CN116652939A - Calibration-free visual servo compliant control method for parallel robot - Google Patents
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
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Abstract
The invention discloses a calibration-free visual servo compliant control method for parallel robots, and belongs to the technical field of robot control. The vibration phenomenon is easy to occur under the working condition of high load, the relative position relation between the platform and the camera is influenced, the camera calibration result is greatly influenced by illumination conditions, and the platform is driven to move by adopting a servo control mode that the camera is not calibrated. Based on nonlinear objective function minimization theory, obtaining the length iteration type of the platform support rod, and adopting a dynamic quasi-Newton method to estimate the image jacobian matrix on line to perform the non-calibration visual servo control of the platform. The visual servo completes the navigation control of the platform, the force control adjusts the pose of the platform, a visual-force fusion control method is provided, the visual servo control and the force control are simultaneously acted in the motion control, the motion performance of the platform is optimized, the robustness and autonomy of the visual navigation control are enhanced, and meanwhile, the flexible butt joint operation requirement required by industrial intelligence is also realized.
Description
Technical Field
The invention relates to the technical field of robot control, in particular to a calibration-free visual servo compliant control method for parallel robots.
Background
In recent years, with the continuous advancement of industry 4.0, the field of China industry has been vigorously developed. While industrial development has promoted technological innovation, the state of the art day-to-day variation has also pushed industrial development to higher steps. The robot technology with wide application scenes is greatly advanced in the trend of industrial development, and the practicability and the precision of the robot technology are greatly improved.
In the present robot assembly research, force control is one of the most widely applied control methods, impedance control is one of the robot force control methods, has the effect of conforming to external force, and can improve the compliance of the robot with environment interaction by constructing impedance dynamics between interaction force and position tracking error, so that the robot can avoid rigid collision in complex working conditions, and therefore, many students are researching on the impedance control. For impedance control, the required impedance dynamics are typically described by linear spring damping dynamics and are achieved by the impedance error being close to zero. To date, many impedance controllers have been proposed and applied to robots to improve interactive compliance. However, the force control approach has limitations in the assembly process.
The existing assembly mode is to use a six-axis force sensor at the tail end of the mechanical arm for assembly, and directly monitor the contact state between a workpiece and a base according to the force value measured by the six-axis force sensor. Impedance control of the manipulator may be achieved by a relationship between the desired pose error and the contact force, and then controlling the force by displacement or velocity of the end effector based on the desired reference trajectory. The method has good adaptability and robustness to the measurement of the force sensor and various interferences and uncertainties generated in the assembly process, but the impedance control is used for a plurality of parameters which are difficult to determine in the assembly process, so that the position and the force cannot be controlled accurately.
For complex assembly contact environments, force control is initially combined with a contact state model. For example, a Lagrangian impact model is used to derive a general form of an impact equation for an industrial robot to perform a shaft hole assembly process. For example, the relationship between the force of the workpiece and the base and the geometric constraint during single hole assembly is illustrated by creating a static geometric model. The disadvantages of such methods are also apparent, not having a model build suitable for a simple arbitrary environment. Moreover, the variables of the analytical model can only be determined from the observed contact states and known state transitions, and not all occurrences in the assembly process can be completely simulated. For some large parameters, the manual modeling is very complex.
Disclosure of Invention
In view of the above, the invention provides a calibration-free visual servo compliant control method for parallel robots, which is used for adding autonomy of a control system, realizing the improvement of control precision of the Stewart parallel robots and further completing the assembly task of the robots.
For this purpose, the invention provides the following technical scheme:
the invention provides a calibration-free visual servo compliant control method for a parallel robot, which comprises the following steps:
giving expected information;
acquiring image information in real time, performing image processing on the image information, and extracting feature point information;
according to the characteristic point information, performing calibration-free visual servo control on the parallel robot;
judging whether the pixel difference of the characteristic points exceeds a set value when the parallel robot enters a set target position range, and if so, performing virtual force-visual control to enable the parallel robot to displace under the action of the virtual force;
judging whether the parallel robot reaches the target position, and if not, returning to the step of giving the expected information.
