CN107414834A - A kind of multirobot cooperative system Static stiffness real-time performance evaluation method - Google Patents

Abstract

The invention provides a method for evaluating the stiffness performance of a multi-robot collaborative system without additional devices. Based on the transfer matrix of robot kinematics and the stiffness matrix of the robot end operation, the joint stiffness identification scheme of the robot is established and implemented to obtain accurate actual joint stiffness of the robot. The robot system software is used to feed back the real-time joint angles to construct the robot Jacobian matrix, and the overall stiffness matrix of the multi-robot collaborative system is formed through the Jacobian matrix and the joint stiffness parameters identified by the robot. The real-time stiffness of the robot is visualized through the robot stiffness matrix ellipsoid, and the maximum value of the eigenvalue of the system stiffness matrix is selected as the evaluation index to evaluate the robot stiffness. Finally, a visual interface for stiffness performance evaluation based on the dual KUKA KR_16 robot collaborative system is designed through the GUI design interface.

Description

A real-time performance evaluation method for static stiffness of a multi-robot collaborative system

technical field

The invention belongs to the technical field of robot processing applications, and relates to an application technology for static stiffness performance evaluation of an industrial robot system, in particular to a method for evaluating the overall function of a robot system aimed at improving the processing accuracy of a multi-robot collaborative system.

Background technique

With the transformation of the manufacturing industry to "intelligence" and "collaboration", the autonomous production mode in which multiple robots cooperate with each other will be more widely used. Under the high-efficiency and high-precision production requirements, an important difficulty faced by the current multi-robot collaborative operation system is how to improve the machining accuracy. Stiffness is the main factor affecting the positional accuracy and dynamic performance of the robot. When performing more complex tasks, better stiffness is needed to improve the overall stability of the multi-robot system, thereby improving the machining accuracy of the robot. According to the research status of stiffness, the stiffness evaluation of robot stiffness machining attitude can effectively solve the problem of low precision caused by machining attitude. At present, the mainstream method of improving robot stiffness is to reduce the processing error caused by robot joint flexibility through a special stiffness enhancement device. Such methods require a special joint stiffness adjustment design for the robot, which increases the difficulty of robot design and limits the versatility of industrial robot applications. The other is to clamp and position the workpiece through special fixtures to reduce the limitation of the original error of the device on the machining accuracy. However, this method requires a special fixture for each workpiece, and its high cost brings great trouble to industrial production.

Therefore, for the existing multi-robot application technology, it is of great significance to propose a reasonable robot stiffness performance evaluation method to improve the machining accuracy of the robot and improve the versatility of industrial robots in processing.

Contents of the invention

The purpose of the present invention is to solve the deficiencies in the existing multi-robot collaborative processing technology, and provide a robot stiffness performance evaluation scheme without additional devices to improve the robot processing accuracy. It is characterized in that the multi-robot collaborative operation system will form a multi-coupling kinematic chain. Based on the viewpoint that each joint of an industrial robot is a driving joint, the stiffness evaluation problem of a multi-robot collaborative system belongs to the research category of hyperstatically indeterminate problems. Based on the conditions established by the robot kinematics matrix and stiffness matrix, implement the robot joint stiffness identification scheme to obtain accurate actual robot joint stiffness, use the robot's real-time joint angle feedback to construct the robot Jacobian matrix, and form a multi-robot collaborative system as a whole through the Jacobian matrix and the actual robot joints stiffness matrix. The robot stiffness matrix ellipsoid is used to visualize the real-time stiffness of the robot, and the maximum value of the eigenvalue of the system stiffness matrix is selected as the evaluation index to evaluate the robot stiffness.

In order to achieve the above-mentioned purpose, the present invention adopts following technical scheme:

(1) Implement the robot joint stiffness identification scheme based on the establishment conditions of the robot kinematics matrix and stiffness matrix;

The general form of the terminal operation matrix of a six-degree-of-freedom robot is as follows:

K is a 6×6 matrix of robot end operation stiffness, is the transformation matrix from the center of the workpiece to the base of the robot, p _e is the displacement vector, pointing from the end of the robot to the center of the workpiece, Joint stiffness matrix, J is the Jacobian matrix of the robot.

