CN115157271B - Mechanical arm control method and device, control terminal and storage medium - Google Patents
Mechanical arm control method and device, control terminal and storage medium Download PDFInfo
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- CN115157271B CN115157271B CN202211076076.3A CN202211076076A CN115157271B CN 115157271 B CN115157271 B CN 115157271B CN 202211076076 A CN202211076076 A CN 202211076076A CN 115157271 B CN115157271 B CN 115157271B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
Abstract
The embodiment of the invention discloses a mechanical arm control method, a device, a control terminal and a storage medium, wherein the method comprises the following steps: acquiring current state parameters of the mechanical arm; according to a preset mechanical arm output model, acquiring mechanical arm output force at the current moment according to a preset motion track and the state parameters, wherein the mechanical arm output model is constructed according to a sliding mode variable structure and a mechanical arm power model; and controlling the mechanical arm to move according to the motion trail according to the output force. The mechanical arm controls the motion of the mechanical arm at every moment according to the model parameters, and the shake can be recovered quickly, so that the control process of the whole mechanical arm is safer, and the calculation is reduced.
Description
Technical Field
The invention relates to the field of robot control, in particular to a mechanical arm control method, a mechanical arm control device, a mechanical arm control terminal and a storage medium.
Background
In the experimental process of the surgical robot, the mechanical arm is controlled through a traditional control theory, the problems of slow response, large jitter, more parameter adjustment and the like are caused by external interference, when the mechanical arm moves according to a preset track and a target posture, the jitter and errors are often generated, and when the movement time of the mechanical arm is longer, the errors are larger and larger, so that the mechanical arm must be calibrated, the steps of calculation and adjustment are increased, and the calculation power is occupied.
Disclosure of Invention
In a first aspect, the present application provides a robot arm control method, including:
acquiring current state parameters of the mechanical arm;
acquiring the output force of the mechanical arm at the current moment according to a preset mechanical arm output model and a preset motion track and the state parameters, wherein the mechanical arm output model is constructed according to a sliding mode variable structure and a mechanical arm power model;
and controlling the mechanical arm to move according to the motion trail according to the output force.
Further, the method also comprises the following steps:
when the mechanical arm shakes in the motion process, the output force is adjusted according to the mechanical arm output model, so that the motion posture of the mechanical arm is recovered to be stable.
Further, the method for acquiring the mechanical arm output model comprises the following steps:
establishing a feedback parameter model according to the mechanical arm power model and the Lyapunov equation, wherein the feedback parameter model is used for eliminating an interference item in the Lyapunov equation;
and establishing the mechanical arm output model according to the feedback parameter model and the second-order parameters of the sliding mode variable structure.
Further, the expression of the mechanical arm output model is as follows:
wherein u is the output force of the mechanical arm, F and K are preset coefficients, e is the deviation value of the actual position and the target position of the mechanical arm joint,
is the deviation value of the actual angular velocity and the target angular velocity of the mechanical arm joint,
is the gravity term and f is the feedback parameter.
Further, establishing a feedback parameter model according to the mechanical arm power model and the lyapunov equation comprises:
and constructing a Lyapunov equation, calculating the differential of the Lyapunov equation, and establishing the corresponding feedback parameter model according to the differential of the Lyapunov equation.
Wherein the expression of the Lyapunov equation is as follows:
wherein V is the Lyapunov equation,
is the inertia matrix of the robot arm.
Further, establishing the corresponding feedback parameter model according to the differential of the lyapunov equation includes:
establishing the feedback parameter model according to the Coriolis force and an inertia matrix of the mechanical arm;
the feedback parameter model expression is as follows:
in the formula (I), the compound is shown in the specification,
is the inertial matrix of the robotic arm,
is a matrix of coriolis force and centripetal force couplings,
is the angle of the joint, and is,
is the angular velocity of the joint or joints,
is the target acceleration of the mechanical arm joint, t is time, and f is the feedback parameter.
Further, the expression of the mechanical arm power model is as follows:
in the formula (I), the compound is shown in the specification,
is the inertia matrix of the mechanical arm, d is the disturbance quantity,
is the angle of the joint, and is,
is the angular velocity of the joint or joints,
is the angular acceleration of the joint,
is a matrix of coriolis forces and centripetal coupling.