Further, the image processing includes:
converting an RGB image acquired from a camera into an HSV image space;
carrying out morphological filtering operation on the image by adopting Gaussian filtering;
graying the image, and extracting a target contour from the gray image;
and after extracting the outline information of the target object, acquiring coordinate information of four characteristic points of the target object.
Further, the calibration-free visual servo control is performed on the parallel robot, including:
defining two independent variable model functions of the length value and the time of the hydraulic cylinder in the control process;
fitting the length value and time of the hydraulic cylinder in the control process by using a nonlinear regression mathematical tool through a successive approximation method to obtain a platform hydraulic support leg length change iterative update formula;
estimating the partial conductance of the length of the hydraulic support leg of the platform by using an image jacobian matrix in an iterative updating formula of the length change of the hydraulic support leg of the platform;
estimating a jacobian matrix by using a dynamic quasi-Newton method, and deducing an image jacobian updating iterative formula;
substituting the image jacobian updating formula into the platform hydraulic support leg length change iterative updating formula to perform calibration-free servo control.
Further, virtual force-visual control, comprising:
carrying out inverse kinematics solution on the parallel robot, and designing an impedance control system;
based on the impedance control system, a camera pixel coordinate system is established, and a distribution diagram of a platform support rod and a movable platform connection point is determined by marking the platform support rod;
determining the application position of the virtual force and the magnitude of the virtual force;
virtual force is applied to the virtual force applying position of the parallel robot, so that virtual force-visual control of the parallel robot is realized.
Further, an impedance control system is designed, comprising:
determining a world coordinate system according to the position of the fixed platform of the parallel robot, and determining a dynamic coordinate system according to the position of the dynamic platform of the parallel robot;
according to the relationship between the current position and the world coordinate system established by the parallel robot and the dynamic coordinate system, the kinematic inverse solution of the parallel robot is solved;
and defining an impedance model, and solving the impedance model by combining the kinematic inverse solution to obtain the impedance control system.
The invention has the advantages and positive effects that:
aiming at the problems of poor visibility and low control precision of the traditional robot control method, the invention combines the provided visual servo without calibration with the admittance control strategy, and provides a visual-force combined control method. In the visual control process, the invention uses impedance control to continuously adjust the gesture between the workpieces to be assembled, thereby avoiding huge contact force possibly occurring in the assembly process. The initiation of the impedance control requires a force, so that the force for driving the impedance control needs to be virtualized, and the virtual force is designed to act as an external force on the platform, so that the pose of the platform vision servo control is adjusted, and a platform vision-virtual force combined control strategy is formed. Compared to existing robotic assembly control strategies that simply combine visual control and force control in a hierarchical sequential control (e.g., bdipi, mohama et al propose a new robotic system that combines visual servoing and force control to transfer a model-free object from undefined places to a human hand, fusion visual control and force control reasons are to ensure safety during human-to-robot interaction. Zhang Yanxia et al propose a robot vision-force fusion control scheme that works in a rigid environment to achieve compliant contact of the robot with a workpiece, a second control mode is an interactive control mode of visual control and force control (e.g., wang, heseng et al propose a hybrid visual force controller that is based on a deformation model that describes deformation and configuration of a soft robot under the action of gravity and force applied to a tip, describes the actual relationship of driving and tip motion by computing the jacobian of the soft robot, and then utilizes visual servoing and force feedback to achieve motion-free spatial force control of the robot, hu Ruiqin. A hybrid visual force controller is first provided with a visual force control system that does not have a motion constraint space, and a visual force control system is not optimized by the human motion control system, and a visual force control system is first provided by combining visual force control system with a visual force control system to the motion control platform, and a visual force control system is not optimized by the human motion control system, and the motion control system is first provided by the invention, and the visual force control system is not optimized by the human motion control platform is equipped with a visual force control system that is based on the visual force control system, meanwhile, the flexible butt joint operation requirement required by industrial intelligence is also realized.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive effort to a person skilled in the art.
