CN112171673B - Robot arm operation control method, control apparatus, and computer-readable storage medium - Google Patents
Robot arm operation control method, control apparatus, and computer-readable storage medium Download PDFInfo
- Publication number
- CN112171673B CN112171673B CN202011017129.5A CN202011017129A CN112171673B CN 112171673 B CN112171673 B CN 112171673B CN 202011017129 A CN202011017129 A CN 202011017129A CN 112171673 B CN112171673 B CN 112171673B
- Authority
- CN
- China
- Prior art keywords
- information
- joint
- pose
- target
- obtaining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- 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
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
Abstract
The invention discloses a mechanical arm operation control method, control equipment and a computer readable storage medium, wherein the mechanical arm operation control method comprises the following steps: acquiring initial joint position information and current arm shape information; obtaining current pose information of the target joint according to the initial joint position information and the current arm shape information; acquiring preset terminal pose information, and obtaining a Cartesian path according to the initial joint position information and the preset terminal pose information; obtaining preset terminal sub-path position information according to the Cartesian path; obtaining pose error information according to preset terminal sub-path position information and terminal current pose information; performing gradient projection processing and redundant decomposition according to the pose error information and obtaining joint increment information; and adjusting the pose of the target joint according to the current pose information and the joint increment information of the target joint. The mechanical arm operation control method adjusts the position of the target joint according to the joint increment information so that the pose of the mechanical arm is the target pose.
Description
Technical Field
The present invention relates to the field of machine control technologies, and in particular, to a method and a device for controlling a robot arm, and a computer-readable storage medium.
Background
At present, in the building decoration project, the working quality of an indoor autonomous wall plastering link determines the practicability and the attractiveness of a house. The autonomous robot can replace manpower to perform complex wall surface operation through station setting and conversion.
However, in the related art, the main component of the autonomous robot is a serial mechanical arm with several degrees of freedom, and there is a serious deficiency in operational flexibility.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a manipulator operation control method which can adjust the pose of the target joint according to joint increment information so that the pose of the manipulator is the target pose.
According to a robot arm operation control method according to an embodiment of a first aspect of the present invention, a robot arm provided with an initial joint and at least one target joint, an end of the robot arm being provided with an end effector, includes: acquiring initial joint position information and current arm shape information; obtaining current pose information of a target joint according to the initial joint position information and the current arm shape information; acquiring preset terminal pose information, and obtaining a Cartesian path according to the initial joint position information and the preset terminal pose information; obtaining preset terminal sub-path position information according to the Cartesian path; obtaining pose error information according to the preset tail end sub-path position information and the tail end current pose information; performing gradient projection processing and redundant decomposition according to the pose error information and obtaining joint increment information; and adjusting the pose of the target joint according to the current pose information and the joint increment information of the target joint.
The mechanical arm operation control method provided by the embodiment of the invention at least has the following beneficial effects: and obtaining pose error information according to the preset terminal pose information and the current terminal pose information, performing gradient projection and redundant decomposition on the pose error information to calculate joint increment, and adjusting the position of the target joint according to the joint increment information to enable the pose of the mechanical arm to be the target pose. The operation of the mechanical arm is completed by adjusting the pose of the target joint in the mechanical arm, and the redundancy and pose error information of the mechanical arm are decomposed by redundancy decomposition, so that the flexibility of the mechanical arm in the operation process of the mechanical arm is improved.
According to some embodiments of the invention, comprising: acquiring terminal speed information according to the preset terminal pose information, and acquiring target joint speed information according to the current pose information of the target joint; obtaining a target joint velocity information general solution according to the terminal velocity information, the target joint velocity information and the Jacobian matrix; and adjusting the pose of the target joint according to the current pose information, the joint increment information and the target joint speed information.
According to some embodiments of the invention, comprising: and the preset weight matrix is an identity matrix, and the target joint velocity information general solution is obtained according to the wide inverse matrix, the vector information and the terminal velocity information of the Jacobian matrix.