In a second aspect, the present application also provides a robot arm control apparatus, including:
the monitoring module is used for acquiring the current state parameters of the mechanical arm;
the construction module is used for acquiring the mechanical arm output force at the current moment according to a preset mechanical arm output force model and a preset motion track and the state parameters, and the mechanical arm output force model is constructed according to a sliding mode variable structure and a mechanical arm power model;
and the control module is used for controlling the mechanical arm to move according to the motion trail according to the output force.
In a third aspect, the present application further provides a control terminal, including a processor and a memory, where the memory stores a computer program, and the computer program executes the robot arm control method when running on the processor.
In a fourth aspect, the present application further provides a readable storage medium storing a computer program which, when run on a processor, executes the robot arm control method.
The embodiment of the invention discloses a mechanical arm control method, a device, a control terminal and a storage medium, wherein the method comprises the following steps: acquiring current state parameters of the mechanical arm; according to a preset mechanical arm output model, acquiring mechanical arm output force at the current moment according to a preset motion track and the state parameters, wherein the mechanical arm output model is constructed according to a sliding mode variable structure and a mechanical arm power model; and controlling the mechanical arm to move according to the motion trail according to the output force. The mechanical arm can control the motion of the mechanical arm at every moment according to the model parameters, and the shake can be quickly recovered to be stable, so that the control process of the whole mechanical arm is safer, the calculation is reduced, the occupation of calculation resources is reduced, and the load of a control terminal is lightened.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings required in the embodiments will be briefly described below, and it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of the present invention. Like components are numbered similarly in the various figures.
Fig. 1 shows a schematic flow chart of a method for controlling a robot according to an embodiment of the present disclosure;
FIG. 2 is a graph showing a simulation graph of angular velocity of a robot arm according to an embodiment of the present application;
FIG. 3 shows an enlarged view of a simulation of angular velocity of a robot arm according to an embodiment of the present application;
FIG. 4 shows an enlarged view of a simulation of angular velocity of a further robot arm according to an embodiment of the present application;
fig. 5 shows a schematic structural diagram of a robot arm control device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Hereinafter, the terms "including", "having", and their derivatives, which may be used in various embodiments of the present invention, are only intended to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing, and should not be construed as first excluding the existence of, or adding to, one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the present invention belong. The terms (such as terms defined in a commonly used dictionary) will be construed to have the same meaning as the contextual meaning in the related art and will not be construed to have an idealized or overly formal meaning unless expressly so defined in various embodiments of the present invention.
The technical scheme of this application is applied to the control of arm, through carrying out the settlement of target gesture to the arm, thereby can calculate the theoretical orbit that obtains the arm from current gesture to target gesture, for making in the control process, there is self-adaptation ability in the face of the disturbance of system, through according to the robot dynamics equation, establish arm power model and feedback parameter model, and then obtain the power that actual arm needs to be exported, thereby control that the arm is stable along predetermineeing the orbit motion.
Example 1
As shown in fig. 1, the robot arm control method of the present application includes the steps of:
and step S100, acquiring current state parameters of the mechanical arm.
After the motion trail is obtained, the motion of the mechanical arm is controlled by the force output by the motor in each joint of the mechanical arm so that the mechanical arm moves according to the motion trail to reach the target posture.
The mechanical arm can be a multi-axis mechanical arm such as a two-axis mechanical arm, a three-axis mechanical arm or a four-axis mechanical arm, and can be an operation mechanical arm for an operation.
Therefore, a power model of the mechanical arm is established according to a robot dynamic equation, and the control of the mechanical arm is realized by controlling the output force of the mechanical arm (namely, the force output by the joint motor) through establishing the relation between the mechanical arm power and the mechanical arm posture.
Wherein, the mechanical arm power model expression is as follows:
in the formula (I), the compound is shown in the specification,
is the inertia matrix of the mechanical arm, d is the disturbance quantity,
is the angle of the joint, and is,
is the angular velocity of the joint or joints,
is the angular acceleration of the joint(s),
is a matrix of coriolis forces and centripetal coupling,
is a gravity term, and u is the output force of the mechanical arm.
