CN114918924B - Robot traction teaching method and device, electronic device and storage medium - Google Patents

Robot traction teaching method and device, electronic device and storage medium Download PDF

Info

Publication number
CN114918924B
CN114918924B CN202210849954.4A CN202210849954A CN114918924B CN 114918924 B CN114918924 B CN 114918924B CN 202210849954 A CN202210849954 A CN 202210849954A CN 114918924 B CN114918924 B CN 114918924B
Authority
CN
China
Prior art keywords
robot
joint
damping
traction
calculating
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
Application number
CN202210849954.4A
Other languages
Chinese (zh)
Other versions
CN114918924A (en
Inventor
王岩
查文斌
张毛飞
丁磊
姚庭
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Faoyiwei Suzhou Robot System Co ltd
Original Assignee
Faoyiwei Suzhou Robot System Co ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Faoyiwei Suzhou Robot System Co ltd filed Critical Faoyiwei Suzhou Robot System Co ltd
Priority to CN202210849954.4A priority Critical patent/CN114918924B/en
Publication of CN114918924A publication Critical patent/CN114918924A/en
Application granted granted Critical
Publication of CN114918924B publication Critical patent/CN114918924B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

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
    • B25J9/1628—Programme controls characterised by the control loop
    • B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J13/00—Controls for manipulators
    • 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
    • B25J9/1607—Calculation of inertia, jacobian matrixes and inverses
    • 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
    • B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Landscapes

  • Engineering & Computer Science (AREA)
  • Robotics (AREA)
  • Mechanical Engineering (AREA)
  • Automation & Control Theory (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Fuzzy Systems (AREA)
  • Software Systems (AREA)
  • Numerical Control (AREA)

Abstract

The invention belongs to the technical field of robots, and discloses a robot traction teaching method, a device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring the position information of the robot joint in real time; after receiving the position information of the joints of the robot, calculating the terminal speed of the robot through a differentiator and a Jacobian matrix; the controller calculates a damping coefficient according to the damping speed relation; calculating joint control torque through an impedance controller; the joint control torque command output by the impedance controller is output to a robot joint servo motor to control the joint to rotate so as to match the traction action of a demonstrator. The robot traction teaching method provided by the invention can judge the traction intention of a demonstrator at low cost and can make a slow traction area smoother.