According to some embodiments of the invention, the gradient projection processing further comprises: obtaining the vector information according to the free vector and the scalar coefficient; adjusting the pose of the target joint according to the vector information; and the free vector is the gradient of the performance coefficient of the mechanical arm.
According to some embodiments of the invention, the coefficient of performance is minimized according to the gradient and a corresponding magnification factor is selected according to the type of the mechanical arm; and obtaining the free vector according to the amplification factor and the adjustable range of the target joint.
According to some embodiments of the invention, further comprising: discretizing and track interpolation processing are carried out on the Cartesian paths to generate a plurality of Cartesian sub-paths; obtaining the pose error information according to the difference value of the starting point and the end point of the Cartesian sub-path; obtaining the joint increment information according to the pose error information; and iterating according to the joint increment information to obtain joint increment information of adjacent joints.
According to some embodiments of the invention, further comprising: adjusting the relation between the tail end contact force and the tail end position of the mechanical arm according to the impedance characteristic of the mechanical arm; obtaining a first target impedance model according to the relation between the tail end contact force and the tail end position of the mechanical arm; adjusting an output power of the end effector according to the first target impedance model.
According to some embodiments of the invention, further comprising: obtaining a contact force deviation value according to the contact force of the target tail end and the actual contact force; obtaining a second target impedance model according to the first target impedance model and the contact force deviation value; adjusting the output power of the end effector according to the second target impedance model.
According to some embodiments of the invention, further comprising: adjusting the tail end contact force and the tail end position of the mechanical arm according to the pose error information and a second target impedance model; or adjusting the tail end contact force and the tail end position of the mechanical arm according to the contact force deviation value and a second target impedance model.
According to some embodiments of the invention, further comprising: the end executor is internally provided with an end motor; obtaining an output torque of the impedance system according to the expected system stiffness, the angle difference, the expected system damping and the speed difference; and obtaining a moment error according to the output moment and the actual moment of the impedance system.
A robot arm control apparatus according to an embodiment of the second aspect of the present invention includes: at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions that are executed by the at least one processor, so that the at least one processor implements the robot operation control method in any of the embodiments described above when executing the instructions.
A computer-readable storage medium according to a third aspect of the present invention is characterized in that the computer-readable storage medium stores computer-executable instructions for causing a computer to execute the robot arm work control method according to any one of the above embodiments.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart illustrating a method for controlling operation of a robot according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for controlling operation of a robot according to another embodiment of the present invention;
FIG. 3 is a flow chart illustrating a method for controlling operation of a robotic arm according to one embodiment of the present invention;
fig. 4 is a schematic diagram illustrating an impedance control process of an output device according to an embodiment of the invention.
Detailed Description
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
Referring to fig. 1, a robot arm operation control method, a robot arm having an initial joint and at least one target joint, and an end effector provided at an end of the robot arm, includes: s100, acquiring initial joint position information and current arm shape information; s200, obtaining current pose information of a target joint according to the initial joint position information and the current arm shape information; s300, acquiring preset terminal pose information, and obtaining a Cartesian path according to the initial joint position information and the preset terminal pose information; s400, obtaining preset terminal sub-path position information according to the Cartesian path; s500, obtaining pose error information according to preset terminal sub-path position information and terminal current pose information; s600, performing gradient projection processing and redundant decomposition according to the pose error information and obtaining joint increment information; and S700, adjusting the pose of the target joint according to the current pose information and the joint increment information of the target joint.
Obtaining current pose information of a target joint of the mechanical arm according to the current arm shape information and the initial joint position information of the mechanical arm so as to determine the current pose of the target joint; and acquiring preset terminal sub-path position information according to the Cartesian path and the target joint in the mechanical arm.
In addition, pose error information is obtained according to preset terminal sub-path position information and terminal current pose information, gradient projection processing and redundant decomposition are further carried out on the pose error information to obtain joint increment information, and the pose of the target joint is adjusted according to the joint increment information. The arm shape of the mechanical arm is adjusted by adjusting the pose of the target joint to a preset pose, thereby adjusting the execution position of the end effector.