According to the mechanical arm power model, the joint angle, the joint angular velocity and the joint angular acceleration are the current motion states of the mechanical arm and are known quantities, the gravity acceleration is constant, so the gravity term is also known quantity, other terms except u and d in all the terms are known quantities, the disturbance quantity d is small and can be ignored, and the motion track of the mechanical arm can be controlled to a certain extent by controlling the output force of the mechanical arm.
And S200, acquiring the mechanical arm output force at the current moment according to a preset mechanical arm output force model and the set motion track and the state parameters, wherein the mechanical arm output force model is constructed according to a sliding mode variable structure and a mechanical arm power model.
Before the mechanical arm starts to move, the motion track of the mechanical arm needs to be planned, for example, the current mechanical arm is at the origin, and the control tail end of the mechanical arm needs to advance for a certain distance to reach a target location, so that target parameters of the mechanical arm, such as the angle of each axis at the target location and the posture of each connecting rod of the mechanical arm, can be set according to the target location. Meanwhile, in order to plan a path, current state parameters of the mechanical arm, such as a current position coordinate of the tail end of the mechanical arm, angles of all axes and the like, are also acquired.
After the state parameters and the target parameters are known, the motion trajectory of the mechanical arm can be planned according to a routing algorithm, and the method for obtaining the motion trajectory can be a method of one line of two points or a nearest point searching method, and the like, which is not limited in the present application.
It can be understood that, in order to enable the mechanical arm to move stably and safely, a model needs to be established for the output force of the mechanical arm so as to calculate a proper theoretical output force, and when the mechanical arm moves according to the force, the track of the whole mechanical arm can be fit with the theoretical track. In addition, the motor is in a new state after moving, so that the control can be performed in a stepping mode, and therefore, according to a fixed sampling period, the force required to be output by the current mechanical arm is acquired periodically to control the movement of the mechanical arm as accurately as possible, the sampling period can be set according to the requirement and the performance of the machine, such as 3 milliseconds or 4 milliseconds, and the sampling period can be selected from 1-5 milliseconds.
Therefore, the mechanical arm output model is constructed according to the sliding mode variable structure and the mechanical arm power model. The sliding mode variable structure is a control strategy and is used for tracking and controlling three motion parameters of an angle, an angular velocity and an angular acceleration of the mechanical arm so as to realize three-order system control of the mechanical arm.
The mechanical arm output model expression is as follows:
wherein u is the output force of the mechanical arm, F and K are corresponding coefficients, e is the deviation value of the actual position and the target position of the mechanical arm joint,
and f is the deviation value of the actual angular velocity and the target angular velocity of the mechanical arm joint, and f is the feedback parameter.
From the above formula, except F, other items are also known, F and K can be preset through tool parameters such as specific mechanical arm models, and e and K
Can be obtained by automatically calculating the planned path and the current gesture of the mechanical arm, reflects the goodness of fit between the current gesture of the mechanical arm and the planned track, so e and
can be regarded as two slide film lines which respectively reflect whether the current angle and speed of the mechanical arm are consistent with the preset ideal numerical value.
The gravity term is also a value which can be obtained by calculation through the current posture of the mechanical arm, so that a proper output force can be output by setting a proper feedback parameter f.
In order to output a proper output force, a proper feedback parameter model needs to be established, and the accuracy of the whole mechanical arm system is ensured by establishing the feedback parameter model, so that a lyapunov equation can be established based on the mechanical arm power model, and the feedback parameter model is established according to the lyapunov equation.
Therefore, the Lyapunov equation can be designed
Differentiating this equation is:
According to the properties of Lyapunov equation
Can ensure that
The system is progressively stable.
By establishing a proper feedback parameter model, unstable factors in the whole system, such as errors caused by friction force, system errors, inertia and the like, are reduced, so that the established feedback parameter model is the following expression:
in the formula (I), the compound is shown in the specification,
is an inertia matrix of the robot arm
Is the coriolis force and centripetal coupling matrix and t is time.
The following formula can be obtained according to the feedback parameter model and the Lyapunov equation:
due to the fact that
Is an oblique symmetric matrix, the result is a 0 matrix, and the following formula is obtained after arrangement:
d is a very small disturbance quantity and can be ignored.