Description

Robot traction teaching method and device, electronic device and storage medium
Technical Field
The invention relates to the technical field of robots, in particular to a robot traction teaching method and device, electronic equipment and a storage medium.
Background
With the rapid development of robot technology, robots are increasingly applied to industrial practical production. The cooperative robot has the advantages of high cost performance, convenience in deployment, convenience in man-machine cooperation and the like, and greatly promotes the development of small and medium-sized manufacturing enterprises. The traction teaching is an important function of the cooperative robot, a demonstrator can freely pull the cooperative robot by hands in a traction teaching mode, the robot can automatically record taught track points and generate action tracks according to the track points, so that complicated code compiling steps are omitted, and the use threshold of the cooperative robot is reduced. The impedance control is one of the schemes for realizing the traction teaching of the cooperative robot and is realized by the quality coefficient in the control algorithmMCoefficient of stiffnessKAnd damping coefficientDThe robot joint control torque is adjusted, so that a demonstrator can freely pull the robot.
However, in the prior art, external devices such as a six-dimensional torque sensor or a laser displacement sensor and the like except for the robot body and the control box are required to acquire information, and a learning algorithm is required to predict a desired position for position control, so that not only is the cost of the whole system greatly increased due to the introduction of the external devices, but also the complexity of the control system is increased due to the communication between different devices and the prediction process of the algorithm, and the real-time performance of control is further influenced. In addition, when the speed of the robot tip is small, for example, when the teach pendant starts to pull or adjusts the pulling direction and the speed is reduced, the damping coefficient is often large, and the robot is difficult to pull.
Therefore, how to judge the traction indication of the robot terminal slow speed area at low cost is a problem to be solved.
Disclosure of Invention
The invention aims to provide a robot traction teaching method, a device, an electronic device and a storage medium, which are used for judging the traction indication of a robot tail end slow speed area with low cost.
In a first aspect, an embodiment of the present invention provides a robot traction teaching method, including:
s1, acquiring joint position information in the traction process of the robot in real time;
s2, after receiving the position information of the robot joint, calculating the terminal speed of the robot through a differentiator and a Jacobian matrix;
s3, calculating a damping function through the damping speed relation, and firstly calculating an adjusting function
Figure M_220714143135968_968464001
Recalculating the damping function
Figure M_220714143136015_015371002
Wherein
Figure M_220714143136062_062466003
、
Figure M_220714143136079_079301004
And
Figure M_220714143136094_094946005
is a constant set according to the range of the actual speed achievable by the robot in traction and the experimentally measured damping coefficient range,
Figure M_220714143136126_126204006
is a modulus of the robot tip velocity vector;
and S4, calculating joint control torque:
Figure M_220714143136157_157443001
wherein
Figure M_220714143136204_204312002
The moment is controlled for the joint in question,qfor the information on the position of the joints of the robot,
Figure M_220714143136219_219929003
is a transpose of the jacobian matrix of the robot,KandDrespectively the rigidity coefficient, the damping coefficient and the damping coefficient of the impedance modelDBy damping function
Figure M_220714143136251_251194004
The method comprises the steps of (1) obtaining,
Figure M_220714143136283_283955005
for the difference between the desired position and the actual position of the robot end,
Figure M_220714143136299_299550006
is the speed of the end of the robot,
Figure M_220714143136330_330761007
is the velocity of the joints of the robot,
Figure M_220714143136346_346407008
in the form of a matrix of the coriolis forces,G(q)is a gravity term;
and S5, outputting the joint control torque command output by the impedance controller to a robot joint servo motor to control the joint to rotate so as to match the traction action of a demonstrator.
Further, in the step S4,
Figure M_220714143136377_377655001
=
Figure M_220714143136408_408910002
，c=
Figure M_220714143136424_424553003
，
Figure M_220714143136455_455790004
is the maximum damping coefficient.
Further, the air conditioner is characterized in that,
Figure M_220714143136473_473325001
to the damping coefficientDBecome into
Figure M_220714143136489_489556002
The speed of time, the teaching of traction at that speed is labor-saving.
In a second aspect, an embodiment of the present invention provides a robot traction teaching device, including:
the acquisition module is used for acquiring joint position information in the robot traction process in real time;
the processing module is used for calculating the tail end speed of the robot through a differentiator and a Jacobian matrix after receiving the position information of the robot joint;
an adjusting module for calculating a damping function according to the damping velocity relationship, and calculating an adjusting function
Figure M_220714143136520_520721001
Recalculating the damping function
Figure M_220714143136551_551992002
Wherein
Figure M_220714143136583_583229003
、
Figure M_220714143136614_614463004
And
Figure M_220714143136630_630104005
is a constant set according to the range of the actual speed that the robot can reach in traction and the range of the experimentally measured damping coefficient,
Figure M_220714143136667_667657006
is a modulus of the robot tip velocity vector;
the calculation module is used for calculating the joint control torque:
Figure M_220714143136686_686712001
wherein
Figure M_220714143136733_733614002
The moment is controlled for the joint in question,qfor the information on the position of the joints of the robot,
Figure M_220714143136749_749235003
is a transpose of the jacobian matrix of the robot,KandDrespectively the rigidity coefficient, the damping coefficient and the damping coefficient of the impedance modelDBy damping function
Figure M_220714143136780_780528004
The method comprises the steps of (1) obtaining,
Figure M_220714143136811_811746005
for the difference between the desired position and the actual position of the robot tip,
Figure M_220714143136827_827387006
is the speed of the end of the robot,
Figure M_220714143136842_842993007
for robot to closeThe speed of the motor is saved,
Figure M_220714143136875_875680008
in the form of a matrix of the coriolis forces,G(q)is the gravity term.
Further, in the adjusting module,
Figure M_220714143136891_891810001
=
Figure M_220714143136923_923075002