FIG. 1 is a schematic diagram of a dynamic and static platform coordinate system in an embodiment of the invention;
FIG. 2 is a schematic diagram illustrating the installation of a mobile platform camera according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a spatial coordinate system of a camera pixel according to an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating the distribution of the connection points between the platform strut and the movable platform in an embodiment of the present invention;
FIG. 5 is a flow chart of a method for non-calibrated visual servo compliance control of a parallel robot in an embodiment of the invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The robot vision servo is a robot application technology which rapidly develops in recent years, takes a place in the field of robot application with excellent control performance, takes a camera as a sensor for acquiring an image, processes the acquired image to obtain image characteristic information, can establish a corresponding functional relation between the image characteristic information and the robot kinematics, and can realize the motion control of the robot according to the functional relation. The navigation control of the Stewart parallel robot is realized through visual servo control, and the autonomy of a control system is increased. However, in the field of assembly, visual servo control cannot avoid the damage of the workpiece to be assembled due to assembly failure caused by huge contact force generated when two objects are contacted. In order to improve the efficiency and the precision of the visual servo control of the robot, the invention provides a method for combining the visual servo control and the force control, so that the control precision of the Stewart parallel robot is improved, and the robot assembly task is further completed.
The invention aims to provide a visual servo compliance control method without calibration for a parallel robot, wherein the positioning accuracy of the visual servo control based on the position in the visual servo control of the robot is greatly dependent on the estimation accuracy of the target pose and is sensitive to image characteristic quantization errors, camera calibration errors and image noise, so that the visual servo control method based on the image is selected and used, and a visual servo control method without calibration for a Stewart platform camera is provided. An image processing section for identifying a target object by using a color space conversion method; the point features are selected as the image feature information, so that the calculated amount is reduced. The platform vision-force combination control part combines the vision servo control and the impedance control according to the error of the pixel value of the image characteristic point in the vision servo control and the advantage that the impedance control can effectively avoid the system oscillation, and provides a Stewart platform vision-virtual force combination motion control strategy to realize the platform compliant docking control function.
As shown in fig. 5, the embodiment of the invention provides a vision-force fusion control method of a parallel robot (Stewart platform), which comprises the following specific steps:
s10, the camera acquires image information in real time, and characteristic point information is extracted after image processing.
The method comprises the following specific steps:
s101, converting RGB images acquired from a camera into HSV image space;
s102, performing morphological filtering operation on the image by adopting Gaussian filtering;
s103, graying the image, and extracting a target contour from the gray image;
and S104, after the contour information of the target object is successfully extracted, acquiring the coordinate information of four characteristic points of the target object.
S20: and designing a visual servo control method without calibration according to the extracted characteristic point information.
The method comprises the following specific steps:
s201: and defining two independent variable model functions of the length value and the time of the hydraulic cylinder in the control process.
Defining characteristic point information on an image plane as f (l, t), setting hydraulic cylinder length as l and time as t, and setting expected characteristic point information f * The difference between the two needs to be minimized in the control process, and the formula is as follows:
e(l,t)＝f(l,t)-f * (1)
s202: and fitting the length value and time of the hydraulic cylinder in the control process by using a nonlinear regression mathematical tool through a successive approximation method, so as to obtain a platform hydraulic support leg length change iterative update formula.
Fitting the data by a successive approximation method, defining a nonlinear objective function:
the hypothesis model can be approximated by a linear function, developed with first order Taylor series:
since the camera collects image information according to a fixed frequency, the partial derivative of F (l, t) with respect to time t is zero, and the partial derivative of F (l, t) with respect to the cylinder length l is a minimum value:
discretization can be achieved:
the following definitions are made and sorted for equation (5):
the iterative updating formula of the length change of the hydraulic landing leg of the platform can be obtained:
description will be given of the formula (6): in the middle ofThe partial derivative of the image characteristic value with respect to time represents the speed change of the target object, and the value can be ignored when the position of the target object is not changed.
And (3) making:
the finishing method can obtain:
substituting equation (8) into equation (7) yields:
the formula (6) can be arranged as follows:
platform landing leg length iterative formula based on nonlinear regression theory needs to be obtainedTo be further processed, firstly, the bias guide R of the image jacobian matrix to the length of the hydraulic support leg of the platform is adopted k (e.g., S203), followed by an estimation in which the image jacobian (e.g., S204).
