter values p Is the compensation coefficient, theta, of the moment compensation device 0 Is a constant coefficient of the installation angle between the torque compensation device and the motor, and Y is the detection parameter value.
The error operation module 11 is configured to obtain a detection parameter value of the joint under driving control of the joint dynamics model, and perform error operation according to the detection parameter value and the expected parameter value, so as to obtain a dynamics error parameter value.
The calculation formula adopted for performing error operation according to the detection parameter value and the expected parameter value is as follows:
wherein,is the dynamic error parameter value, theta d 、/>And->Respectively, the expected parameter values are for the expected value of the angular position, the expected value of the angular velocity and the expected value of the angular acceleration of the joint, Γ is a preset constant, +.>The method comprises an inertia optimized value, a coulomb friction optimized value, an optimized coefficient of viscous friction, a compensation coefficient optimized value, a coulomb friction fixed bias optimized value and a constant coefficient optimized value.
The parameter optimization module 12 is configured to perform parameter optimization on the dynamic operation parameter values of the motor and the torque compensation device on the joint in the joint dynamic model according to the dynamic error parameter values, where the motor is used to drive the joint to rotate under the driving control of the joint dynamic model, and the torque compensation device is used to perform torque compensation on the motor.
Wherein the parameter optimization module 12 is further configured to: and respectively carrying out parameter updating on inertia of the motor, coulomb friction of the joint, a coefficient of viscous friction of the joint, a compensation coefficient of the moment compensation device and a constant coefficient of an installation angle between the moment compensation device and the motor in the coulomb friction fixed offset value of the joint in the dynamic model of the joint according to the inertia optimized value, the coulomb friction optimized value, the viscous friction optimized coefficient, the compensation coefficient optimized value, the coulomb friction fixed offset optimized value and the constant coefficient optimized value in the dynamic error parameter value of the dynamic error.
Optionally, the joint dynamics model optimization system 100 further includes:
the optimization iteration module 13 is used for respectively acquiring parameter differences of different parameters between the dynamic operation parameter value and the dynamic error parameter value;
if the parameter difference value of any parameter between the dynamics error parameter value and the dynamics operation parameter value is larger than a difference threshold value, updating the expected parameter value, and inputting the updated expected parameter value into the joint dynamics model;
instructing the joint dynamics model to drive and control the joint according to the updated expected parameter value;
Acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and performing error operation according to the detection parameter value and the updated expected parameter value to obtain a dynamic iteration parameter;
and carrying out parameter iteration on dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic iteration parameters.
Optionally, the optimization iteration module 13 is further configured to: and if the parameter difference value of all the parameters between the dynamic error parameter value and the dynamic operation parameter value is smaller than or equal to the difference threshold value, stopping parameter optimization of the joint dynamic model.
In this embodiment, the design of the dynamic error parameter value is obtained by performing error operation according to the detected parameter value and the expected parameter value, so that the control error of the joint dynamic model on the joint can be effectively calculated, and the parameter of the dynamic equation in the joint dynamic model can be effectively updated by performing parameter optimization design on the dynamic operation parameter values of the motor and the torque compensation device on the joint in the joint dynamic model according to the dynamic error parameter value, thereby improving the accuracy of dynamic control of the joint dynamic model and preventing the phenomenon of inaccurate joint dynamic model caused by dynamic parameter setting by artificial experience.
It should be noted that, because the content of information interaction and execution process between the above devices/modules is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.
Fig. 6 is a schematic structural diagram of a terminal device 2 according to a fourth embodiment of the present application. As shown in fig. 6, the terminal device 2 of this embodiment includes: at least one processor 20 (only one processor is shown in fig. 6), a memory 21 and a computer program 22 stored in the memory 21 and executable on the at least one processor 20, the processor 20 implementing the steps in any of the various method embodiments described above when executing the computer program 22.
The terminal device 2 may be a computing device such as a desktop computer, a notebook computer, a palm computer, a cloud server, etc. The terminal device may include, but is not limited to, a processor 20, a memory 21. It will be appreciated by those skilled in the art that fig. 6 is merely an example of the terminal device 2 and is not meant to be limiting as to the terminal device 2, and may include more or fewer components than shown, or may combine certain components, or different components, such as may also include input-output devices, network access devices, etc.