，c=
Figure M_220714143136938_938697003
，
Figure M_220714143136969_969930004
is the maximum damping coefficient.
Further, the air conditioner is provided with a fan,
Figure M_220714143136985_985583001
is a damping coefficientDBecome into
Figure M_220714143137016_016823002
The speed of time, the teaching of traction at that speed is labor-saving.
In a third aspect, an embodiment of the present invention provides an electronic device, including: the system comprises a processor, a memory and a bus, wherein the processor is connected with the memory through the bus, and the memory stores computer readable instructions which are used for realizing the steps of the method provided by the first aspect and any one of the implementation modes of the first aspect when being executed by the processor.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored, and the computer program is used to implement the steps in the method provided by any implementation manner of the first aspect and the first aspect.
By the method, the traction intention of the demonstrator can be effectively judged under the condition that peripheral devices such as a force sensor, a displacement sensor and the like are not added, so that the joint control torque of the robot is adjusted, and the traction of the demonstrator is more labor-saving. The cost of the whole system is reduced because no peripheral equipment is needed, in addition, the whole control process is simpler, links for improving the complexity of the control system such as communication and learning algorithms among a plurality of devices are not introduced, and the real-time performance of the control is ensured. The smoother nature of the slow draft zone may better address these issues when the teach pendant adjusts the tip orientation to cause deceleration to a critical speed.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments of the present invention will be briefly described below, 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, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic diagram of a robot traction teaching control system according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for robot towing teaching according to an embodiment of the present invention;
fig. 3 is a diagram of a damping velocity function of a robot traction teaching method according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a device for teaching robot traction according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
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.
In the prior art, the teaching of the cooperative robot needs to use external equipment such as a six-dimensional torque sensor or a laser displacement sensor except a robot body and a control box to acquire information, and a desired position needs to be predicted through a learning algorithm to control the position, so that the cost of the whole system is greatly increased due to the introduction of the external equipment, the complexity of the control system is increased by the communication among different equipment and the prediction process of the algorithm, and the real-time performance of the control is influenced. In addition, when the speed of the robot end is slow, for example, the speed is decreased when the teach pendant starts to pull or adjusts the pulling direction, and the damping coefficient is often large, so that the robot is difficult to pull.
As shown in fig. 1, the whole robot traction teaching system can be divided into two main parts: controllers and actuators (robots). The main components of the controller are a differentiator, a positive kinematic model, a damping regulator and an impedance controller, and the main components of the actuator are a servo motor and an encoder.
The embodiment provides a robot traction teaching method, as shown in fig. 2, the traction teaching method may include the following steps:
step S1: acquiring joint position information in the robot traction process in real time;
in the process that a demonstrator drags the robot to carry out traction teaching, an induction encoder at a robot joint acquires the position information of the robot joint in real time and sends the information to a controller;
step S2: after receiving the position information of the robot joint, calculating the terminal speed of the robot through a differentiator and a Jacobian matrix;
after receiving the position information of the robot joint, the controller calculates the tail end speed of the robot through a differentiator;
the specific calculation process in the differentiator is that the joint position is firstly filtered by Butterworth
Figure M_220714143137032_032457001
And carrying out filtering processing to reduce noise in the data and avoid inaccurate speed obtained by subsequent differential calculation. Then, the differential calculation is carried out on the joint positions after filtering to obtain the joint speed
Figure M_220714143137065_065146002
. Then, the Jacobian matrix calculated according to a specific robot model is usedJ (q)Calculating the terminal velocity
Figure M_220714143137081_081263003
；
And step S3: at the time of obtaining the terminal velocity
Figure M_220714143137112_112515001
Then, the controller calculates the damping coefficient according to the damping speed relation
Figure M_220714143137128_128147002
；
First, an adjustment function is calculated
Figure M_220714143137159_159446001
Recalculating the damping function
Figure M_220714143137190_190659002
，
Wherein
Figure M_220714143137221_221924001
、
Figure M_220714143137253_253140002
And
Figure M_220714143137270_270685003
is a constant set according to the range of the actual speed that the robot can reach in traction and the range of the experimentally measured damping coefficient,
Figure M_220714143137302_302472004
is the modulus of the terminal velocity vector. Damping velocity function as shown in the velocity damping diagram of fig. 3, velocity on the horizontal axis, damping value on the vertical axis,
Figure M_220714143137333_333701005
it is decided thatDIs reduced to
Figure M_220714143137349_349315006
Velocity of the end of time, i.e.
Figure M_220714143137380_380586007
It is decided that
Figure M_220714143137427_427464008
The speed of the change along with the speed of the tail end;
Figure M_220714143137443_443087009
it is determined that the damping coefficient
Figure M_220714143137458_458714010
Maximum value achievable
Figure M_220714143137494_494351011
I.e. by
Figure M_220714143137509_509984012
。
In particular, as tip speedSize of (2)
Figure M_220714143137541_541220001
Is equal to
Figure M_220714143137556_556858002
Then, can obtain
Figure M_220714143137588_588099003
Therefore, it is
Figure M_220714143137619_619380004
The value of (A) represents when the damping parameter isDIs reduced to
Figure M_220714143137634_634987005
The velocity of the tip.
Figure M_220714143137668_668147001
The damping function has the following advantages:
firstly, a damping regulator in the controller adjusts the damping coefficient of the robot
Figure M_220714143137684_684277001