S203: and estimating the partial derivatives of the length of the hydraulic support legs of the platform by using the image jacobian matrix in the iterative updating formula of the length change of the hydraulic support legs of the platform.
Partial guide of image jacobian matrix on length of hydraulic landing leg of platform
If the difference function e (l, t) is small in the initial state, R is k Can be ignored. When R is k A value greater thanAt the time, R cannot be ignored k It is necessary to R k The value is estimated:
according to R k Definition:
and (3) finishing and simplifying:
s204: estimating the jacobian matrix by using a dynamic quasi-Newton method, and deducing an image jacobian updating iteration formula.
For the function e (l, t) defined by equation (1), the radiation model of its first order Taylor series expansion is defined as y (l, t), which can be obtained:
for time k-1:
subtracting the two formulas, and finishing to obtain:
definition of formula (15): Δj=j k -J k-1
Δl＝l k -l k-1
Δt＝t k -t k-1
Δe＝e k -e k-1
And (3) finishing a formula (15), and obtaining the two-side device:
solving for a minimum norm solution of the solution (16):
because the iterative relation of the formula (17) can generate a divergence phenomenon, the system oscillation is reduced to maintain the stability of the system by adopting a form of minimum residual square sum.
Defining a forgetting factor as lambda, and a cost function as:
minimizing this, the image jacobian update iteration formula can be obtained:
P k is a state estimation error variance matrix, the initial value of which is P 0 ＝10 5 I, I is the identity matrix.
S30, deducing the corresponding relation between the pose of the platform and the length of the platform rod, and designing an impedance control system by using the relation.
The method comprises the following specific steps:
s301: and determining a world coordinate system according to the position of the robot fixed platform, and determining a dynamic coordinate system according to the position of the robot dynamic platform.
As shown in fig. 1, the world coordinate system W is fixed on the base, and the coordinate system P is fixed at the reference point P 0 On a mobile platform.
S302: and solving the inverse solution of the kinematics of the platform according to the current position established by the platform, the world coordinate system and the dynamic coordinate system.
The position of the coordinate system P relative to the coordinate system W is defined by the vector x= (X, Y, Z) T The position coordinates of the point with respect to the coordinate system W are specified, i.e. given. The pose of the coordinate system P relative to the coordinate system W is determined by a rotation matrix W R P ＝(r 1 ,r 2 ,r 3 ) Description.
A generalized coordinate vector q is defined to describe the pose of the platform:definition vector l= (l) 1 ,l 2 ,l 3 ,l 4 ,l 5 ,l 6 ) T Wherein l i (i=1, 2, ·, 6) is the length of six struts of a Stewart six-degree-of-freedom parallel platform.
Adopts the rotation sequence of ZXZ Euler angles, and the sizes of the rotation angles are as followsThe correspondence relationship between the dynamic coordinate system P and the world coordinate system W is obtained as follows:
where c and s represent cosine cos and sine sin.
Defining the world coordinate system W the angular velocity ω= (ω) X ,ω Y ,ω Z ) T Obtaining:
known connection point a i The coordinates in the moving platform coordinate system are P a i The connection point a under the world coordinate system can be obtained by combining the formula (20) i Coordinates:
a i ＝x+ W R p P a i (22)
vector L of platform strut i i Obtaining:
L i ＝a i -b i (23)
wherein b i Representing the coordinates of the stationary platform connection point in the world coordinate system W.
Length l of platform strut i i The method comprises the following steps:
equation (22) differentiates over time t:
obtaining the elongation value of the ith support rod according to the projection of the speed vector on the joint axis of the ith support rod:
written in the form of a matrix:
wherein:
substituting (21) into (27):
wherein:
s303: and defining an impedance model, and solving the impedance model by combining the kinematic inverse solution of the steps.