In some embodiments, multiple joints are provided in the robotic arm to construct a six degree of freedom serial robotic arm, and a painting device or a spray device is provided at the end of the robotic arm.
In some embodiments, the corresponding joint increment information is generated by performing a gradient projection and redundant decomposition on the pose error information to calculate joint increments. The pose error information is subjected to gradient projection to solve the pose nonlinear programming of the mechanical arm, so that the optimal solution of the nonlinear path programming is obtained. The redundancy of the mechanical arm is decomposed through redundancy decomposition so as to avoid pose difference caused by joint pose limit under the condition that the pose of a smearing device or a spraying device at the tail end of the mechanical arm is guaranteed to be a preset pose, and therefore secondary optimization is conducted on the optimal solution of the nonlinear path planning of the pose of the mechanical arm. For example, by combining gradient projection and redundant decomposition to solve an optimal solution for a nonlinear programming of a machine, and adjusting a path of the mechanical arm according to the optimal solution, the pose of a painting device or a spraying device at the end of the mechanical arm is adjusted to a preset pose.
In some embodiments, the target joint is positionally adjusted according to the joint increment information to bring the robot arm pose to the target pose. For example, the mechanical arm comprises a plurality of joints, joint increment information is iterated according to the position relation between adjacent joints to obtain joint increments corresponding to a plurality of target joints, and the pose of the corresponding target joint is adjusted according to the corresponding joint increments, so that the pose of the mechanical arm is dynamically adjusted, and the dynamic operation of the mechanical arm is completed.
For example, the pose of the mechanical arm is adjusted to enable the mechanical arm to complete a series of plastering actions, so that wall plastering operation is performed on a wall through the mechanical arm. The wall body is plastered through the mechanical arm, the traditional manual operation can be replaced, and the labor cost is reduced. And the mechanical arm can adapt to different environments, such as a low oxygen environment, by carrying out automatic operation in a background.
Wherein initial joint position information theta is acquiredinitialDetected current arm type information and based on initial joint position information thetainitialObtaining the current pose information X of the target joint from the current arm type informationjoint(ii) a Acquiring preset terminal pose information XfinalAnd obtaining a Cartesian path; discretizing the cartesian paths to generate a plurality of cartesian sub-paths; selecting a corresponding target joint according to the Cartesian subpath and obtaining preset terminal subpath pose information Xref＝f(Xinitial,Xfinal) (ii) a According to the current terminal pose information X of the mechanical armcur＝f(θcur,DL) Presetting terminal sub-path pose information Xref＝f(Xinitial,Xfinal) Obtaining pose error information delta X (delta X ═ X)ref-Xcur) (ii) a Gradient projection processing and redundant decomposition are carried out on the pose error information delta X, and joint increment information is obtained; and adjusting the pose of the target joint according to the current pose information and the joint increment information of the target joint.
In some embodiments, at least a first joint, a second joint, and a third joint are provided in the robotic arm. The first joint is used as an initial joint, and the second joint is used as a target joint, so that the pose of the second joint is adjusted; the second joint is used as an initial joint, and the third joint is used as a target joint, so that the pose of the third joint is adjusted, and the pose of the whole mechanical arm is adjusted. The pose of the joint in the mechanical arm is adjusted in an iterative manner step by step, so that the mechanical arm can complete multi-degree-of-freedom adjustment, and complex wall plastering operation can be completed.
Referring to fig. 1 and 2 together, in some embodiments, a robot operation control method includes: s701, the processor obtains end speed information according to preset end pose information and obtains target joint speed information according to current pose information of a target joint; s702, the processor obtains a general solution of the target joint velocity information according to the terminal velocity information, the target joint velocity information and the Jacobian matrix; and S703, the controller adjusts the pose of the target joint according to the current pose information, the joint increment information and the target joint speed information.
In the operation process of the mechanical arm, each joint is in a motion state, terminal speed information is obtained according to the current terminal pose information, joint speed information is obtained according to the initial joint position information, and therefore the joint speed of the mechanical arm is dynamically analyzed, and dynamic adjustment is achieved. In addition, the operation state or the pose of the mechanical arm is adjusted through joint speed information, so that the mechanical arm has excellent continuity in work.