Set as a function of the velocity of the robot tip rather than a preset fixed value. The function has the following functions: the damping coefficient decreases when the tip speed increases and increases when the tip speed decreases. The damping coefficient participates in the calculation of the joint control torque, so that the joint control torque output by the controller is correspondingly adjusted according to the traction speed of a demonstrator.
Secondly, during the traction teaching, the situation that the traction is just started or the orientation of the tail end is adjusted is often encountered, at this time, the speed of the tail end is very small, the tail end of the robot is in a slow traction area, as shown in fig. 3, in the slow traction area at the upper right corner,
Figure M_220714143137715_715561001
the change of the damping function is smoother, and sudden change can not occur, thereby influencing the feeling of a demonstrator. Specifically, the conventional method requires the demonstrator to spend a large amount of effort to increase the tip speed to break through the critical speed and make the damping parameterDDescending; conventional methods result in damping parameters when the teach pendant adjusts the tip orientation resulting in deceleration to a critical speedDSuddenly rises to the maximum value, so that the robot is difficult to pull and the demonstrator cannot react in time.
Figure M_220714143137731_731167002
The smoother nature of the traction zone at slow speeds may better address these issues.
Finally, the parameters
Figure M_220714143137762_762408001
Determine (a)DIs reduced to
Figure M_220714143137778_778051002
Velocity of the tip, which means no matter what the velocity of the tipbOrcHow to change the number of the first and second groups,
Figure M_220714143137824_824912003
must pass through the point
Figure M_220714143137856_856160004
I.e. this constraint can ensure that the velocity changes to at the end
Figure M_220714143137889_889419005
When necessary, there areD=
Figure M_220714143137920_920668006
This enables to select an appropriate one according to actual needs
Figure M_220714143137951_951875007
The value is obtained. Through experimental tests, the method has the advantages thatD=
Figure M_220714143137983_983168008
The demonstrator feels more labor-saving,
Figure M_220714143138014_014380009
is a damping coefficientDBecome into
Figure M_220714143138030_030023010
The speed of time, the traction teaching is more labor-saving at the speed.
And step S4: calculating joint control torque through an impedance controller;
the robot impedance control is realized by firstly representing the dynamic characteristics of the robot to the external force in the terminal Cartesian space by the impedance model:
Figure M_220714143138061_061674001
；
wherein,M、DandKfor the mass, damping and stiffness coefficients of the impedance model,
Figure M_220714143138094_094449001
the difference between the desired acceleration and the actual acceleration for the end of the robot,
Figure M_220714143138110_110087002
for the difference between the desired velocity and the actual velocity of the robot tip,
Figure M_220714143138141_141350003
for the difference between the desired position and the actual position of the robot tip,
Figure M_220714143138156_156984004
the contact external force applied to the tail end of the robot;
will end up actually accelerating
Figure M_220714143138188_188198001
To robot joint acceleration of
Figure M_220714143138250_250688002
；
Wherein,
Figure M_220714143138299_299533001
is the actual acceleration of the end of the robot,
Figure M_220714143138346_346424002
an acceleration is desired for the robot tip and,J(q) Is a jacobian matrix of the robot,
Figure M_220714143138377_377645003
derivation for Jacobian matrix;
through inverse dynamics of the robot, the joint control torque is obtained as follows:
Figure P_220714143138408_408913001
wherein,
Figure M_220714143138455_455798001
in order to control the moment for the joint,M(q)is the inertial matrix of the robot in question,
Figure M_220714143138473_473304002
is the inverse of the jacobian matrix,
Figure M_220714143138505_505059003
is a jacobian matrix of the joint velocities,
Figure M_220714143138536_536342004
is the transpose of the Jacobian matrix,
Figure M_220714143138567_567607005
is a matrix of the coriolis forces,G(q) Is a gravity term;
because the external force term in the above formula needs a six-dimensional force sensor, and the six-dimensional force sensor belongs to a peripheral with higher cost, impedance control is simplified, so that the measurement of the external force is omitted, and the influence of the terminal acceleration term is eliminated.
Calculating a system dynamic characteristic function:
Figure M_220714143138582_582740001
，
Figure M_220714143138630_630097002
the acceleration of the joint is brought into the joint control moment, and the updated joint control moment is obtained
Figure M_220714143138645_645716001
；
And controlling the moment based on the joint, thereby realizing the motion control of the robot.
Step S5: the joint control torque command output by the impedance controller is output to a robot joint servo motor, and the joint servo motor receives the joint control torque output by the impedance controller and drives the robot joint to move so as to conform to the guiding action of a demonstrator, so that the comfort of the demonstrator is improved.
Through the technical scheme, the traction robot teaching method effectively judges the traction intention of a demonstrator under the condition that peripheral devices such as a force sensor or a displacement sensor are not added, so that the joint control torque of the robot is adjusted, and the traction of the demonstrator is more labor-saving. The cost of the whole system is reduced because no peripheral equipment is needed, in addition, the whole control process is simpler, links for improving the complexity of the control system such as communication and learning algorithms among a plurality of devices are not introduced, and the real-time performance of the control is ensured; in addition, in a slow speed area when the tail end of the robot just starts to pull or the position of the tail end is adjusted, the pulling change is smoother by setting a damping function, and the feeling of a demonstrator is not influenced like sudden change; by selecting appropriate ones according to actual requirements
Figure M_220714143138693_693577001
The value can judge when the demonstrator feels more labor-saving.
According to an embodiment of the present invention, there is also provided a robot teaching apparatus corresponding to the robot teaching method, specifically, the apparatus including:
an acquisition module: acquiring joint position information in the robot traction process in real time;
in the process that a demonstrator drags the robot to carry out traction teaching, an induction encoder at a robot joint acquires the position information of the robot joint in real time and sends the information to a controller;
a processing module: after receiving the position information of the robot joint, calculating the tail end speed of the robot through a differentiator and a Jacobian matrix;