The impedance system is a spring (K) -damping (B) -mass (M) system, and the mathematical expression in the time domain is:
wherein: m, B, K are respectively representations of the inertial, damping and stiffness effects on the system, F d 、F c Is the expected stress and the actual stress of the Stewart platform strut, x and x d The actual position and the expected position of the movable platform end of the Stewart platform are respectively, so the position deviation of the movable platform end is x-x d The speed deviation isThe acceleration deviation of the end is +.>
Impedance controllers are available:
X(s)-X r (s)＝Y(s)ΔF(s) (30)
natural frequency W of impedance controller m Damping ratio ζ, gain Z:
translational acceleration of the platform tip at time tAnd Euler angular acceleration->Solving:
wherein:Δx＝x-x d ,/>Δw＝w-w d ,ΔF＝F d -F c
the acceleration value and the Euler angle acceleration value of the tail end of the movable platform at the time t are respectively as follows:
substituting equations (35) and (36) into (27) yields the joint velocity at time t:
combining (24) to obtain the length value l of the platform strut i i The method comprises the following steps:
l i and (t) is the final control quantity of the Stewart platform impedance control.
S40: and the motion control of the Stewart platform is realized by combining the visual servo of the platform with the force control of the platform by utilizing a fusion control rule.
The two objects do not come into contact when they do not reach the assembly area. The premise of adjusting the posture of the platform visual servo control by starting the impedance control is that the force is applied to the platform, so that the force for driving the impedance control is needed to be virtualized, the virtual force is designed to act as an external force on the platform, the posture of the platform visual servo control is continuously adjusted, and the final assembly process is completed. The control effect of the Stewart stage impedance control is determined by the force applied to the stage, and thus it is necessary to determine the virtual force and determine the application position of the virtual force.
Based on working conditions faced by the Stewart platform, the influence of large contact force change and vibration of the platform on the motion control of the platform is avoided, and an impedance control method is adopted for force control. It is necessary to build an impedance control system. The premise of adjusting the posture of the platform visual servo control by starting the impedance control is that force is applied to the platform, so that the force for driving the impedance control is needed to be virtualized, the virtual force is designed to act as an external force on the platform, and the posture of the platform visual servo control is adjusted.
The method comprises the following specific steps:
s401: and establishing a camera pixel coordinate system, marking the platform support rod, and determining a distribution diagram of the connection point of the platform support rod and the movable platform.
As shown in fig. 2, the camera is fixedly installed on the movable platform. Fig. 3 shows a camera pixel space, four red points are given expected image feature points, four A, B, C, D points are real-time image feature points, an O point is a center point of a rectangle surrounded by the image feature points, and a coordinate origin of the pixel space is a lower left corner. Fig. 4 is a distribution diagram of connection points of the platform support rod and the movable platform, and the relative position relationship between the camera and the movable platform is fixed, that is, the relative position relationship between the pixel space of the camera and the movable platform is fixed, so that the corresponding relationship exists between the pixel space and the six support rods of the platform at the hinge point position on the movable platform, and the quadrant distribution of the single image feature point in fig. 4 can be determined.
S402: the application location of the virtual force is determined.
And marking the point of which the pixel value of the image characteristic point does not reach the set error requirement as an E point:
1. according to the abscissa value of the center point O of the rectangular outline of the target image, whether the point E is positioned in the II and III intervals or the I and IV intervals in the pixel coordinate system can be determined;
2. if the point E is in the II and III interval, the ordinate of the point E and the ordinate of the contour center point are differed, and whether the absolute value of the difference is in a set range is judged;
3. if the virtual force point is within the set range, setting the virtual force point on the No. 5 supporting rod; if the difference is not in the setting range, the action point of the pseudo force is set on the No. 6 support rod, and if the difference is negative, the action point of the pseudo force is set on the No. 4 support rod. And judging the same as the I and IV intervals.
S403: the magnitude of the virtual force is determined.
Defining the absolute value of the maximum error value of the pixel coordinates of the image feature points as X, wherein the applied force is F, and the image feature errors are real-time:
w i ＝UV i -UV 0i (i＝1,2,…,8) (39)
wherein: i represents 4 abscissa values and 4 ordinate values of pixel coordinates of 4 image feature points, UV i UV for real-time data 0i Is the desired data.
Virtual force can be obtained:
s404: and a visual servo and impedance control mode is designed to realize motion control of the platform.