Then, according to the nature of the lyapunov equation, there is a difference between,
，
the system can be determined to be gradually stable, that is, the current mechanical arm can be in a stable state by setting appropriate parameters, so that the actual motion track of the mechanical arm is matched with the ideal track as much as possible.
And step S300, controlling the mechanical arm to move according to the motion trail according to the output force.
The feedback parameter model and the mechanical arm output model in the steps are combined to obtain an expression
. The formula is a final mechanical arm output model, and when the mechanical arm actually works, the force which should be output by a motor of the mechanical arm can be obtained through the expression after the motion trail is obtained by setting target parameters and obtaining current state parameters of the mechanical arm.
In addition, because the expression is steady-state according to the Lyapunov equation, when disturbance occurs in the working process of the mechanical arm, the expression can be used for continuing control, and the disturbance can be quickly eliminated due to the stability of the system.
For convenience of explanation, taking a two-axis robot as an example, the lengths of two connecting rods of the two-axis robot are respectively set as
，
The mass of the two connecting rods is respectively
，
Ideal angle signals of two joints
，
And the initial vector of the system is zero, so as to carry out simulation experiment.
The simulation experiment can be performed on MATLAB, and fig. 2 is a simulation experiment diagram performed with the above initial quantities, where a curve 100 is a coincidence curve of a real-time angular velocity curve and an ideal angular velocity curve of a first axis of the two-axis robot arm, and a curve 200 is a coincidence curve of a real-time angular velocity curve and an ideal angular velocity curve of a second axis of the two-axis robot arm, and because an actual trajectory and a target trajectory are attached, the two curves may overlap.
An enlarged view of the circled portion 210 is shown in fig. 3.
As shown in fig. 3, the vibration generated during the motion of the mechanical arm is generated from the curve 200, that is, during the motion, an error occurs, so that the mechanical arm link has a shift, so that the curve 200 and the ideal angular velocity curve 300 do not coincide, and the ideal angular velocity is re-estimated and calculated due to the movement of the mechanical arm position, so that the curve 300 is also re-calculated according to the current shifted pose and is not continuous with the original trajectory, so that it can be seen from fig. 3 that a short gap exists between the curve 300 and the curve 200, and then the two curves coincide again, thereby representing the stability of the whole system.
Figure 4 is an enlarged view of the portion 220 of figure 2, showing a graph of the beginning of the robot motion, wherein initially there is a significant difference, small and equal trend, between the curves 200 and 300, and they soon coincide with each other, showing that the robot can quickly enter a steady state operation as soon as it begins to operate. All adjustments are calculated only through the model, and correction is not needed through other modes when shaking occurs.
According to the mechanical arm control method, a mechanical arm power model is established according to a robot dynamics equation by setting target parameters of the mechanical arm according to a target posture; according to the mechanical arm power model, establishing a mechanical arm output model; establishing a feedback parameter model according to the mechanical arm power model, and acquiring the output force of the mechanical arm according to the target parameter and the feedback parameter model; and controlling the mechanical arm to move according to the target parameters according to the output force and the mechanical arm output force model. The mechanical arm can control the motion of the mechanical arm at every moment according to the model parameters, and the shake can be quickly recovered to be stable, so that the control process of the whole mechanical arm is safer, the calculation is reduced, the occupation of calculation resources is reduced, and the load of a control terminal is lightened.
Example 2
The present application also provides a robot arm control apparatus, as shown in fig. 5, including:
the monitoring module 10 is used for acquiring current state parameters of the mechanical arm;
the building module 20 is configured to obtain the output force of the mechanical arm at the current moment according to a preset mechanical arm output model and a preset motion trajectory and the state parameters, wherein the mechanical arm output model is built according to a sliding mode variable structure and a mechanical arm power model;
and the control module 30 is used for controlling the mechanical arm to move according to the motion trail according to the output force.
The application also provides a control terminal, which comprises a processor and a memory, wherein the memory stores a computer program, and the computer program executes the mechanical arm control method when running on the processor.
The present application also provides a readable storage medium storing a computer program which, when run on a processor, executes the robot arm control method.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, each functional module or unit in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions may be stored in a computer-readable storage medium if they are implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the present invention or a part thereof which contributes to the prior art in essence can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a smart phone, a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk, and various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention.