after receiving the position information of the robot joint, the controller calculates the tail end speed of the robot through a differentiator;
the specific calculation process in the differentiator is that the joint position is firstly filtered by Butterworth
Figure M_220714143138709_709205001
And carrying out filtering processing to reduce noise in the data and avoid inaccurate speed obtained by subsequent differential calculation. Then, the differential calculation is carried out on the joint positions after filtering to obtain the joint speed
Figure M_220714143138740_740446002
. Then, the Jacobian matrix calculated according to a specific robot model is used
Figure M_220714143138756_756100003
Calculating the terminal velocity
Figure M_220714143138787_787329004
；
An adjusting module: at the time of obtaining the terminal velocity
Figure M_220714143138818_818579001
Then, the controller calculates the resistance according to the damping speed relationCoefficient of damping
Figure M_220714143138834_834201002
；
First, an adjustment function is calculated
Figure M_220714143138849_849832001
Recalculating the damping function
Figure M_220714143138885_885467002
，
Wherein
Figure M_220714143138932_932342001
、
Figure M_220714143138947_947960002
And
Figure M_220714143138978_978745003
is a constant set according to the range of the actual speed that the robot can reach in traction and the range of the experimentally measured damping coefficient,
Figure M_220714143138994_994857004
is the modulus of the terminal velocity vector. Damping velocity function as shown in the velocity damping diagram of fig. 3, velocity on the horizontal axis, damping value on the vertical axis,
Figure M_220714143139026_026090005
it is decided thatDIs reduced to
Figure M_220714143139041_041719006
Velocity of the end of time, i.e.
Figure M_220714143139074_074887007
It is decided thatDThe speed of the change along with the speed of the tail end;
Figure M_220714143139122_122334008
it is determined that the damping coefficientDMaximum value achievable
Figure M_220714143139137_137914009
I.e. by
Figure M_220714143139153_153543010
。
In particular, the magnitude of the tip speed
Figure M_220714143139184_184782001
Is equal to
Figure M_220714143139216_216045002
Then, can obtain
Figure M_220714143139231_231659003
Therefore, it is
Figure M_220714143139265_265307004
The value of (A) represents when the damping parameter isDIs reduced to
Figure M_220714143139297_297091005
The velocity of the tip.
Figure M_220714143139312_312716001
The damping function has the following advantages:
firstly, a damping regulator in the controller adjusts the damping coefficient of the robot
Figure M_220714143139359_359088001
Set as a function of the velocity of the robot tip rather than a preset fixed value. The function has the effect of: the damping coefficient decreases when the tip speed increases and increases when the tip speed decreases. The damping coefficient participates in the calculation of the joint control torque, so that the joint control torque output by the controller is correspondingly adjusted according to the traction speed of a demonstrator.
Secondly, during the towing teaching, the end of the towing or adjusting is often touchedIn the case of azimuth, when the speed of the end is very low, the end of the robot is in the slow traction zone, as shown in fig. 3, in the slow zone in the upper right corner,
Figure M_220714143139374_374743001
the change of the damping function is smoother, and sudden change cannot occur, so that the feeling of a demonstrator is influenced. Specifically, the conventional method requires the demonstrator to spend a large amount of effort to increase the tip speed to break through the critical speed and make the damping parameterDDescending; conventional methods result in damping parameters when the teach pendant adjusts the tip orientation resulting in deceleration to a critical speedDSuddenly rises to the maximum value, so that the robot is difficult to pull and the demonstrator cannot react in time.
Figure M_220714143139406_406497002
The smoother nature of the traction zone at slow speeds may better address these issues.
Finally, the parameters
Figure M_220714143139422_422109001
Determine (ing)DIs reduced to
Figure M_220714143139453_453337002
The velocity of the tip, which means that no matter how b or c changes,
Figure M_220714143139471_471861003
must pass through the point
Figure M_220714143139503_503658004
I.e. this constraint can ensure that the velocity changes to at the end
Figure M_220714143139534_534881005
When necessary, there are
Figure M_220714143139550_550531006
This enables to select an appropriate one according to actual needs
Figure M_220714143139581_581775007
The value is obtained. Through experimental tests, the method has the advantages that
Figure M_220714143139597_597378008
，The demonstrator feels that the labor is saved,
Figure M_220714143139628_628640009
is a damping coefficientDBecome into
Figure M_220714143139659_659883010
The speed of time, the teaching of traction at that speed is labor-saving.
A calculation module: calculating joint control torque through an impedance controller;
the robot impedance control is realized by firstly representing the dynamic characteristics of the robot to the external force in the terminal Cartesian space by the impedance model:
Figure M_220714143139676_676936001
；
wherein,M、DandKfor the mass, damping and stiffness coefficients of the impedance model,
Figure M_220714143139708_708738001
the difference between the desired acceleration and the actual acceleration for the end of the robot,
Figure M_220714143139739_739951002
for the difference between the desired velocity and the actual velocity of the robot tip,
Figure M_220714143139755_755583003
for the difference between the desired position and the actual position of the robot tip,
Figure M_220714143139786_786855004
outside of the contact of the robot endForce;
will end up actually accelerating
Figure M_220714143139802_802471001
To robot joint acceleration of
Figure M_220714143139849_849350002
；
Wherein,
Figure M_220714143139898_898158001
is the actual acceleration of the end of the robot,
Figure M_220714143139929_929410002
an acceleration is desired for the robot tip,
Figure M_220714143139945_945030003
is a jacobian matrix of the robot,
Figure M_220714143139976_976288004
；
and obtaining the joint control torque through inverse dynamics of the robot as follows:
Figure P_220714143140007_007556001
wherein,
Figure M_220714143140054_054442001
in order to control the moment for the joint,
Figure M_220714143140071_071465002
is an inertia matrix of the robot
Figure M_220714143140103_103256003
Jacobian matrix for joint velocity
Figure M_220714143140134_134523004
Is the transpose of the Jacobian matrix,
Figure M_220714143140165_165259005
is a matrix of the coriolis forces,
Figure M_220714143140181_181367006
is a gravity term;
because the external force term in the above formula needs a six-dimensional force sensor, and the six-dimensional force sensor belongs to a peripheral with higher cost, impedance control is simplified, so that the measurement of the external force is omitted, and the influence of the terminal acceleration term is eliminated.