Defining a control function of a visual servo control method of the Stewart platform based on the image as L i (u, v) the control function of the impedance control method is L Z (F) A. The invention relates to a method for producing a fibre-reinforced plastic composite The two control methods are combined to control the movement of the platform, so that the compliant butt joint control function of the platform is realized. The value of the image characteristic point of the platform in the state does not meet the control requirement, and the visual servo control function L based on the image i (u, v) stopping control of the motion of the platform, starting impedance control to adjust the pose of the platform, and after determining the position of the strut applying the force and acting the force, impedance control function L Z (F) Executing the control task of the platform, and starting the judging condition again by the control strategy to detect and judge the current pose until the error value is over in the set range.
In the embodiment, aiming at the problems of poor visibility and low control precision of a single control mode of the traditional robot control method, the provided calibration-free visual servo and admittance control strategy is combined, the visual-force combined control method is provided, the motion performance of a platform is optimized, the robustness and autonomy of visual navigation control are enhanced, and meanwhile, the flexible butt joint operation requirement required by industrial intelligence is also realized.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (5)
1. A calibration-free visual servo compliant control method for a parallel robot is characterized by comprising the following steps:
giving expected information;
acquiring image information in real time, performing image processing on the image information, and extracting feature point information;
according to the characteristic point information, carrying out calibration-free visual servo control on the parallel robot;
the parallel robot enters a set target position range, whether the pixel difference of the characteristic points exceeds a set value is judged, and if so, virtual force-visual control is performed to enable the parallel robot to displace under the action of virtual force;
and judging whether the parallel robot reaches a target position, and if not, returning to the step of giving expected information.
2. The parallel robot non-calibrated visual servo compliance control method of claim 1, wherein the image processing comprises:
converting an RGB image acquired from a camera into an HSV image space;
carrying out morphological filtering operation on the image by adopting Gaussian filtering;
graying the image, and extracting a target contour from the gray image;
and after extracting the outline information of the target object, acquiring coordinate information of four characteristic points of the target object.
3. The method for non-calibrated visual servo compliance control of a parallel robot according to claim 1, wherein the performing the non-calibrated visual servo control of the parallel robot comprises:
defining two independent variable model functions of the length value and the time of the hydraulic cylinder in the control process;
fitting the length value and time of the hydraulic cylinder in the control process by using a nonlinear regression mathematical tool through a successive approximation method to obtain a platform hydraulic support leg length change iterative update formula;
estimating the partial conductance of the length of the hydraulic landing leg of the platform by using an image jacobian matrix in the iterative updating formula of the length change of the hydraulic landing leg of the platform;
estimating a jacobian matrix by using a dynamic quasi-Newton method, and deducing an image jacobian updating iterative formula;
substituting the image jacobian updating formula into the platform hydraulic support leg length change iterative updating formula to perform calibration-free servo control.
4. The parallel robot non-calibrated visual servo compliance control method of claim 1, wherein the virtual force-visual control comprises:
performing inverse kinematics solution on the parallel robot, and designing an impedance control system;
based on the impedance control system, a camera pixel coordinate system is established, and a distribution diagram of a platform support rod and a movable platform connection point is determined by marking the platform support rod;
determining the application position of the virtual force and the magnitude of the virtual force;
and applying virtual force to the application position of the virtual force by the parallel robot, so as to realize virtual force-visual control of the parallel robot.
5. The method for non-calibrated visual servoing compliance control of a parallel robot of claim 4, wherein said designing an impedance control system comprises:
determining a world coordinate system according to the position of the parallel robot fixed platform, and determining a dynamic coordinate system according to the position of the parallel robot dynamic platform;
according to the relationship between the current position and the world coordinate system established by the parallel robot and the dynamic coordinate system, carrying out kinematic inverse solution on the parallel robot;
and defining an impedance model, and solving the impedance model by combining the kinematic inverse solution to obtain an impedance control system.
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| CN116911079B (en) * | 2023-09-13 | 2024-02-09 | 江苏云幕智造科技有限公司 | Self-evolution modeling method and system for incomplete model |
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