CN114770500A - Method, system and application for correcting parameters of mechanical arm controller based on impedance mode - Google Patents
Method, system and application for correcting parameters of mechanical arm controller based on impedance mode Download PDFInfo
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- CN114770500A CN114770500A CN202210342804.4A CN202210342804A CN114770500A CN 114770500 A CN114770500 A CN 114770500A CN 202210342804 A CN202210342804 A CN 202210342804A CN 114770500 A CN114770500 A CN 114770500A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
Abstract
The invention discloses a method, a system and application for correcting a mechanical arm controller based on an impedance mode, wherein the method comprises the following steps: step S1, obtaining impedance control parameters; step S2, controlling the mechanical arm to contact an environmental object along a force control direction, and calculating the environmental rigidity in the force control direction; step S3, obtaining force control parameters according to the environmental rigidity; and step S4, outputting the force control parameters to a controller of the mechanical arm. The invention can solve the problem of adjusting the force control parameters of the mechanical arm in different environments; the rigidity coefficient of the environment is obtained through calculation and is used for reflecting environment information, so that corresponding force control parameters are obtained to correct the controller, and the interaction capacity of the mechanical arm and the environment is improved.
Description
Technical Field
The invention relates to the technical field of control of mechanical arms, in particular to a method, a system and application for correcting parameters of a controller of a mechanical arm based on an impedance mode.
Background
In the classical force control theory impedance control method, a relation model is established according to the dynamic relation between a mechanical arm and the environment, the tail end acting force is indirectly controlled by controlling the tail end displacement of a robot, but the interaction capacity of the mechanical arm and the environment still needs to be further improved, so that the mechanical arm can adaptively adjust force control parameters according to the change of the environment, and the purpose that the optimal force control parameters can be used and fed back to a controller under any environment is achieved.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present invention is to provide a method, a system and an application for correcting parameters of a manipulator controller based on an impedance mode, which can adjust force control parameters according to measured environmental stiffness in different environments, thereby improving real-time interaction capability between the manipulator and the environment.
In order to solve the above technical problem, the present invention provides a method for correcting a parameter of a robot controller based on an impedance mode, comprising:
step S1, obtaining impedance control parameters;
step S2, controlling the mechanical arm to contact an environmental object along a force control direction, and calculating the environmental rigidity in the force control direction;
step S3, obtaining force control parameters according to the environmental rigidity;
and step S4, outputting the force control parameters to a controller of the mechanical arm.
According to the method for correcting the parameters of the manipulator controller based on the impedance mode, in step S1, the impedance control parameters comprise one or more of an elastic coefficient, a damping coefficient, a mass and a virtual friction force.
The invention provides a method for correcting parameters of a mechanical arm controller based on an impedance mode, wherein in step S2, the calculating of the environmental stiffness in the force control direction comprises the following steps:
and calculating the environmental rigidity of the force control direction based on the tail end moment sensor or the joint moment sensor and the environmental deformation amount in the force control direction.
The invention provides a method for correcting parameters of a manipulator controller based on an impedance mode, wherein in step S2, the manipulator is controlled to contact an environmental object along a force control direction, and the method comprises the following steps:
controlling the mechanical arm to move towards an environment object along a force control direction, and obtaining the data of a tail end sensor of the mechanical arm and the position movement data of a tool center point when the tool center point of the mechanical arm is in contact with the environment object and reaches stress balance;
obtaining the environmental stiffness based on the tip sensor data and the positional movement data of the tool center point.
The invention provides a method for correcting parameters of a manipulator controller based on an impedance mode, which comprises the following steps of obtaining force control parameters according to environmental rigidity in step S3:
determining the force control parameters according to preset mapping data from environmental rigidity to the force control parameters; and/or the presence of a gas in the atmosphere,
determining the force control parameters according to a linear model fitting function related to the environmental rigidity; and/or the presence of a gas in the atmosphere,
determining the force control parameters according to a nonlinear model fitting function related to the environmental rigidity; and/or the presence of a gas in the gas,
force control parameters are determined from a neural network of the nonlinear model related to the stiffness of the environment.