Calculating a system dynamic characteristic function:
Figure M_220714143140212_212615001
，
Figure M_220714143140243_243874002
the acceleration of the joint is brought into the joint control moment, and the updated joint control moment is obtained
Figure M_220714143140276_276542001
。
A control module: the joint control torque command output by the impedance controller is output to a robot joint servo motor, and the joint servo motor receives the joint control torque output by the impedance controller and drives the robot joint to move so as to conform to the guiding action of a demonstrator, so that the comfort of the demonstrator is improved.
Through the technical scheme, the traction robot teaching device provided by the invention can effectively judge the traction intention of a demonstrator under the condition of not increasing external devices such as a force sensor or a displacement sensor, so that the joint control torque of the robot is adjusted, and the traction of the demonstrator is more labor-saving. The cost of the whole system is reduced because no peripheral equipment is needed, in addition, the whole control process is simpler, and links for improving the complexity of the control system, such as communication among a plurality of devices, learning algorithm and the like are not introducedThe real-time performance of control is ensured; in addition, in a slow speed area when the tail end of the robot just starts to pull or the position of the tail end is adjusted, the pulling change is smoother by setting a damping function, and the feeling of a demonstrator is not influenced like sudden change; by selecting appropriate ones according to actual requirements
Figure M_220714143140323_323935001
The value can judge when the demonstrator feels more labor-saving.
According to an embodiment of the present invention, there is also provided an electronic device corresponding to a robot teaching method, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the method steps of the above teaching method when executing the computer program.
According to an embodiment of the present invention, there is also provided a computer-readable storage medium corresponding to the robot teaching method, the computer-readable storage medium storing a computer program which, when executed by a processor, implements the method steps of the above teaching method.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention, and the electronic device 500 shown in fig. 5 may include: at least one processor 510, e.g., a CPU, at least one communication interface 520, at least one memory 530, and at least one communication bus 540. Wherein the communication bus 540 is used for realizing direct connection communication of the components. The communication interface 520 of the device in the embodiment of the present invention is used for performing signaling or data communication with other node devices. Memory 530 may be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. Memory 530 may optionally be at least one memory device located remotely from the aforementioned processor. The memory 530 stores computer readable instructions, which when executed by the processor 510, cause the electronic device to perform the method process of fig. 3.
An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a server, implements the method process shown in fig. 3.
In the embodiments provided in the present invention, it should be understood that the disclosed system and method can be implemented in other ways. The above-described system embodiments are merely illustrative, and for example, the division of the system apparatus into only one logical functional division may be implemented in other ways, and for example, a plurality of apparatuses or components may be combined or integrated into another system, or some features may be omitted, or not implemented.
In addition, units described as separate parts may or may not be physically separate, and parts displayed 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
The above description is only an example of the present invention, and is not intended to limit the scope of the present invention, and it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A robot traction teaching method is characterized by comprising the following steps:
s1, acquiring joint position information in the traction process of the robot in real time;
s2, after receiving the position information of the robot joint, calculating the tail end speed of the robot through a differentiator and a Jacobian matrix;
s3, calculating a damping function through the damping speed relation, and firstly calculating an adjusting function
Figure M_220907102603591_591855001
According to the regulationFunction calculation damping function
Figure M_220907102603687_687514002
Wherein
Figure M_220907102603750_750082003
、bandcis a constant set according to the range of the actual speed that the robot can reach in traction and the range of the experimentally measured damping coefficient,
Figure M_220907102603781_781324004
is a modulus of the robot tip velocity vector;
and S4, calculating joint control torque:
Figure M_220907102603828_828685001
wherein
Figure M_220907102603892_892635002
The moment is controlled for the joint in question,qfor the information on the position of the joints of the robot,
Figure M_220907102603924_924399003
is a transpose of the jacobian matrix of the robot,KandDrespectively the rigidity coefficient and the damping coefficient of the impedance modelDBy damping function
Figure M_220907102603955_955678004
The method comprises the steps of (1) obtaining,
Figure M_220907102604065_065016005
for the difference between the desired position and the actual position of the robot end,
Figure M_220907102604098_098210006
is the speed of the end of the robot,
Figure M_220907102604238_238834007
is the speed of the joint of the robot,
Figure M_220907102604270_270112008
in the form of a matrix of the coriolis forces,G(q) Is a gravity term;
and S5, outputting the joint control torque command output by the impedance controller to a robot joint servo motor to control the joint to rotate.
2. The robot towing teaching method according to claim 1, wherein in the step S3,c=
Figure M_220907102604286_286655001
，
Figure M_220907102604318_318477002
is the maximum damping coefficient.
3. The robot drag teaching method according to claim 2, wherein the method further comprises
Figure M_220907102604334_334062001
=
Figure M_220907102604365_365340002
Damping coefficient of timeDBecome into
Figure M_220907102604380_380938003
。
4. The robot tow teaching method according to claim 1, wherein the calculating a joint control moment includes:
representing the dynamic characteristics of the robot to the external force in the terminal Cartesian space by using the impedance model:
Figure M_220907102604412_412173001
；
wherein,M、DandKfor the mass, damping and stiffness coefficients of the impedance model,
Figure M_220907102604459_459071001