When the machine is subjected to a processing force, a generalized offset is generated at the end of the machine, and the robot stiffness fitting equation is formed by the force and the generalized displacement

In formula (2), Bi is n groups of 6×6 observation matrices, and Di is the n-footed generalized displacement measurement vector. Due to the existence of measurement errors, equation (2) can obtain the six joint stiffness values c _i (i=1, 2...6) of the actual six-DOF robot through least square fitting.

(2) Establish a real-time multi-robot collaborative stiffness matrix based on the actual stiffness values of industrial robots

K＝K ₁ +K ₂ ...+K _n (3)

The terminal operation stiffness matrix of a single robot is given in the derivation (1), and the kinematic link coupling of the whole system is performed to obtain the linear accumulation of the robot system stiffness and the robot individual stiffness matrix.

(3) Use the matrix ellipsoid to visualize the real-time stiffness matrix of the robot;

The stiffness matrix of the robot is a 6×6 real symmetric matrix. The relationship between the generalized displacement and the generalized force vector at the end of the robot is not one-to-one correspondence, but a mutual influence and correlation relationship is formed according to the matrix k _ij , so it is impossible to intuitively see that a certain The advantages and disadvantages of stiffness performance under different attitudes. For this we build the robot stiffness matrix ellipsoid:

Assume that the end of the robot is always subject to a generalized force vector of τ=1

τ·τ ^T = 1 (4)

Established by the relationship between the generalized force vector of the robot and the operating stiffness matrix

Equation (5) represents the elliptic equation related to the matrix K. Through the three-dimensional drawing software, the stiffness ellipsoid of the above formula can be drawn, and the image can be loaded into the robot control system. While adjusting the attitude of the robot, the stiffness performance of the robot system under the current attitude can be intuitively observed through the image.

(4) Stiffness performance evaluation of multi-robot collaborative system

The robot stiffness matrix cannot directly express the advantages and disadvantages of the robot stiffness performance. The present invention aims at the multi-coupling characteristics of the multi-robot collaborative system, and uses the matrix Rayleigh quotient in the matrix to establish the stiffness matrix Rayleigh quotient of the multi-robot system to obtain an intuitive scalar and quantitative representation The multi-robot collaborative stiffness performance is used to evaluate its function.

The multi-machine collaborative stiffness matrix is divided into four sub-matrices according to the relationship between force and deformation:

Among them, the sub-matrix K _fd is the relationship between linear displacement and linear force:

The Rayleigh quotient of the stiffness matrix can be expressed by the length of the vector, and the expression of the Rayleigh quotient of the stiffness matrix K _fd of the cooperative system is deduced, which is the ratio of the square of the length of the generalized force vector at the end of the robot to the square of the length of the end deformation.

Bundle The calculated Rayleigh quotient of the stiffness matrix is used as the evaluation index of the robot stiffness matrix, then:

|f|＝H|d| (9)

H represents the magnitude of the external force that needs to be applied to cause the deformation of the robot collaborative system unit. The larger H is, the greater the structural resistance to deformation is, and the smaller H is, the worse the system’s resistance to deformation is. H is a function of d, it changes with the direction of d, assuming that the eigenvalue of K ^T K is λ ₁ ≤λ ₁ ≤...λ _n , according to the properties of K ^T K, it can be proved that Then we choose the smallest eigenvalue of K as the stiffness performance index I. According to k, we can see the advantages and disadvantages of the stiffness performance of the robot collaborative system under the joint angle configuration.

Compared with the prior art, the present invention has the advantages of:

The subsequent real-time stiffness performance evaluation can be completed only by identifying the joint stiffness of the industrial robot. The method has simple steps and good real-time performance. After traversing various patents at home and abroad, this invention is the first to analyze the performance of the multi-robot system stiffness, and apply this stiffness performance evaluation method to the industrial processing system through visualization software, which significantly improves the processing accuracy of the industrial robot system.

Description of drawings

Figure 1 is a flow chart of the structure of the dual-robot cooperative stiffness system.

Figure 2 is a schematic diagram of the joint stiffness identification of a six-degree-of-freedom industrial robot.

Figure 3 is a flowchart of real-time data processing of robot joints.