For example, the kinematic velocity equation of the mechanical arm is
Wherein the content of the first and second substances,
the speed of an actuating mechanism on a tail end joint of the mechanical arm;
the joint speed of the mechanical arm; j is an element of Rm×nIs the Jacobian matrix of the mechanical arm.
Based on the gradient projection method, the general solution of the formula (1-1) is
Wherein W ∈ Rm×nIs a weight matrix.
In some embodiments, a robotic arm operation control method comprises: the preset weight matrix is an identity matrix, and a target joint velocity information general solution is obtained according to the wide inverse matrix, the vector information and the terminal velocity information of the Jacobian matrix.
By adjusting the value of the weight matrix, the speed of an actuator on the end joint of the mechanical arm is adjusted
Thereby obtaining a general solution of joint velocity information.
For example, when W ═ I is taken, formula (1-1) becomes
Wherein, J+＝JT(JJT)-1A generalized inverse matrix, also called pseudo-inverse matrix, which is J; i is as large as Rn×nIs an identity matrix;
is arbitrary vector information.
In some embodiments, the robotic arm operation control method, the gradient projection process, comprises: obtaining vector information according to the free vector and the scalar coefficient; and performing gradient projection on joint increment according to the vector information. The free vector is the gradient of the coefficient of performance of the mechanical arm. The position of the target joint is adjusted by combining the mechanical arm performance coefficient of the mechanical arm, so that the actual working performance of the mechanical arm is optimized.
The free vector is obtained by solving the gradient of the performance coefficient of the mechanical arm, and vector information is obtained according to the free vector and the scalar coefficient.
For example,
formula (1-3)
As the velocity of the end point, is,
is composed of
By (I-J)+J) Any vector is projected into the null space of J, thereby defining joint space self-motion that does not affect tip motion. The gradient projection method carries out kinematic optimization by adjusting the self-motion of the mechanical arm in the joint space.
By free vector
Arbitrary vector information composed of scalar coefficients K called "amplification factors
In the formula (I), the compound is shown in the specification,
is the gradient of the performance function H (theta).
By solving for
In order to minimize H (theta) at a high level by the homogeneous solution of the formula (1-3) while ensuring that the end motion is not affected, thereby avoiding the limitation of joints due to the small stroke of the micro-robot arm driver, and setting the performance function H (theta) to
In the formula (1-5), αi＝[θimax+θimin]The median value of the allowable range for each joint is represented by/2, and the joint range is optimized so that H (θ) is the minimum value.
In some embodiments, the robot arm operation control method further comprises: enabling the performance coefficient to be the minimum value according to the gradient, and selecting a corresponding amplification coefficient K according to the type of the mechanical arm; and obtaining a free vector according to the amplification factor K and the adjustable range of the target joint.
The gradient is used for enabling the performance coefficient to be the minimum value, and the amplification coefficient is correspondingly adjusted to adjust any vector information, so that the optimal solution of pose adjustment of the mechanical arm is achieved.
Selecting different amplification factors K and free vectors according to the adjustment range of the mechanical arm joint
Is expressed as
The problem that the motion range of the micro-robot is limited when the macro-micro robot moves in a planning mode, so that the overall motion cannot be met can be solved through the formula (1-6). Wherein the amplification factor is set to K [ -5 × 10 [ ]-2I3×3]
In addition, in order to realize that the macro mechanical arm is responsible for large-scale space movement and the micro mechanical arm is responsible for posture adjustment, the weight matrix W in the formula (1-2) is set as follows:
in some embodiments, the robot arm operation control method further comprises: s401, discretizing and track interpolation processing is carried out on the Cartesian paths to generate a plurality of Cartesian sub-paths and obtain position information of the preset terminal sub-paths; s402, obtaining pose error information according to preset terminal sub-path position information and terminal current pose information; and S403, obtaining joint increment information according to the pose error information, and iterating the joint increment information to obtain joint increment information of adjacent joints.