the difference between the desired acceleration and the actual acceleration for the end of the robot,
Figure M_220907102604492_492226002
for the difference between the desired velocity and the actual velocity of the robot tip,
Figure M_220907102604508_508365003
for the difference between the desired position and the actual position of the robot tip,
Figure M_220907102604539_539611004
the contact external force applied to the tail end of the robot;
will end up actually accelerating
Figure M_220907102604555_555271001
Switching to robot joint acceleration of
Figure M_220907102604617_617740002
；
Wherein,
Figure M_220907102604683_683630001
is the actual acceleration of the end of the robot,
Figure M_220907102604715_715427002
an acceleration is desired for the robot tip,J(q) Is a jacobian matrix of the robot,
Figure M_220907102604731_731037003
derivation for Jacobian matrix;
and obtaining the joint control torque through inverse dynamics of the robot as follows:
Figure P_220907102604762_762289001
wherein,
Figure M_220907102604793_793536001
in order to control the moment for the joint,M(q) Is the inertial matrix of the robot in question,
Figure M_220907102604824_824784002
is the inverse of the jacobian matrix,
Figure M_220907102604856_856028003
is a Jacobian matrix of joint velocities,
Figure M_220907102604887_887694004
is the transpose of the Jacobian matrix,
Figure M_220907102604902_902898005
is a matrix of the coriolis forces,G(q) Is a gravity term;
calculating a system dynamic characteristic function:
Figure M_220907102604934_934141001
，
Figure M_220907102604965_965400002
the joint acceleration is brought into the joint control torque, and the updated joint control torque is obtained
Figure M_220907102604996_996665001
。
5. A robot traction teaching device is characterized by comprising the following modules:
the acquisition module is used for acquiring joint position information in the robot traction process in real time;
the processing module is used for calculating the tail end speed of the robot through a differentiator and a Jacobian matrix after receiving the position information of the joints of the robot;
an adjusting module for calculating the damping function according to the damping speed function relation and calculating the adjusting function
Figure M_220907102605043_043511001
Then, calculating a damping function from the adjustment function
Figure M_220907102605074_074777002
Wherein, in the process,
Figure M_220907102605107_107988003
、bandcis a constant set according to the range of the actual speed that the robot can reach in traction and the range of the experimentally measured damping coefficient,
Figure M_220907102605139_139226004
is a modulus of the robot tip velocity vector;
the calculation module is used for calculating the joint control torque:
Figure M_220907102605154_154849001
wherein
Figure M_220907102605201_201717002
The moment is controlled for the joint in question,qfor the information on the position of the joints of the robot,
Figure M_220907102605217_217363003
as a machineThe transpose of the human jacobian matrix,KandDrespectively the rigidity coefficient, the damping coefficient and the damping coefficient of the impedance modelDBy damping function
Figure M_220907102605248_248598004
The method comprises the steps of (1) obtaining,
Figure M_220907102605264_264225005
for the difference between the desired position and the actual position of the robot tip,
Figure M_220907102605297_297424006
is the speed of the end of the robot,
Figure M_220907102605313_313085007
is the velocity of the joints of the robot,
Figure M_220907102605329_329627008
in the form of a matrix of the coriolis forces,G(q) Is a gravity term;
and the control module is used for outputting the joint control torque command output by the impedance controller to a robot joint servo motor to control the joint to rotate.
6. Robot traction teaching device according to claim 5, wherein in the adjusting module,c=
Figure M_220907102605361_361438001
，
Figure M_220907102605392_392199002
is the maximum damping coefficient.
7. Robot traction teaching device according to claim 6, characterized in that when
Figure M_220907102605408_408275001
=
Figure M_220907102605439_439528002
Damping coefficient of timeDBecome into
Figure M_220907102605455_455154003
。
8. The robotic traction teaching device according to claim 5, wherein the calculating a joint control torque includes:
firstly, the dynamic characteristics of the robot presented to external force in the terminal Cartesian space are represented by the impedance model:
Figure M_220907102605487_487832001
；
wherein,M、DandKfor the mass, damping and stiffness coefficients of the impedance model,
Figure M_220907102605519_519615001
the difference between the desired acceleration and the actual acceleration for the end of the robot,
Figure M_220907102605550_550861002
for the difference between the desired velocity and the actual velocity of the robot tip,
Figure M_220907102605582_582186003
for the difference between the desired position and the actual position of the robot tip,
Figure M_220907102605613_613364004
the contact external force applied to the tail end of the robot;
will end the actual acceleration
Figure M_220907102605644_644617001
To robot joint acceleration of
Figure M_220907102605692_692422002
；
Wherein,
Figure M_220907102605755_755456001
is the actual acceleration of the end of the robot,
Figure M_220907102605786_786705002
an acceleration is desired for the robot tip,J(q) Is a jacobian matrix of the robot,
Figure M_220907102605802_802355003
derivation for Jacobian matrix;
through inverse dynamics of the robot, the joint control torque is obtained as follows:
Figure P_220907102605833_833564001
wherein,
Figure M_220907102605864_864843001
in order to control the moment for the joint,M(q) Is the inertial matrix of the robot in question,
Figure M_220907102605898_898492002
is the inverse of the jacobian matrix,
Figure M_220907102605914_914152003
is a Jacobian matrix of joint velocities,
Figure M_220907102605945_945400004
as a transpose of Jacobian matrices
Figure M_220907102605976_976643005
Is a matrix of the coriolis forces which,G(q) Is a gravity term;
calculating a system dynamic characteristic function:
Figure M_220907102606023_023510001
，
Figure M_220907102606070_070393002
the acceleration of the joint is brought into the joint control moment, and the updated joint control moment is obtained
Figure M_220907102606104_104564001
。
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the robot-towing teaching method of any of claims 1-4 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out a method according to any one of claims 1 to 4.
CN202210849954.4A 2022-07-20 2022-07-20 Robot traction teaching method and device, electronic device and storage medium Active CN114918924B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210849954.4A CN114918924B (en) 2022-07-20 2022-07-20 Robot traction teaching method and device, electronic device and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210849954.4A CN114918924B (en) 2022-07-20 2022-07-20 Robot traction teaching method and device, electronic device and storage medium