The processor 20 may be a central processing unit (Central Processing Unit, CPU), and the processor 20 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 21 may in some embodiments be an internal storage unit of the terminal device 2, such as a hard disk or a memory of the terminal device 2. The memory 21 may in other embodiments also be an external storage device of the terminal device 2, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 2. Further, the memory 21 may also include both an internal storage unit and an external storage device of the terminal device 2. The memory 21 is used for storing an operating system, application programs, boot loader (BootLoader), data, other programs, etc., such as program codes of the computer program. The memory 21 may also be used for temporarily storing data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
The embodiment of the application also provides a network device, which comprises: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, which when executed by the processor performs the steps of any of the various method embodiments described above.
Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, implements steps that may implement the various method embodiments described above.
Embodiments of the present application provide a computer program product which, when run on a mobile terminal, causes the mobile terminal to perform steps that may be performed in the various method embodiments described above.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application implements all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (RAM, random Access Memory), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (8)
1. A method of joint dynamics model optimization, the method comprising:
inputting expected parameter values for joints into a joint dynamics model, and indicating the joint dynamics model to carry out driving control on the joints according to the expected parameter values;
Acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and performing error operation according to the detection parameter value and the expected parameter value to obtain a dynamics error parameter value;
parameter optimization is carried out on dynamic operation parameter values of a motor and a moment compensation device on the joint in the joint dynamic model according to the dynamic error parameter values, the motor is used for driving the joint to rotate under driving control of the joint dynamic model, and the moment compensation device is used for compensating moment of the motor;
the kinetic equation in the joint kinetic model is as follows:
τ＝Yp
where τ is the torque loss value, τ o Is the output torque of the motor, tau i Is the input torque of the motor, p is the dynamic operation parameter value of the motor and the torque compensation device on the joint in the joint dynamic model, and k c Is the coulomb friction, k, of the joint v Is the coefficient of viscous friction of the joint, c 0 Is the coulomb frictional force fixed offset value of the joint,is the inertia, θ, & gt of the motor>And->The detected value of the angular position, the detected value of the angular velocity and the detected value of the angular acceleration of the joint, k, are respectively among the detected parameter values p Is the compensation coefficient, theta, of the moment compensation device 0 Is a constant coefficient of the installation angle between the torque compensation device and the motor, and Y is the detection parameter value;
the calculation formula adopted for carrying out error operation according to the detection parameter value and the expected parameter value is as follows:
wherein,is the dynamic error parameter value, theta d 、/>And->Respectively, the expected parameter values are for the expected value of the angular position, the expected value of the angular velocity and the expected value of the angular acceleration of the joint, Γ is a preset constant, +.>The method comprises an inertia optimized value, a coulomb friction optimized value, an optimized coefficient of viscous friction, a compensation coefficient optimized value, a coulomb friction fixed bias optimized value and a constant coefficient optimized value.
2. The method for optimizing a dynamic model of a joint according to claim 1, wherein the parameter optimizing the dynamic operation parameter values of the motor and the torque compensation device on the joint in the dynamic model of the joint according to the dynamic error parameter values comprises:
and respectively carrying out parameter updating on inertia of the motor, coulomb friction of the joint, a coefficient of viscous friction of the joint, a compensation coefficient of the moment compensation device and a constant coefficient of an installation angle between the moment compensation device and the motor in the coulomb friction fixed offset value of the joint in the dynamic model of the joint according to the inertia optimized value, the coulomb friction optimized value, the viscous friction optimized coefficient, the compensation coefficient optimized value, the coulomb friction fixed offset optimized value and the constant coefficient optimized value in the dynamic error parameter value of the dynamic error.