The Cartesian path is discretized into a series of intermediate points and subjected to trajectory interpolation. By setting the movement time T and the sampling period T of the mechanical arm, the Cartesian path is equally divided into sections k and T/T.
Wherein, the end point of the Nth segment is the end point of the (N + 1) th segment, the interval between the adjacent path points is very small, the motion of the robot on each small segment of the path can be similar to the uniform motion with the speed delta theta, and the motion can be obtained by the formula (1-1),
ΔX＝JΔθ (1-8)
in the formula, Δ X is attitude error between adjacent path points; and delta theta is the robot joint increment corresponding to the adjacent path points.
In the formula, Kp is a PID coefficient matrix,
the poses of the tail end of the mechanical arm at the starting point and the ending point of each path in the space are Xc and Xd respectively, and the corresponding position of the robot joint is thetacAnd thetadThen there is
θd＝θc+TΔθ (1-10)
In some embodiments, the robot arm operation control method further comprises: adjusting the relation between the tail end contact force and the tail end position of the mechanical arm according to the impedance characteristic of the mechanical arm; and setting a first target impedance model according to the relation between the tail end contact force and the tail end position of the mechanical arm.
Wherein the ratio of the contact force between the robot arm and the environment to the position is defined as the mechanical impedance of the robot arm. According to the impedance characteristic of the mechanical arm, the relation between the tail end contact force and the tail end position of the mechanical arm is adjusted, so that accurate tail end force/position following control of the mechanical arm is achieved. And setting a first target impedance model according to the relation between the tail end contact force and the tail end position of the mechanical arm, and adjusting the pose of the mechanical arm through the first target impedance model so as to realize the pose adjustment of the mechanical arm.
The first impedance model second order differential kinetic equation can be expressed as
Wherein m is the system mass; c is a damping coefficient; k is a stiffness coefficient; f is the environmental contact force.
The first target impedance model obtained from the equation (2-1) has the following three forms
In the formula Md，Bd,KdRespectively an inertia matrix, a damping matrix and a rigidity matrix of the target impedance model;
x is the acceleration, speed and position vector of the tail end of the robot respectively;
Xdrespectively representing the target acceleration, the target speed and the target position vector of the tail end of the robot; f is the actual contact force vector between the robot tip and the environment.
In some embodiments, the robot arm operation control method further comprises: obtaining a contact force deviation value according to the contact force of the target tail end and the actual contact force; and obtaining a second target impedance model according to the first target impedance model and the contact force deviation value.
By introducing a target tip contact force FdCalculating the difference between the actual contact force F and the actual contact force F, and calculating the contact force deviation Fe＝F-FdA second impedance model can be obtained by introducing equation (2-2):
to ensure more accurate force control, a third target impedance model of the second impedance model in equation (2-3), i.e., the impedance model is typically selected
In some embodiments, the robot arm operation control method further comprises: and adjusting the contact force and the position of the tail end of the mechanical arm according to the pose error information and the second target impedance model.
And converting the position deviation of the tail end of the mechanical arm into a target contact force between the tail end of the mechanical arm and the environment through a second target impedance model, and performing joint torque closed-loop control on the mechanical arm through an inner loop control circuit to enable the actual contact force between the mechanical arm and the environment to follow the target contact force.
In some embodiments, the tip contact force and the tip position of the robotic arm are adjusted according to the contact force deviation value and the second target impedance model. The contact force deviation between the mechanical arm and the environment is converted into mechanical arm joint position feedback adjustment so as to correct the tail end position of the robot and enable the actual contact force to follow the target contact force.
Referring to fig. 4, in some embodiments, the method for controlling the operation of the robot further includes: obtaining an output torque of the impedance system according to the expected system stiffness, the angle difference, the expected system damping and the speed difference; obtaining a moment error according to the output moment and the actual moment of the impedance system; and adjusting the output torque of the tail end motor according to the torque error.