Publications (2)

Publication Number Publication Date
CN114918924A CN114918924A (en) 2022-08-19
CN114918924B true CN114918924B (en) 2022-10-04

Family

ID=82815638

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202210849954.4A Active CN114918924B (en) 2022-07-20 2022-07-20 Robot traction teaching method and device, electronic device and storage medium

Country Status (1)

Country Link
CN (1) CN114918924B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117921665B (en) * 2024-01-31 2024-09-20 北京纳通医用机器人科技有限公司 Mechanical arm control method, device, equipment and storage medium
CN118357956B (en) * 2024-06-19 2024-10-01 上海交大智邦科技有限公司 Integrated intelligent clamping jaw device and control method

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101332604B (en) * 2008-06-20 2010-06-09 哈尔滨工业大学 Control method of man machine interaction mechanical arm
CN107026755B (en) * 2017-03-13 2019-07-16 南京邮电大学 A kind of service recommendation method based on sequence study
CN108983601B (en) * 2018-06-19 2021-08-03 江苏大学 Parameter self-tuning impedance control system construction method for improving flexible grabbing performance of picking robot
WO2020001742A1 (en) * 2018-06-26 2020-01-02 Franka Emika Gmbh Device for controlling a robot manipulator
CN109848983B (en) * 2018-12-10 2020-07-28 华中科技大学 Method for guiding robot to cooperatively work by high-compliance person
CN109746913B (en) * 2018-12-29 2022-03-15 深圳市大象机器人科技有限公司 Method and system for teaching robot posture keeping dragging
CN114310965A (en) * 2022-01-18 2022-04-12 上海景吾酷租科技发展有限公司 Mechanical arm impedance control method and system without joint torque measurement
CN114571444A (en) * 2022-03-01 2022-06-03 中南大学 Q-learning-based impedance control method for slagging-off robot

Also Published As

Publication number Publication date
CN114918924A (en) 2022-08-19

Similar Documents

Publication Publication Date Title
CN114918924B (en) Robot traction teaching method and device, electronic device and storage medium
DE102018001676B4 (en) Robot for learning control with regard to operation of a production line and method for controlling the same
US10261497B2 (en) Machine tool for generating optimum acceleration/deceleration
DE102015010124B4 (en) A robot program generating device that generates a robot program for reducing bumps of the joints of the robot
JP6669715B2 (en) Vibration suppressor
CN102189550A (en) Robot having learning control function
CN112809667B (en) Force control method and device of industrial robot and application of force control device
CN106965171A (en) Possesses the robot device of learning functionality
CN109746913B (en) Method and system for teaching robot posture keeping dragging
CN112894821B (en) Current method based collaborative robot dragging teaching control method, device and equipment
US20170090452A1 (en) Machine tool for generating speed distribution
CN107748496B (en) Impedance controller algorithm based on parameter self-adaptive adjustment
CN109507879B (en) Control device and machine learning device
TWI594858B (en) Robotic arm teaching system
US20230191600A1 (en) Motion control method, robot, and computer-readable storage medium
CN116604565A (en) Force guiding control method and system for variable admittance of robot
CN114800523B (en) Mechanical arm track correction method, system, computer and readable storage medium
CN114800513B (en) System and method for automatically generating robot shaft hole assembly program based on single dragging teaching
WO2022247615A1 (en) Method and apparatus for reducing acting force of robot on mounting platform, and storage medium
JPH0635525A (en) Robot arm control method
CN107972029A (en) Mechanical arm instructs control system
JPH08190433A (en) Load weight estimating method
Arango et al. Automatic tuning of adaptive gradient descent based motion cueing algorithm using particle swarm optimisation
CN111742270A (en) Information processing apparatus, information processing method, and computer program
WO2024050729A1 (en) Robot teleoperation system and method

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