3. The method for optimizing a dynamic model of a joint according to claim 1, wherein after the parameter optimization of the dynamic operation parameter values of the motor and the torque compensation device on the joint in the dynamic model of the joint according to the dynamic error parameter values, the method further comprises:
respectively obtaining parameter differences of different parameters between the dynamic operation parameter value and the dynamic error parameter value;
if the parameter difference value of any parameter between the dynamics error parameter value and the dynamics operation parameter value is larger than a difference threshold value, updating the expected parameter value, and inputting the updated expected parameter value into the joint dynamics model;
instructing the joint dynamics model to drive and control the joint according to the updated expected parameter value;
acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and performing error operation according to the detection parameter value and the updated expected parameter value to obtain a dynamic iteration parameter;
and carrying out parameter iteration on dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic iteration parameters.
4. The joint dynamics model optimization method according to claim 3, wherein after the parameter differences of different parameters between the dynamics operation parameter value and the dynamics error parameter value are obtained, further comprising:
and if the parameter difference value of all the parameters between the dynamic error parameter value and the dynamic operation parameter value is smaller than or equal to the difference threshold value, stopping parameter optimization of the joint dynamic model.
5. A joint dynamics model optimization system, comprising:
the system comprises an expected parameter value input module, a joint dynamic model and a control module, wherein the expected parameter value input module is used for inputting an expected parameter value for a joint into the joint dynamic model and indicating the joint dynamic model to carry out driving control on the joint according to the expected parameter value;
the error operation module is used for acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and carrying out error operation according to the detection parameter value and the expected parameter value to obtain a dynamics error parameter value;
the parameter optimization module is used for carrying out parameter optimization on the dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic error parameter values, the motor is used for driving the joint to rotate under the driving control of the joint dynamic model, and the moment compensation equipment is used for carrying out moment compensation on the motor;
The kinetic equation in the joint kinetic model is as follows:
τ＝Yp
where τ is the torque loss value, τ o Is the output torque of the motor, tau i Is the input torque of the motor, p is the dynamic operation parameter value of the motor and the torque compensation device on the joint in the joint dynamic model, and k c Is the coulomb friction, k, of the joint v Is the coefficient of viscous friction of the joint, c 0 Is the coulomb frictional force fixed offset value of the joint,is the inertia, θ, & gt of the motor>And->The detected value of the angular position, the detected value of the angular velocity and the detected value of the angular acceleration of the joint, k, are respectively among the detected parameter values p Is the compensation coefficient, theta, of the moment compensation device 0 Is a constant coefficient of the installation angle between the torque compensation device and the motor, and Y is the detection parameter value;
the calculation formula adopted for carrying out error operation according to the detection parameter value and the expected parameter value is as follows:
wherein,is the dynamic error parameter value, theta d 、/>And->Respectively, the expected parameter values are for the expected value of the angular position, the expected value of the angular velocity and the expected value of the angular acceleration of the joint, Γ is a preset constant, +.>The method comprises an inertia optimized value, a coulomb friction optimized value, an optimized coefficient of viscous friction, a compensation coefficient optimized value, a coulomb friction fixed bias optimized value and a constant coefficient optimized value.
6. The joint dynamics model optimization system of claim 5, further comprising:
the optimization iteration module is used for respectively acquiring parameter differences of different parameters between the dynamic operation parameter value and the dynamic error parameter value;
if the parameter difference value of any parameter between the dynamics error parameter value and the dynamics operation parameter value is larger than a difference threshold value, updating the expected parameter value, and inputting the updated expected parameter value into the joint dynamics model;
instructing the joint dynamics model to drive and control the joint according to the updated expected parameter value;
acquiring a detection parameter value of the joint under the driving control of the joint dynamics model, and performing error operation according to the detection parameter value and the updated expected parameter value to obtain a dynamic iteration parameter;
and carrying out parameter iteration on dynamic operation parameter values of the motor and the moment compensation equipment on the joint in the joint dynamic model according to the dynamic iteration parameters.
7. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1 to 4 when executing the computer program.
8. A storage medium storing a computer program which, when executed by a processor, implements the method of any one of claims 1 to 4.
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| CN109664298A (en) * | 2018-12-26 | 2019-04-23 | 深圳市越疆科技有限公司 | Identification of Dynamic Parameters of Amanipulator method, apparatus, terminal device and storage medium |
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