And adjusting the output torque of the tail end motor according to the torque error so as to carry out compliant contact control on the output angular displacement of the tail end actuating mechanism of the mechanical arm, thereby controlling the contact state of the actuating mechanism and the wall to be operated.
Wherein, the actuating mechanism impedance control model is:
in the formula, KimA desired system stiffness; dimDamping the desired system; f. ofimOutputting force/moment for the impedance system; thetadesIs a desired angle; thetaactIs an actual angle;
a desired speed;
is the actual speed. A resistance f can be obtained from the formula (2-5)imSo that it follows the actual moment f acquired by the force sensoractThen can acquireError amount e in equation (2-6)n。
en＝fact-fim (2-6)
The inner ring of the impedance control is used as force control, and the current of the motor is controlled to control the output to be
u＝un+KfIfim (2-7)
In the formula KfI-motor torque/current conversion factor.
As shown in fig. 4, a corresponding parameter list is obtained through test data of the field test, and the expected angle θ of the actuator is obtained by judging the construction state according to the parameter listdes(ii) a Detecting the angle of the actuating mechanism to obtain the actual angle thetaact(ii) a According to the desired angle thetadesActual angle thetaactTo obtain a desired speed
Actual speed
Obtaining the current expected system rigidity K through construction state judgmentimDesired system damping Dim. Through a desired angle thetadesActual angle thetaactDesired speed
Actual speed
And formula (2-5) obtaining the impedance moment fim。
Obtaining the actual moment f of the actuator by means of a force sensoractAnd by means of an impedance moment fimActual moment factObtain an error amount en。
According to error quantity enProportional integral derivative control (PID control) of the control signal of the actuator to adjust the torque of the actuator, in particular, as a function of the actual torque factResistance, resistanceMoment of resistance fimThe current value of the control motor of the actuating mechanism is adjusted to adjust the motor torque of the actuating mechanism.
In some embodiments, the actual torque f is determinedact, moment of impedance fimGravity compensation coefficient f of mechanical armcomObtain an error amount enAccording to the error amount enProportional integral derivative control (PID control) is performed on the control signal of the actuator to adjust the torque of the actuator.
Wherein, the gravity compensation coefficient fcomFor compensating the influence of gravity on the mechanical arm by using a gravity compensation coefficient fcomSo as to eliminate the nonlinear disturbance of the gravity moment on the mechanical arm joint. According to the gravity compensation coefficient fcomAnd generating corresponding gravity compensation information according to the pose of the mechanical arm and the working state and execution information of the end effector, and performing gravity compensation on the operation of the mechanical arm according to the gravity compensation information.
In some embodiments, an embodiment of the present invention further provides a robot arm control apparatus, including: at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions that are executed by the at least one processor, so that the at least one processor implements the robot operation control method in any of the embodiments described above when executing the instructions.
The control device controls the pose of the mechanical arm and the working state of the end effector so that the mechanical arm can complete different execution instructions, for example, the actuator can complete wall plastering operation according to the instruction issued by the processor. The pose of the mechanical arm is adjusted through a mechanical arm operation control method, so that the pose of the mechanical arm is changed, and plastering is performed on the designated position of the wall surface.
The end effector is subjected to flexible contact control through the impedance model, so that the end effector can uniformly apply wall dust on the wall surface.
In some embodiments, the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores computer-executable instructions for causing a computer to execute the robot arm operation control method according to any one of the above embodiments.