Figure 4 is a visualization interface of the stiffness performance of the multi-robot collaborative system.

detailed description

Below in conjunction with accompanying drawing 1-4 and specific embodiment, the present invention is described in further detail:

As shown in Figure 1, in the stiffness performance evaluation system of the multi-robot collaborative processing system proposed by the present invention, multiple robots jointly clamp the same workpiece, and the posture of the individual robot unit is selected by the multi-robot collaborative posture planner. The nominal joint stiffness value of the robot individual unit will deviate from the actual situation. The identification experiment is carried out for each robot joint stiffness value, and the actual robot joint stiffness value is obtained for subsequent system stiffness analysis. According to the joint angle assigned by the attitude planner to the robot individual unit, the operating stiffness matrix of the robot individual sub-unit is constructed. The accumulative relationship between the operating stiffness matrix of the robot individual unit and the system coordination stiffness matrix is established by the derivation (3). Import the D-H model of the robot into the three-dimensional drawing software MATLAB, and integrate the multi-robot collaborative stiffness matrix algorithm with the robot model to form the visualization result of the multi-robot collaborative stiffness performance. At the same time, the value of the collaborative stiffness performance index under the current attitude is given to determine whether the performance index value meets the process requirements. If the requirements are not met, the multi-robot collaborative attitude planner reassigns the individual robot unit attitude, and repeats the above steps. The change record of the robot stiffness performance index is also an optimization process of the planner in the attitude assignment.

As shown in FIG. 2 , it is a robot joint stiffness parameter identification device of the present invention. The nominal joint stiffness value of the robot individual unit will deviate from the actual situation, and the cumulative effect of the error on the end deformation often leads to changes in machining accuracy that are not completely consistent with the results obtained in the present invention. Therefore, obtaining the actual robot joint stiffness value is the key to the present invention link. The present invention designs the static deformation indirect measurement experiment method to obtain this parameter. It mainly includes an industrial robot unit 1, a clamping plate 2, a laser tracker reflective ball 3, a loading bracket 4, an external force regulator 5, a laser tracker 6, a data processor 7, and a loading device 8. The plate 2 is clamped at the end of the robot 1 under test. The main component of the laser tracker, the reflective ball 3, is fixedly connected to the clamped plate 2. The coordinate information of the reflective ball is obtained through the laser tracker 6, and the resulting load generated by the end of the robot is indirectly measured. deviation. The loading device is composed of a loading bracket 4, a load adjuster 5 and a load weight 8. The external force on the end of the robot is a three-dimensional vector in space, and the reasonable direction of the loading force is given by the load adjuster, and the purpose of the load change is achieved by changing the number of loads. The change of the static deformation of the robot is obtained by: 1) adjusting the attitude of the robot 1; 2) adjusting the direction of the loading force; 3) adjusting the end load. Finally, according to the relationship between load, attitude and deformation, the joint parameters of each individual robot unit are identified

As shown in FIG. 3 , it is a flow chart of data processing of real-time data of machining attitude in the present invention. The industrial robot system software can provide real-time data of the robot joints, connect it with the 3D visualization software MATLAB, provide MATLAB with the robot attitude data during processing in real time, and write the collaborative system stiffness algorithm into the MATLAB software, according to the robot processing attitude transmitted in real time Data, use the stiffness matrix ellipsoid to reflect the robot stiffness performance under the current joint configuration in real time, and display the robot stiffness performance through the software visualization interface.

As shown in Figure 4, it is a visualization interface of the robot stiffness performance designed through the visualization design software GUI. This interface mainly includes the joint angle configuration of individual robot units, the visualization interface of the stiffness performance of the multi-robot collaborative system, and the display of the stiffness performance index value in the current state. Through the intuitive display of the visual interface, you can not only observe the stiffness performance of the current system in any direction in three-dimensional space, but also evaluate the stiffness performance of multi-robot collaboration through the quantitative description of the stiffness performance index. At the same time, the joint configuration under this interface, force ellipse Both the ball and the stiffness performance index value can be used as historical data to guide the optimization of the stiffness performance of the multi-robot collaborative system.

Claims (4)

1. implementing joint of robot rigidity identification scheme based on robot kinematics' matrix and stiffness matrix set up the condition, its is specific Step is as follows：