The method for correcting the parameters of the manipulator controller based on the impedance mode further includes, in step S3: and fitting the mapping data through the linear model fitting function or the nonlinear model fitting function to determine the force control parameters.
In order to solve the above technical problem, the present invention further provides a system for modifying a robot controller based on an impedance mode, including:
the impedance control module is used for obtaining an impedance control parameter;
the environment rigidity module is used for controlling the mechanical arm to contact an environment object along a force control direction and calculating the environment rigidity in the force control direction;
the force control parameter module is used for obtaining force control parameters according to the environmental rigidity;
and the controller correction module is used for outputting the force control parameters to a controller of the mechanical arm.
The invention provides a system for correcting parameters of a manipulator controller based on an impedance mode.
The invention provides a system for correcting parameters of a manipulator controller based on an impedance mode, wherein a manipulator is controlled to contact an environmental object along a force control direction, and the system comprises:
controlling the mechanical arm to move towards an environment object along a force control direction, and obtaining the data of a tail end sensor of the mechanical arm and the position movement data of a tool center point when the tool center point of the mechanical arm is in contact with the environment object and reaches stress balance;
obtaining the environmental stiffness based on the tip sensor data and the positional movement data of the tool center point.
In addition, the invention also provides a mechanical arm product which uses the method for correcting the mechanical arm controller based on the impedance mode or the system for correcting the mechanical arm controller based on the impedance mode.
The implementation of the invention has the following beneficial effects:
the invention can solve the problem of adjusting the force control parameters of the mechanical arm in different environments; the rigidity coefficient of the environment is obtained through calculation and is used for reflecting environment information, so that corresponding force control parameters are obtained to correct the controller, and the interaction capacity of the mechanical arm and the environment is improved.
Drawings
Fig. 1 is a flowchart of a method for modifying a robot controller based on an impedance mode according to an embodiment of the present invention.
FIG. 2 is a graph of z-direction force of a tool center point moving in the z-direction and contacting three different environments, with time dt on the horizontal axis and time dt on the vertical axis indicating the magnitude of the z-direction force.
FIG. 3 shows the stiffness K according to the environment1And (3) a curve linearly fitted with the mapping data of the force control parameter r.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention more comprehensible, embodiments accompanying figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.
It will be understood that when an element is referred to as being "secured to" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like are used herein for purposes of illustration only.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.
As shown in fig. 1, an embodiment of the present invention provides a method for modifying a parameter of a robot arm controller based on an impedance mode, including:
step S1, starting the impedance control mode, and setting the damping coefficient B, the mass m and the elastic coefficient K of the impedance controller in the impedance control mode0And a virtual friction force f1Constant impedance control parameter, in which the elastic coefficient K can be set0Is set to 0 (in other embodiments, the elastic coefficient K may be set0Other impedance control parameters can be set by a user or default by a system, or the user can also set the maximum contact force (so that the stress of the tail end of the mechanical arm is always smaller than the maximum contact force when the mechanical arm moves to the environment), the mechanical arm converts the maximum contact force into a resistance parameter, and the maximum force in the measurement process of the mechanical arm can be ensured to be always within the range of the sensor; in the impedance control mode, the flexibility of the mechanical arm (or the robot) can be kept, the mechanical arm (or the robot) is protected from large impact, and the mechanical arm (or the robot) is prevented from moving and being damaged in the environment; reasonable impedance control parameters are set in the embodiment, so that the mechanical arm is connected with the ringImpact damage is reduced during object contact.
Step S2, controlling the mechanical arm to move towards the environment object along the force control direction, and when the tool center point of the mechanical arm contacts with the environment object and reaches the stress balance, obtaining the terminal sensor data of the mechanical arm and the position movement data of the tool center point, wherein the stress balance refers to the balance between the acting force of the tool center point of the mechanical arm on the environment object and the reacting force of the environment object and the tool center point of the mechanical arm; obtaining an environmental stiffness K in the force control direction based on the end-point sensor data and the tool center point positional movement data, and the amount of environmental deformation in the force control direction1。
Since the velocity of the center point of the tool is kept constant v during the movement, the elastic coefficient K of the virtual spring is already set in step S10Set to 0 (to ensure that the maximum force is only related to the resistance parameters B and f)1Related to). Finally, after the central point of the tool is contacted with the environment, the motion command is counteracted with the motion generated by the impedance controller to reach balance, and the reading of the sensor is F ═ F at the moment1+ Bv, where B is the damping coefficient, f1Is the virtual friction. In the process, the environmental deformation is L and can be obtained through the position change of the central point of the tool, and the environmental rigidity K is1Can be approximately calculated as K1F/L (according to F. K)1L), where F is resistance sensor data, and the environmental deformation amount in the process is L, which can be obtained from the tool center point position variation data.
Fig. 2 is a graph showing z-direction force of a tool center point moving in the z direction and contacting three different environments, wherein the transverse coordinate axis is time, and the vertical coordinate axis marks the magnitude of the z-direction force. It can be seen that the variation for different environmental forces is greatest at contact, then decreases rapidly, and the resulting force tends to be constant, dt being affected by the environmental stiffness.
Step S3, according to the environmental rigidity K1Obtaining a force control parameter r;
and step S4, outputting the force control parameter r to a controller G (S) of the mechanical arm, and correcting the controller G (S) according to the force control parameter r. The correction function of the correction controller G '(s) is G'(s) ═ r G(s), so that the final output of the correction controller realizes the adjustment of the robot arm controller to adapt to various environments.
Alternatively, in step S3, the stiffness K is adjusted according to the environment1The force control parameter r can be obtained in various ways, including but not limited to the following ways:
(1) according to a preset environmental rigidity K1Determining a force control parameter r according to mapping data of the force control parameter r; the following table gives the environmental stiffness K of the environment in 51And the force control parameter r, usually calculated to obtain the environmental stiffness K1Then, if it is exactly one of the environmental stiffnesses K1High approximation, e.g. environmental stiffness K1Is 2.97 (in the mapping data, the environmental stiffness K1Without 2.97 data nodes) which are very close to 3, reference can be made to the use environment stiffness K1If the corresponding force control parameter r is 0.4, the system can simply determine that the corresponding force control parameter r is 0.4, and output r to 0.4 and G'(s) to r G(s);
(2) fitting a function r ═ H (K) according to a linear model1)＝a*K1+ b, determining a force control parameter r, wherein a and b are both correction coefficients of a fitting function; a. b can be a system preset value or a numerical value screened according to conditions; the mapping relationship provided in the manner (1) may be selected, for example, the calculation process according to the fitted curve shown in fig. 3 is as follows:
the example shows 5 environments, and the environmental rigidity K is measured by the method (1)11, 2, 3, 4 and 5, for each environment, manually adjusting the optimal control parameter coefficients to be 0.1, 0.3, 0.4, 0.5 and 0.7, and when the method is used by a user, firstly measuring the environmental stiffness system by using the methodFor example, if the measured value is 1.5, the system automatically performs linear interpolation according to the above table, and the algorithm automatically sets the controller parameter to (0.1+ 0.3)/2-0.2.
The values of a and b in each section can be fitted according to the data given above, (r, K)1) The coordinates of the two adjacent points can be calculated to obtain specific values of the correction parameters a and b of the connecting line between the two points, for example, at the given two points (1, 0.1), (2, 0.3), the correction parameter a of the corresponding interval can be obtained12、b12Can thus give the expression of the linear model fitting function r over the whole function interval:
r12＝H(K1)＝a12*K1+b12，(1≤K1≤2)；
r23＝H(K1)＝a23*K1+b23，(2≤K1≤3)；
r34＝H(K1)＝a34*K1+b34，(3≤K1≤4)；
r45＝H(K1)＝a45*K1+b45，(4≤K1≤5)。
(3) fitting a function r ═ W (K) according to a nonlinear model1) Usually r ═ W (K)1)＝d*K1 2+e*K1+ f, d, e, f is a function W (K)1) For the correction coefficient, the specific nonlinear model fitting function calculation may refer to the method (2), but the calculation process is slightly complicated and will not be described herein again.
(4) The neural network of the nonlinear model determines the force control parameter r, and usually needs to design a neural network model to perform calculation integration on data, and the neural network model can use the above linear and nonlinear models, and can also use other nonlinear models.
The embodiment of the invention also provides a system for correcting the parameters of the manipulator controller based on the impedance mode, which comprises an impedance control module, an environmental rigidity module, a force control parameter module and a controller correction module. Wherein:
impedance controlA module for starting the impedance control mode and setting the damping coefficient B, the mass m and the elastic coefficient K of the impedance controller in the impedance control mode0And a virtual frictional force f1Constant impedance control parameter, in which the elastic coefficient K can be set0Is set to 0 (the elastic coefficient K may be set in other embodiments0Other impedance control parameters can be set by a user or default by a system, or the user can set the maximum contact force (so that the tail end stress of the mechanical arm moving to the environment is always smaller than the maximum contact force), the mechanical arm converts the maximum contact force value into a resistance parameter, and the maximum force in the mechanical arm measuring process can be ensured to be always within the range of the sensor; in the impedance control mode, the flexibility of the mechanical arm (or the robot) can be kept, the mechanical arm (or the robot) is protected from large impact, and the mechanical arm (or the robot) is prevented from moving and being damaged in the environment; reasonable impedance control parameters are set in the embodiment, so that impact damage is reduced when the mechanical arm is in contact with an environmental object.
The system comprises an environment rigidity module, a force control module and a data processing module, wherein the environment rigidity module controls a mechanical arm to move towards an environment object along a force control direction, and when a tool center point of the mechanical arm is in contact with the environment object and reaches stress balance, the data of a tail end sensor of the mechanical arm and the position movement data of the tool center point are obtained, wherein the stress balance refers to the balance between the acting force of the tool center point of the mechanical arm on the environment object and the reacting force of the environment object and the tool center point of the mechanical arm; obtaining an environmental stiffness K in a force control direction based on the end-point sensor data and the tool center point position movement data, and the amount of environmental deformation in the force control direction1。
Since the velocity of the tool center point is kept constant v during the movement, the elastic coefficient K of the virtual spring is set in step S10Set to 0 (to ensure that the maximum force is only related to the resistance parameters B and f)1Related to). Finally, after the central point of the tool is contacted with the environment, the motion command is counteracted with the motion generated by the impedance controller, and the balance is achieved, wherein the reading of the sensor is F ═ F1+ Bv, where B is the damping coefficient, f1Is a virtual frictionForce. In the process, the environmental deformation is L and can be obtained through the position change of the central point of the tool, and the environmental rigidity K is1Can be approximately calculated as K1F/L (according to F. K)1L), where F is the resistance sensor data and L is the tool center point position movement data; the environmental deformation quantity in the process is L, and can be directly obtained from the position change data of the tool center point.
Fig. 2 is a graph showing the z-direction force of the tool center point moving along the z-direction and contacting three different environments, wherein the transverse coordinate axis is time, and the vertical coordinate axis marks the magnitude of the z-direction force. It can be seen that the variation for different environmental forces is greatest at contact, then decreases rapidly, and the resulting force tends to be constant, dt being affected by the environmental stiffness.
A force control parameter module for determining the environmental stiffness K1Obtaining a force control parameter r;
and the controller correction module is used for outputting the force control parameter r to a controller G(s) of the mechanical arm and correcting the controller G(s) according to the force control parameter r. The correction function of the correction controller G '(s) is G'(s) ═ r G(s), so that the final output of the correction controller realizes the adjustment of the robot arm controller to adapt to various environments.
Optionally, the force control parameter module is configured to control the force according to the environmental stiffness K1The force control parameter r can be obtained in various ways, including but not limited to the following ways:
(1) according to a predetermined environmental rigidity K1Determining a force control parameter r according to mapping data of the force control parameter r; the following table gives the environmental stiffness K of the environment in 51And the force control parameter r, usually by calculation to obtain the ambient stiffness K1Then, if it is exactly one of the environmental stiffnesses K1Highly approximated, e.g. ambient stiffness K1Is 2.97 (in the mapping data, the environmental stiffness K1Without 2.97 data nodes) which are very close to 3, reference can be made to the use environment stiffness K1If the force control parameter r is 3, the system can simply determine that the corresponding force control parameter r is 0.4, and output r is 0.4 to G '(G')s)＝r*G(s)；
| K1 | r |
| 1 | 0.1 |
| 2 | 0.3 |
| 3 | 0.4 |
| 4 | 0.5 |
| 5 | 0.7 |
(2) Fitting a function r ═ H (K) according to a linear model1)＝a*K1+ b, determining a force control parameter r, wherein a and b are both correction coefficients of a fitting function; a. b can be a system preset value or a numerical value screened according to conditions; the mapping relationship provided in the manner (1) may be selected, for example, the calculation process according to the fitted curve shown in fig. 3 is as follows:
the example shows 5 environments, and the environmental rigidity K is measured by the method (1)11, 2, 3, 4 and 5, for each environment, the optimal control parameter coefficients are manually adjusted to be 0.1, 0.3, 0.4, 0.5 and 0.7, when the system is used by a user, the system firstly measures the environmental stiffness coefficient by using the method, for example, if the measured value is 1.5, the system automatically carries out linear interpolation according to the table, and the algorithm automatically sets the controller parametersThe ratio of (0.1+0.3)/2 is 0.2.
The values of a and b in each interval can also be fitted according to the data given above, (r, K)1) The coordinates of the two adjacent points can be calculated to obtain specific values of the correction parameters a and b of the connecting line between the two points, for example, at the given two points (1, 0.1), (2, 0.3), the correction parameter a of the corresponding interval can be obtained12、b12Can thus give the expression of the linear model fitting function r over the whole function interval:
r12＝H(K1)＝a12*K1+b12，(1≤K1≤2)；
r23＝H(K1)＝a23*K1+b23，(2≤K1≤3)；
r34＝H(K1)＝a34*K1+b34，(3≤K1≤4)；
r45＝H(K1)＝a45*K1+b45，(4≤K1≤5)。
(3) fitting a function r ═ W (K) according to a nonlinear model1) Typically r ═ W (K)1)＝d*K1 2+e*K1+ f, d, e, f is a function W (K)1) For the correction coefficient, the specific nonlinear model fitting function calculation may refer to the method (2), but the calculation process is slightly complicated and will not be described herein again.
(4) The neural network of the nonlinear model determines the force control parameter r, and usually a neural network model needs to be designed to calculate and integrate data, and the neural network model can use the above linear and nonlinear models, and can also use other nonlinear models.
As shown in fig. 1, an embodiment of the present invention provides a method for measuring environmental stiffness based on an impedance mode, including:
step S1, starting the impedance control mode, and setting the damping coefficient B, the mass m and the elastic coefficient K of the impedance controller in the impedance control mode0And a virtual frictional force f1Isoimpedance control parameter ofThe elastic coefficient K can be adjusted0Is set to 0 (in other embodiments, the elastic coefficient K may be set0Other impedance control parameters can be set by a user or default by a system, or the user can also set the maximum contact force (so that the stress of the tail end of the mechanical arm is always smaller than the maximum contact force when the mechanical arm moves to the environment), the mechanical arm converts the maximum contact force into a resistance parameter, and the maximum force in the measurement process of the mechanical arm can be ensured to be always within the range of the sensor; in the impedance control mode, the flexibility of the mechanical arm (or the robot) can be kept, the mechanical arm (or the robot) is protected from large impact, and the mechanical arm (or the robot) is prevented from moving and being damaged in the environment; reasonable impedance control parameters are set in the embodiment, so that impact damage is reduced when the mechanical arm is in contact with an environmental object.
Step S2, controlling the mechanical arm to move towards the environment object along the force control direction, and when the tool center point of the mechanical arm contacts with the environment object and reaches the stress balance, obtaining the terminal sensor data of the mechanical arm and the position movement data of the tool center point, wherein the stress balance refers to the balance between the acting force of the tool center point of the mechanical arm on the environment object and the reacting force of the environment object and the tool center point of the mechanical arm; obtaining an environmental stiffness K in a force control direction based on the end-point sensor data and the tool center point position movement data, and the amount of environmental deformation in the force control direction1。
Since the velocity v of the tool center point is kept constant during the movement, the elastic coefficient K of the virtual spring is already set in step S10Set to 0 (to ensure that the maximum force is only related to the resistance parameters B and f)1Related to). Finally, after the central point of the tool is contacted with the environment, the motion command is counteracted with the motion generated by the impedance controller, and the balance is achieved, wherein the reading of the sensor is F ═ F1+ Bv, where B is the damping coefficient, f1Is the virtual friction. In the process, the environmental deformation is L and can be obtained through the position change of the central point of the tool, and the environmental rigidity K is1Can be approximately calculated as K1F/L (according to F. K)1L), where F is resistance sensor data, this processThe environment deformation is L, which can be obtained by the tool center point position variation data.
Fig. 2 is a graph showing z-direction force of a tool center point moving in the z direction and contacting three different environments, wherein the transverse coordinate axis is time, and the vertical coordinate axis marks the magnitude of the z-direction force. It can be seen that the variation for different environmental forces is greatest at contact, then decreases rapidly, and the resulting force tends to be constant, dt being affected by the environmental stiffness.
The embodiment of the invention also provides a system for measuring the environmental rigidity based on the impedance mode, which comprises an impedance control module and an environmental rigidity module. Wherein:
an impedance control module for starting an impedance control mode and setting a damping coefficient B, a mass m and an elastic coefficient K of an impedance controller of the impedance control mode in the impedance control mode0And a virtual frictional force f1Constant impedance control parameter, in which the elastic coefficient K can be set0Is set to 0 (in other embodiments, the elastic coefficient K may be set0Other impedance control parameters can be set by a user or default by a system, or the user can also set the maximum contact force (so that the stress of the tail end of the mechanical arm is always smaller than the maximum contact force when the mechanical arm moves to the environment), the mechanical arm converts the maximum contact force into a resistance parameter, and the maximum force in the measurement process of the mechanical arm can be ensured to be always within the range of the sensor; in the impedance control mode, the flexibility of the mechanical arm (or the robot) can be kept, the mechanical arm (or the robot) is protected from large impact, and the mechanical arm (or the robot) is prevented from moving and being damaged in the environment; reasonable impedance control parameters are set in the embodiment, so that impact damage is reduced when the mechanical arm is in contact with an environmental object.
And the environment rigidity module is used for controlling the mechanical arm to move towards an environment object along the force control direction, and when the tool center point of the mechanical arm is in contact with the environment object and reaches stress balance, acquiring the data of a tail end sensor of the mechanical arm and the position movement data of the tool center point, wherein the stress balance refers to the acting force of the tool center point of the mechanical arm on the environment object, the environment object and the tool center of the mechanical armThe reaction forces of the points are balanced; obtaining an environmental stiffness K in a force control direction based on the end-point sensor data and the tool center point position movement data, and the amount of environmental deformation in the force control direction1。
Since the speed v of the tool center point is kept constant during the movement, the elastic coefficient K of the virtual spring is already set in step S10Set to 0 (to ensure that the maximum force is only related to the resistance parameters B and f)1Related to). Finally, after the central point of the tool is contacted with the environment, the motion command is counteracted with the motion generated by the impedance controller to reach balance, and the reading of the sensor is F ═ F at the moment1+ Bv, where B is the damping coefficient, f1Is the virtual friction. In the process, the environmental deformation is L and can be obtained through the position change of the central point of the tool, and the environmental rigidity K is1Can be approximately calculated as K1F/L (according to F. K)1L), where F is the resistance sensor data and L is the tool center point position movement data; the environmental deformation quantity in the process is L, and can be directly obtained from the position change data of the tool center point.
Fig. 2 is a graph showing the z-direction force of the tool center point moving along the z-direction and contacting three different environments, wherein the transverse coordinate axis is time, and the vertical coordinate axis marks the magnitude of the z-direction force. It can be seen that the variation for different environmental forces is greatest at contact, then decreases rapidly, and the resulting force tends to be constant, dt being affected by the environmental stiffness.
In addition, embodiments of the present invention also provide a robot arm product, where the robot arm product uses the method for correcting parameters of a robot arm controller based on an impedance mode provided in the above embodiments, or the above system for correcting parameters of a robot arm controller based on an impedance mode, or the above method for measuring environmental rigidity based on an impedance mode, or the above system for measuring environmental rigidity based on an impedance mode.
The invention can solve the problem of adjusting the force control parameters in different environments; the rigidity coefficient of the environment is obtained through calculation and is used for reflecting environment information, so that corresponding force control parameters are obtained to correct the controller, and the interaction capacity of the mechanical arm and the environment is improved.
All possible combinations of the technical features in the above embodiments may not be described for the sake of brevity, but should be considered as being within the scope of the present disclosure as long as there is no contradiction between the combinations of the technical features.
The above examples only show some embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that various changes and modifications can be made by those skilled in the art without departing from the spirit of the invention, and these changes and modifications are all within the scope of the invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for modifying a parameter of a robot arm controller based on an impedance model, comprising:
step S1, obtaining impedance control parameters;
step S2, controlling the mechanical arm to contact an environmental object along a force control direction, and calculating the environmental rigidity in the force control direction;
step S3, obtaining force control parameters according to the environmental rigidity;
and step S4, outputting the force control parameters to a controller of the mechanical arm.
2. The method of claim 1,
in step S1, the impedance control parameter includes one or more of an elastic coefficient, a damping coefficient, a mass, and a virtual friction.
3. The method of claim 1,
in step S2, the calculating the environmental stiffness in the force control direction includes:
and calculating the environmental rigidity of the force control direction based on the tail end moment sensor or the joint moment sensor and the environmental deformation amount in the force control direction.
4. The method of claim 3,
in step S2, controlling the robotic arm to contact the environmental object along the force control direction includes:
controlling the mechanical arm to move towards an environment object along a force control direction, and obtaining the data of a tail end sensor of the mechanical arm and the position movement data of a tool center point when the tool center point of the mechanical arm is in contact with the environment object and reaches stress balance;
obtaining the environmental stiffness based on the tip sensor data and the tool center point positional movement data.
5. The method of claim 1,
in step S3, obtaining a force control parameter according to the environmental stiffness includes:
determining the force control parameters according to mapping data from preset environmental rigidity to the force control parameters; and/or the presence of a gas in the gas,
determining the force control parameters according to a linear model fitting function related to the environmental rigidity; and/or the presence of a gas in the gas,
determining the force control parameters according to a nonlinear model fitting function related to the environmental rigidity; and/or the presence of a gas in the gas,
force control parameters are determined from a neural network of a non-linear model related to the stiffness of the environment.
6. The method of claim 5,
in step S3, the method further includes: and fitting the mapping data through the linear model fitting function or the nonlinear model fitting function to determine the force control parameters.
7. A system for modifying a parameter of a robot arm controller based on an impedance model, comprising:
the impedance control module is used for obtaining impedance control parameters;
the environment rigidity module is used for controlling the mechanical arm to contact an environment object along a force control direction and calculating the environment rigidity in the force control direction;
the force control parameter module is used for obtaining force control parameters according to the environmental rigidity;
and the controller correction module is used for outputting the force control parameters to a controller of the mechanical arm.
8. The system of claim 7,
in the impedance control module, the impedance control parameters include one or more of an elastic coefficient, a damping coefficient, a mass, and a virtual friction.
9. The system of claim 7,
the control arm contacts environmental object along the direction of power accuse, includes:
controlling the mechanical arm to move towards an environment object along a force control direction, and obtaining the data of a tail end sensor of the mechanical arm and the position movement data of a tool central point when the tool central point of the mechanical arm is in contact with the environment object and reaches stress balance;
obtaining the environmental stiffness based on the tip sensor data and the positional movement data of the tool center point.
10. A robot arm product, characterized in that the robot arm product uses the method for correcting parameters of a robot arm controller based on impedance patterns according to any one of claims 1 to 6, or the system for correcting parameters of a robot arm controller based on impedance patterns according to any one of claims 7 to 9.
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