The robot arm work control method in the above embodiments is quickly executed by programming the above method to be stored in a computer-readable storage medium to be called by a processor from the computer-readable storage medium.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (9)
1. The mechanical arm operation control method is characterized in that an initial joint and at least one target joint are arranged on the mechanical arm, and an end effector is arranged at the tail end of the mechanical arm, and the mechanical arm operation control method comprises the following steps:
acquiring initial joint position information and current arm shape information;
obtaining current pose information of a target joint according to the initial joint position information and the current arm shape information;
acquiring preset terminal pose information, and obtaining a Cartesian path according to the initial joint position information and the preset terminal pose information;
obtaining preset terminal sub-path position information according to the Cartesian path;
obtaining pose error information according to the preset terminal sub-path position information and the terminal current pose information;
performing gradient projection processing and redundant decomposition according to the pose error information and obtaining joint increment information;
adjusting the pose of the target joint according to the current pose information and the joint increment information of the target joint;
acquiring terminal speed information according to the preset terminal pose information, and acquiring target joint speed information according to the current pose information of the target joint;
obtaining a target joint velocity information general solution according to the terminal velocity information, the target joint velocity information and the Jacobian matrix;
and adjusting the pose of the target joint according to the current pose information, the joint increment information and the target joint speed information.
2. The robot arm work control method according to claim 1, comprising:
and the preset weight matrix is an identity matrix, and the target joint velocity information general solution is obtained according to the wide inverse matrix of the Jacobian matrix, the vector information and the terminal velocity information.
3. The robot arm work control method according to claim 2, further comprising:
discretizing and track interpolation processing is carried out on the Cartesian paths to generate a plurality of Cartesian sub-paths and obtain position information of the preset terminal sub-paths;
obtaining pose error information according to the preset tail end sub-path position information and the tail end current pose information;
and obtaining the joint increment information according to the pose error information, and iterating the joint increment information to obtain joint increment information of adjacent joints.
4. The robot arm work control method according to claim 1, further comprising:
adjusting the relation between the tail end contact force and the tail end position of the mechanical arm according to the impedance characteristic of the mechanical arm;
obtaining a first target impedance model according to the relation between the tail end contact force and the tail end position of the mechanical arm;
adjusting an output power of the end effector according to the first target impedance model.
5. The robot arm work control method according to claim 4, further comprising: obtaining a contact force deviation value according to the contact force of the target tail end and the actual contact force;
obtaining a second target impedance model according to the first target impedance model and the contact force deviation value;
adjusting the output power of the end effector according to the second target impedance model.
6. The robot arm work control method according to claim 5, further comprising: adjusting the tail end contact force and the tail end position of the mechanical arm according to the pose error information and a second target impedance model;
or the like, or, alternatively,
and adjusting the tail end contact force and the tail end position of the mechanical arm according to the contact force deviation value and a second target impedance model.
7. The robot arm work control method according to claim 6, further comprising: the end executor is internally provided with an end motor;
obtaining an output torque of the impedance system according to the expected system stiffness, the angle difference, the expected system damping and the speed difference;
obtaining a moment error according to the output moment and the actual moment of the impedance system;
and adjusting the output torque of the tail end motor according to the torque error.
8. The robot arm control apparatus is characterized by comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions for execution by the at least one processor to cause the at least one processor, when executing the instructions, to implement a method of controlling operation of a robotic arm as claimed in any one of claims 1 to 7.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer-executable instructions for causing a computer to execute the robot arm work control method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011017129.5A CN112171673B (en) | 2020-09-24 | 2020-09-24 | Robot arm operation control method, control apparatus, and computer-readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011017129.5A CN112171673B (en) | 2020-09-24 | 2020-09-24 | Robot arm operation control method, control apparatus, and computer-readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112171673A CN112171673A (en) | 2021-01-05 |