(1) six-DOF robot end effector matrix general type is as follows：

<mrow> <mi>K</mi> <mo>=</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mi>I</mi> </mtd> <mtd> <mrow> <mi>S</mi> <mrow> <mo>(</mo> <mmultiscripts> <mi>R</mi> <mi>E</mi> <mi>O</mi> </mmultiscripts> <mo>&amp;CenterDot;</mo> <msub> <mi>p</mi> <mi>e</mi> </msub> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow></mrow> </mtd> <mtd> <mi>I</mi> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mo>&amp;CenterDot;</mo> <msup> <mi>J</mi> <mrow> <mo>-</mo> <mi>T</mi> </mrow> </msup> <mo>&amp;CenterDot;</mo> <msubsup> <mi>K</mi> <mi>&amp;theta;</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msubsup> <mo>&amp;CenterDot;</mo> <msup> <mi>J</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>&amp;CenterDot;</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mi>I</mi> </mtd> <mtd> <mrow> <mi>S</mi> <mrow> <mo>(</mo> <mmultiscripts> <mi>R</mi> <mi>E</mi> <mi>O</mi> </mmultiscripts> <mo>&amp;CenterDot;</mo> <msub> <mi>p</mi> <mi>e</mi> </msub> <mo>)</mo> </mrow> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow></mrow> </mtd> <mtd> <mi>I</mi> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow>

K is that robot end operates the matrix of rigidity 6 × 6,It is transition matrix of the work piece center to robot base, p_eIt is position The amount of shifting to, work piece center is pointed to by robot end,Joint stiffness matrix, J are robot Jacobian matrix.

When machine is subject to processing active force, machine end produces broad sense offset, and Robot Stiffness is formed by power and generalized displacement Fit equation

<mrow> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>B</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>B</mi> <mn>2</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>B</mi> <mi>n</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>&amp;times;</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>c</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>c</mi> <mn>2</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>c</mi> <mn>6</mn> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>D</mi> <mn>1</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>D</mi> <mn>2</mn> </msub> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <msub> <mi>D</mi> <mi>n</mi> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </mrow>

Bi is the observing matrix of n groups 6 × 6 in formula (2), and Di is measurement n foots generalized displacement measurement vector.Due to depositing for measurement error Formula (2) can obtain six joint stiffness value c of actual six-DOF robot by least square fitting_i(i=1,2 ... 6)。

(2) real-time multirobot collaboration stiffness matrix is established based on industrial robot practical stiffness value

K=K₁+K₂…+K_n (3)

The end effector stiffness matrix of individual machine individual human is given in derivation formula (1), motion chain link is carried out to whole system Coupling obtains robot system rigidity and the linear superposition of machine individual human stiffness matrix.

(3) visual representation is carried out to the real-time stiffness matrix of robot using matrix ellipsoid；

Robot Stiffness matrix is 6 × 6 real symmetric matrixs, and robot end's generalized displacement and the relation of broad sense force vector are not Correspondingly, but according to matrix k_ijFormation influences each other the relation of being mutually related, therefore can not intuitively find out robot Rigidity property is good and bad under some posture.For this, we establish Robot Stiffness matrix ellipsoid：

Assuming that robot end is all the time by the broad sense force vector of τ=1

τ·τ^T=1 (4)

Established by the relation of Robot Generalized force vector and operation stiffness matrix

<mrow> <msup> <mi>D</mi> <mi>T</mi> </msup> <mo>&amp;CenterDot;</mo> <msup> <mi>K</mi> <mi>T</mi> </msup> <mi>K</mi> <mo>&amp;CenterDot;</mo> <mi>D</mi> <mo>=</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mi>x</mi> </mtd> </mtr> <mtr> <mtd> <mi>y</mi> </mtd> </mtr> <mtr> <mtd> <mi>z</mi> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mo>&amp;CenterDot;</mo> <msup> <mi>K</mi> <mi>T</mi> </msup> <mi>K</mi> <mo>&amp;CenterDot;</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mi>x</mi> </mtd> </mtr> <mtr> <mtd> <mi>y</mi> </mtd> </mtr> <mtr> <mtd> <mi>z</mi> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mn>1</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>5</mn> <mo>)</mo> </mrow> </mrow>

The expression that formula (5) represents is with the related elliptic equation of matrix K.It is ellipse that rigidity can be carried out to above formula by three-dimensional drawing software The drafting of ball, this image is loaded into robot control system, also can be straight by image while robot pose is adjusted Rigidity property under the observer robot system current pose of sight.

(4) multirobot cooperative system rigidity property is evaluated

Robot Stiffness matrix can not directly express the quality of Robot Stiffness performance, and the present invention is directed to multirobot cooperative system Multiple coupled characteristic, use for reference matrix Ruili business in a matrix with multi-robot system stiffness matrix Ruili business is established, obtain One scalar directly perceived, quantization signifying multirobot collaboration rigidity property, carries out functional evaluation to it whereby.

More machines collaboration stiffness matrix is divided into four submatrixs according to the relation of power and deformation：

<mrow> <mi>K</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>K</mi> <mrow> <mi>f</mi> <mi>d</mi> </mrow> </msub> </mtd> <mtd> <msub> <mi>K</mi> <mrow> <mi>f</mi> <mi>&amp;delta;</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>K</mi> <mrow> <mi>n</mi> <mi>d</mi> </mrow> </msub> </mtd> <mtd> <msub> <mi>K</mi> <mrow> <mi>n</mi> <mi>&amp;delta;</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>6</mn> <mo>)</mo> </mrow> </mrow>

Wherein submatrix K_fdIt is to characterize linear displacement and the relation before linear force：

<mrow> <mi>f</mi> <mo>=</mo> <msub> <mi>K</mi> <mrow> <mi>f</mi> <mi>d</mi> </mrow> </msub> <mo>&amp;CenterDot;</mo> <mi>d</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>k</mi> <mn>11</mn> </msub> </mtd> <mtd> <msub> <mi>k</mi> <mn>12</mn> </msub> </mtd> <mtd> <msub> <mi>k</mi> <mn>13</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>k</mi> <mn>21</mn> </msub> </mtd> <mtd> <msub> <mi>k</mi> <mn>22</mn> </msub> </mtd> <mtd> <msub> <mi>k</mi> <mn>23</mn> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>k</mi> <mn>31</mn> </msub> </mtd> <mtd> <msub> <mi>k</mi> <mn>32</mn> </msub> </mtd> <mtd> <msub> <mi>k</mi> <mn>33</mn> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>&amp;CenterDot;</mo> <mi>d</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>7</mn> <mo>)</mo> </mrow> </mrow>

Stiffness matrix Ruili business can be represented with the length of vector, derive cooperative system stiffness matrix submatrix K_fdRuili business Expression formula, it is the ratio between length square of flat method and end deformation failure in love of robot end's generalized force vector length.

<mrow> <msub> <mi>R</mi> <mi>K</mi> </msub> <mrow> <mo>(</mo> <mi>d</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <mo>|</mo> <mi>f</mi> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> <mrow> <mo>|</mo> <mi>d</mi> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> </mfrac> <mo>=</mo> <mfrac> <mrow> <mo>|</mo> <msub> <mi>K</mi> <mrow> <mi>f</mi> <mi>d</mi> </mrow> </msub> <mo>&amp;CenterDot;</mo> <mi>d</mi> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> <mrow> <mo>|</mo> <mi>d</mi> <msup> <mo>|</mo> <mn>2</mn> </msup> </mrow> </mfrac> <mo>=</mo> <mfrac> <mrow> <msup> <mi>d</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <msubsup> <mi>K</mi> <mrow> <mi>f</mi> <mi>d</mi> </mrow> <mi>T</mi> </msubsup> <mo>&amp;CenterDot;</mo> <msub> <mi>K</mi> <mrow> <mi>f</mi> <mi>d</mi> </mrow> </msub> <mo>)</mo> </mrow> <mi>d</mi> </mrow> <mrow> <msup> <mi>d</mi> <mi>T</mi> </msup> <mo>&amp;CenterDot;</mo> <mi>d</mi> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mrow> <mo>(</mo> <mn>8</mn> <mo>)</mo> </mrow> </mrow>

Evaluation index of the stiffness matrix Ruili quotient of calculating as Robot Stiffness matrix, then have：

| f |=H | d | (9)

2. according to the method for claim 1, it is characterised in that：In step (1), industrial robot joint rigidity joint scheme Active force or load only need to be applied in robot end, without being measured to joint of robot internal drive element, passed through Least square fitting goes out to meet the joint of robot rigidity of experimental result.

3. according to claim 1, it is characterised in that：In step (2), multirobot collaboration system is derived according to theoretical algorithm The overlaying relation united between Static stiffness and robot individual cell operation rigidity, find the compound matrice of description system stiffness.

4. according to claim 1, it is characterised in that：In step (3) and step (4), it is to collaboration using visual software System rigidity is visualized, and an intuitively rigidity property display platform is provided for operator, and according to rigidity property Optimizing index, quantization signifying go out system stiffness quality, and posture configuration provides judgment criteria is cooperateed with for multirobot.