Claims (8)
1. A robot arm control method is characterized by comprising:
acquiring current state parameters of the mechanical arm;
according to a preset mechanical arm output model, acquiring mechanical arm output force at the current moment according to a preset motion track and the state parameters, wherein the mechanical arm output model is constructed according to a sliding mode variable structure and a mechanical arm power model;
controlling the mechanical arm to move according to the motion trail according to the output force;
the method for acquiring the mechanical arm output model comprises the following steps:
establishing a feedback parameter model according to the mechanical arm power model and the Lyapunov equation, wherein the feedback parameter model is used for eliminating an interference item in the Lyapunov equation;
establishing the mechanical arm output model according to the feedback parameter model and the second-order parameters of the sliding mode variable structure;
the expression of the mechanical arm output model is as follows:
wherein u is the output force of the mechanical arm, F and K are preset coefficients, e is the deviation value of the actual position and the target position of the mechanical arm joint,
is the deviation value of the actual angular velocity and the target angular velocity of the mechanical arm joint,
is the gravity term and f is the feedback parameter.
2. The robot arm control method according to claim 1, further comprising:
when the mechanical arm shakes in the motion process, the output force is adjusted according to the mechanical arm output model, so that the motion posture of the mechanical arm is recovered to be stable.
3. The robot arm control method according to claim 1, wherein building a feedback parameter model based on the robot arm dynamic model and the lyapunov equation comprises:
constructing a Lyapunov equation, calculating the differential of the Lyapunov equation, and establishing a corresponding feedback parameter model according to the differential of the Lyapunov equation;
wherein the expression of the Lyapunov equation is as follows:
wherein V is the Lyapunov equation,
is the inertia matrix of the robot arm.
4. The robot arm control method according to claim 3, wherein establishing the corresponding feedback parameter model according to the differential of the Lyapunov equation comprises:
establishing the feedback parameter model according to the Coriolis force and an inertia matrix of the mechanical arm;
the feedback parameter model expression is as follows:
in the formula (I), the compound is shown in the specification,
is the inertial matrix of the robotic arm,
is a matrix of coriolis force and centripetal force couplings,
is the angle of the joint, and is,
is the angular velocity of the joint or joints,
is the target acceleration of the mechanical arm joint, t is time, and f is the feedback parameter.
5. The robot arm control method according to claim 1, wherein the expression of the robot arm power model is:
in the formula (I), the compound is shown in the specification,
is the inertia matrix of the mechanical arm, d is the disturbance quantity,
is the angle of the joint, and is,
is the angle of the jointThe speed of the motor is controlled by the speed of the motor,
is the angular acceleration of the joint,
is the coriolis force and centripetal coupling matrix.
6. A robot arm control apparatus, comprising:
the monitoring module is used for acquiring the current state parameters of the mechanical arm;
the construction module is used for acquiring the mechanical arm output force at the current moment according to a preset mechanical arm output force model and a preset motion track and the state parameters, and the mechanical arm output force model is constructed according to a sliding mode variable structure and a mechanical arm power model; the method for acquiring the mechanical arm output model comprises the following steps:
establishing a feedback parameter model according to the mechanical arm power model and the Lyapunov equation, wherein the feedback parameter model is used for eliminating an interference item in the Lyapunov equation;
according to the feedback parameter model and the second-order parameters of the sliding mode variable structure, establishing a mechanical arm output model;
the expression of the mechanical arm output model is as follows:
wherein u is the output force of the mechanical arm, F and K are preset coefficients, e is the deviation value of the actual position and the target position of the mechanical arm joint,
is the deviation value of the actual angular velocity and the target angular velocity of the mechanical arm joint,
is a gravity term, f is the feedback parameter;
and the control module is used for controlling the mechanical arm to move according to the motion track according to the output force.
7. A control terminal, characterized in comprising a processor and a memory, said memory storing a computer program which, when run on said processor, performs the robot arm control method of any of claims 1 to 5.
8. A readable storage medium, characterized in that it stores a computer program which, when run on a processor, performs the robot arm control method of any one of claims 1 to 5.
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