| CN112171673B true CN112171673B (en) | 2022-03-29 |
Family
ID=73955515
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011017129.5A Active CN112171673B (en) | 2020-09-24 | 2020-09-24 | Robot arm operation control method, control apparatus, and computer-readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112171673B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112809686B (en) * | 2021-02-02 | 2022-08-16 | 杭州柳叶刀机器人有限公司 | Robot body state follow-up control method and device |
| CN113263498B (en) * | 2021-04-12 | 2022-06-10 | 万勋科技(深圳)有限公司 | Mechanical arm movement control method and device, terminal equipment and storage medium |
| CN113334391B (en) * | 2021-08-06 | 2021-11-09 | 成都博恩思医学机器人有限公司 | Method and system for controlling position of mechanical arm, robot and storage medium |
| CN113616338B (en) * | 2021-09-15 | 2023-10-20 | 上海微创医疗机器人（集团）股份有限公司 | Computer readable storage medium, alignment method and system, and surgical robot system |
| CN114523470A (en) * | 2021-12-30 | 2022-05-24 | 浙江图盛输变电工程有限公司 | Robot operation path planning method based on bearing platform linkage |
| WO2023163955A1 (en) * | 2022-02-22 | 2023-08-31 | Intuitive Surgical Operations, Inc. | Techniques for repositioning a computer-assisted system with motion partitioning |
| CN114800523B (en) * | 2022-05-26 | 2023-12-01 | 江西省智能产业技术创新研究院 | Mechanical arm track correction method, system, computer and readable storage medium |
| CN116512278B (en) * | 2023-06-26 | 2023-12-01 | 极限人工智能(北京)有限公司 | Mechanical arm tail end linear motion control method and system based on virtual target point |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102004026813A1 (en) * | 2004-06-02 | 2005-12-29 | Kuka Roboter Gmbh | Method and device for controlling handling devices |
| CN108621162A (en) * | 2018-05-09 | 2018-10-09 | 广西科技大学 | A kind of manipulator motion planning method |
| CN109159151B (en) * | 2018-10-23 | 2021-12-10 | 北京无线电测量研究所 | Mechanical arm space trajectory tracking dynamic compensation method and system |
| CN109366488B (en) * | 2018-12-07 | 2021-07-16 | 哈尔滨工业大学 | Superimposed oscillating force Cartesian impedance control method for robot assembly |
-
2020
- 2020-09-24 CN CN202011017129.5A patent/CN112171673B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN112171673A (en) | 2021-01-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112171673B (en) | Robot arm operation control method, control apparatus, and computer-readable storage medium | |
| CN111136633B (en) | All-state control method for flexible master-slave robot system under time-varying delay | |
| Dixon | Adaptive regulation of amplitude limited robot manipulators with uncertain kinematics and dynamics | |
| JP2022169722A (en) | Method for controlling mechanical system, mechanical system controller, robotic manipulator, and non-transitory computer readable storage medium | |
| US20200282558A1 (en) | System and method for controlling a robot with torque-controllable actuators | |
| Yin et al. | Direct adaptive robust tracking control for 6 DOF industrial robot with enhanced accuracy | |
| Rigatos | Model-based and model-free control of flexible-link robots: A comparison between representative methods | |
| CN110253574B (en) | Multi-task mechanical arm pose detection and error compensation method | |
| Aghili | Adaptive control of manipulators forming closed kinematic chain with inaccurate kinematic model | |
| WO2007111252A1 (en) | Manipulator control method and control system | |
| US20110010008A1 (en) | Method And Device For Controlling A Manipulator | |
| CN110154024B (en) | Assembly control method based on long-term and short-term memory neural network incremental model | |
| Kraus | Force control of cable-driven parallel robots | |
| Deutschmann et al. | Position control of an underactuated continuum mechanism using a reduced nonlinear model | |
| Wang et al. | Adaptive Jacobian position/force tracking control of free-flying manipulators | |
| Zollo et al. | Regulation with on-line gravity compensation for robots with elastic joints | |
| GB2592404A (en) | Robotic device | |
| Ghasemi et al. | Adaptive image-based visual servoing of 6 DOF robots using switch approach | |
| Lippiello et al. | Robot interaction control using force and vision | |
| Fateh et al. | On the transforming of control space by manipulator Jacobian | |
| Nganga-Kouya et al. | A novel adaptive hybrid force-position control of a robotic manipulator | |
| KR102156655B1 (en) | Control framework based on dynamic simulation for robot | |
| CN114888793A (en) | Double-layer cooperative control method for multi-arm double-beam laser welding robot | |
| Fernandez et al. | Multi-Surface Admittance Control Approach applied on Robotic Assembly of Large-Scale parts in Aerospace Manufacturing | |
| Bascetta et al. | Task space visual servoing of eye-in-hand flexible manipulators |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |