CN107391861A - Industrial robot loading kinetics parameter identification method independent of body kinetic parameter - Google Patents

Industrial robot loading kinetics parameter identification method independent of body kinetic parameter Download PDF

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Publication number
CN107391861A
CN107391861A CN201710629039.3A CN201710629039A CN107391861A CN 107391861 A CN107391861 A CN 107391861A CN 201710629039 A CN201710629039 A CN 201710629039A CN 107391861 A CN107391861 A CN 107391861A
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庹华
于文进
袁顺宁
韩建欢
韩峰涛
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Luo Shi (shandong) Technology Co Ltd
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Luo Shi (shandong) Technology Co Ltd
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Abstract

The present invention proposes a kind of industrial robot loading kinetics parameter identification method independent of body kinetic parameter, including：Establish robot body and loading kinetics parameter model；The motion-activated track of computational load dynamic parameters identification；Load torque identification motion is performed according to the motion-activated track, and gathers the exercise data in motion process；According to the exercise data obtained in the robot body and loading kinetics parameter model, and step S3 established in step S1, loading kinetics parameter processing is carried out, estimates load parameter.The present invention establishes the linear model of joint of robot driving moment and loading kinetics parameter, reduces the complexity that the identification of loading kinetics parameter solves.

Description

Industrial robot loading kinetics parameter identification independent of body kinetic parameter Method
Technical field
The present invention relates to Industrial Robot Technology field, more particularly to a kind of industrial machine independent of body kinetic parameter Device people's loading kinetics parameter identification method.
Background technology
With the continuous extension of industrial robot application scenarios, application task proposes more next to the performance of industrial robot Higher requirement.The dynamics of robot is dynamics an important factor for influenceing its movement velocity and control accuracy Influence to robot can be described by kinetic model, the pass that kinetic model is established between joint drive power and motion System, the easier accurate control of kinetic characteristic of the more accurate then robot of the relation.Therefore it is simultaneously accurate that modeling comprehensively is carried out to robot Its kinetic parameter is really obtained, online compensation is carried out to its dynamics by control system, is that lifting industrial robot moves Make the important technology approach of speed and tracking accuracy.
Industrial robot movement structure is made up of two parts in practical application：Robot body and it is connected to robot end Tool load, referring specifically to schematic diagram 1.In industrial robot field, the dynamic of robot body is not typically paid close attention to or only focused on Mechanics influence, ignore the influence of loading kinetics factor, but occur with the robot of high capacity-ratio of inertias, loading kinetics Influence of the factor in robot control also gradually protrudes.
The acquisition of robot loading kinetics parameter can be obtained by design parameter, can also be obtained by recognizing experiment. Due to the presence of machining deviation, the kinetic parameter such as support structures center of gravity, rotary inertia and actual value there may be relatively large deviation, Especially for the tool load that configuration is complicated, its dynamics parameter is often difficult to accurately obtain.Therefore industrial robot Loading kinetics parameter identification technique be to lift the important step of its performance by dynamics.
The content of the invention
The purpose of the present invention is intended at least solve one of described technological deficiency.
Therefore, it is an object of the invention to propose a kind of industrial robot load power independent of body kinetic parameter Learn parameter identification method.
To achieve these goals, embodiments of the invention provide bears independent of the industrial robot of body kinetic parameter Dynamic parameters identification method is carried, is comprised the following steps：
Step S1, robot body and loading kinetics parameter model are established, wherein, establish industrial robot load power Parameter model is learned, it is as follows：
Wherein, τlinkJoint drive power, τ when being moved for robot bodylinkloadJoint drive power during to there is tool load；
When installation tool loads front and rear execution identical movement locus, i.e. q=q0=q1 Then have：
θL=[m, sx,sy,sz,Ixx,Iyy,Izz]T
I=3,4,5,6
Wherein, WloadWhen being connected firmly for load with joint six, load movement is to power caused by robot end, and the power is by loading Kinetic parameter θLMoved with robot endTogether decide on, i=3,4,5,6 be to load using the joint of end 4 Kinetic parameter is recognized, kinetic parameter θLDefined in robot end's flange coordinate system,
Then multi-point sampling meets equation：
I.e.：
Y=ΦLθL
Step S2, the motion-activated track of computational load dynamic parameters identification, wherein, loading kinetics parameter identification fortune It is dynamic to use Y=ΦLθLFourier space excitation cycle track：
Wherein：qiFor joint i position command, ωfTo encourage track fundamental frequency, k is Fourier space, qi,0, ai,k, bi,kFor Fourier space parameter,
Excitation trajectory parameters in above formula are optimized：
minimize cond(ΦL)
Wherein, optimization object function cond (ΦL) be formula (3) in regression matrix conditional number, optimization be constrained to each joint Motion limitation, after obtained Fourier space excitation track will be optimized by emulating further checking working space collisionless, choosing For the motion-activated track of load torque identification；
Step S3, load torque identification motion is performed according to the motion-activated track, and gather the motion number in motion process According to；
Step S4, according in the robot body and loading kinetics parameter model, and step S3 established in step S1 Obtained exercise data, loading kinetics parameter processing is carried out, estimate load parameter.
Further, it is described to establish robot body and loading kinetics parameter model including as follows in the step S3 Step：The Fourier space excitation path instructions driving for optimizing to obtain according to step S2, whole identification process is divided into two steps, each Step repeats 3~5 times：
(1) the unloaded identification motion of robot；
(2) robot installation load identification motion；
In each motion process, the cycle gathers and preserves each joint position and torque data.
Further, in the step S4,
For Y=ΦLθLShown in linear equation θL, optimal solution can be obtained by weighted least-squares method：
θL *=(ΦL TW-1ΦL)-1ΦL TW-1Y
The varivance matrix that wherein weight matrix W is determined by joint moment noise：
Wherein, M is repeated sampling number, and K is the sampling number of unitary sampling, xi,m(k) it is the repeated sampling of i joints the m times K-th of sample point data of process.
Further, in the step S4,
Joint velocity, acceleration information are obtained to difference after joint position data frequency-selective filtering, are specifically divided into two sub-steps Suddenly：
Joint position filters：
qi,filtered(k)=filter (qi(0),qi(1),…qi(K))
Filter posterior joint position data difference：
Further, in the step S1, industrial robot loading kinetics modeling method, by the gravity of load movement, Inertia force is equivalent to load the external force of robot end, establishes the relational model of loading kinetics parameter and joint motions, enters one Walk the linear relationship for by loading kinetics model linearization, establishing joint driven torque and loading kinetics parameter.
Further, in the step S2, industrial robot load torque identification excitation Trajectory Design, is with regression matrix condition The minimum target of number, the load torque identification optimal excitation orbit generation method obtained by Optimization Solution.
Further, loading kinetics parameter processing method, it is the pass by frequency-selective filtering to collection in the step S4 Save position data processing, and obtained by Filtering position data difference joint velocity, the processing method of acceleration information and The method of estimation of loading kinetics parameter is fitted by weighted least-squares method.
Industrial robot loading kinetics parameter identification independent of body kinetic parameter according to embodiments of the present invention Method, under the conditions of the kinetic parameter independent of robot body, load weight, centroid position can be independently obtained, rotates and is used to Parameter is measured, can be applied to high performance control of the robot based on model.
The present invention has following advantage：
1st, the linear model of joint of robot driving moment and loading kinetics parameter is established, reduces loading kinetics The complexity that the identification of parameter solves；
2nd, the axle of identification process Zhi Xu robots 3/4/5/6 moves in a small range, and the limitation to space is insensitive, because This can be widely applied to task scene and tool load recognized；
3rd, the identification process time is short, and identification process need to only gather robot itself joint kinematic parameter, without extra Measuring apparatus, cost is small to be easy to apply；
Because Identification Data Processing process does not need extra robot body power in addition to robot links sized data Parameter is learned, therefore institute's extracting method can be widely applied to the industrial robot load torque identification of various configuration.
The additional aspect of the present invention and advantage will be set forth in part in the description, and will partly become from the following description Obtain substantially, or recognized by the practice of the present invention.
Brief description of the drawings
The above-mentioned and/or additional aspect and advantage of the present invention will become in the description from combination accompanying drawings below to embodiment Substantially and it is readily appreciated that, wherein：
Fig. 1 is the schematic diagram of industrial robot movement structure；
Fig. 2 is the industrial robot loading kinetics parameter independent of body kinetic parameter according to the embodiment of the present invention The flow chart of discrimination method；
Fig. 3 is the kinetic parameter θ according to the embodiment of the present inventionLShowing defined in robot end's flange coordinate system It is intended to；
Fig. 4 is the schematic diagram according to the motion-activated track of the load torque identification of the embodiment of the present invention.
Embodiment
Embodiments of the invention are described below in detail, the example of the embodiment is shown in the drawings, wherein from beginning to end Same or similar label represents same or similar element or the element with same or like function.Below with reference to attached The embodiment of figure description is exemplary, it is intended to for explaining the present invention, and is not considered as limiting the invention.
As shown in Fig. 2 the industrial robot loading kinetics independent of body kinetic parameter of the embodiment of the present invention are joined Number discrimination method, comprises the following steps：
Step S1, robot body and loading kinetics parameter model are established, wherein, establish industrial robot load power Parameter model is learned, it is as follows：
Wherein, τlinkJoint drive power, τ when being moved for robot bodylinkloadJoint drive power during to there is tool load；
When installation tool loads front and rear execution identical movement locus, i.e. q=q0=q1 Then have：
θL=[m, sx,sy,sz,Ixx,Iyy,Izz]T
I=3,4,5,6
Wherein, WloadWhen being connected firmly for load with joint six, load movement is to power caused by robot end, and the power is by loading Kinetic parameter θLMoved with robot endTogether decide on, i=3,4,5,6 be to load using the joint of end 4 Kinetic parameter is recognized, kinetic parameter θLDefined in robot end's flange coordinate system, with reference to figure 3.
Multi-point sampling meets equation：
I.e.：
Y=ΦLθL
Step S2, the motion-activated track of computational load dynamic parameters identification, wherein, loading kinetics parameter identification fortune It is dynamic to use Y=ΦLθLFourier space excitation cycle track：
Wherein：qiFor joint i position command, ωfTo encourage track fundamental frequency, k is Fourier space, qi,0, ai,k, bi,kFor Fourier space parameter,
Excitation trajectory parameters in above formula are optimized：
minimize cond(ΦL)
Wherein, optimization object function cond (ΦL) it is Y=ΦLθLThe conditional number of middle regression matrix, optimization are constrained to each pass Section motion limitation, after obtained Fourier space excitation track will be optimized by emulating further checking working space collisionless, Elect the motion-activated track of load torque identification as, as shown in Figure 4.
Step S3, load torque identification motion is performed according to motion-activated track, and gather the exercise data in motion process.
Specifically, in step s3, it is described to establish robot body and loading kinetics parameter model, including following step Suddenly：Driven according to the step S2 Fourier space excitation path instructions for optimizing to obtain, during load torque identification, 1,2 joint position Fixed, 3/4/5/6 joint position is driven by the Fourier space excitation path instructions obtained by step 2) optimization, whole identification Process is divided into two steps, and each step repeats 3~5 times：
(1) the unloaded identification motion of robot；
(2) robot installation load identification motion；
The cycle gathers and preserves 3/4/5/6 joint position and torque data in each motion process.
Step S4, according in the robot body and loading kinetics parameter model, and step S3 established in step S1 Obtained exercise data, loading kinetics parameter processing is carried out, estimate load parameter.
Specifically, in the step S4,
For Y=ΦLθLShown in linear equation θL, optimal solution can be obtained by weighted least-squares method：
θL *=(ΦL TW-1ΦL)-1ΦL TW-1Y
The varivance matrix that wherein weight matrix W is determined by joint moment noise：
Wherein, M is repeated sampling number, and K is the sampling number of unitary sampling, xi,m(k) it is the repeated sampling of i joints the m times K-th of sample point data of process.
Due to regression matrix ΦLCalculate the joint velocity needed and acceleration information directly can not be provided by sensor, together When joint position data carry certain noise, by obtaining joint to difference after joint position data frequency-selective filtering in this programme Speed, acceleration information, it is specifically divided into two sub-steps：
Joint position filters：
qi,filtered(k)=filter (qi(0),qi(1),…qi(K))
Filter posterior joint position data difference：
Industrial robot loading kinetics modeling method, the gravity of load movement, inertia force particularly be equivalent to load The external force of robot end, so as to establish the relational model of loading kinetics parameter and joint motions, further by load power Model linearization is learned, establishes the linear relationship of joint driven torque and loading kinetics parameter.
Industrial robot load torque identification encourages Trajectory Design, particularly with the minimum target of regression matrix conditional number, passes through The load torque identification optimal excitation orbit generation method that Optimization Solution obtains.
Loading kinetics parameter processing method, especially by joint position data processing of the frequency-selective filtering to collection, and The joint velocity that is obtained by Filtering position data difference, the processing method of acceleration information and by weighted least-squares side Method is fitted the method for estimation of loading kinetics parameter.
Industrial robot loading kinetics parameter identification independent of body kinetic parameter according to embodiments of the present invention Method, under the conditions of the kinetic parameter independent of robot body, load weight, centroid position can be independently obtained, rotates and is used to Parameter is measured, can be applied to high performance control of the robot based on model.
The present invention has following advantage：
1st, the linear model of joint of robot driving moment and loading kinetics parameter is established, reduces loading kinetics The complexity that the identification of parameter solves；
2nd, the axle of identification process Zhi Xu robots 3/4/5/6 moves in a small range, and the limitation to space is insensitive, because This can be widely applied to task scene and tool load recognized；
3rd, the identification process time is short, and identification process need to only gather robot itself joint kinematic parameter, without extra Measuring apparatus, cost is small to be easy to apply；
Because Identification Data Processing process does not need extra robot body power in addition to robot links sized data Parameter is learned, therefore institute's extracting method can be widely applied to the industrial robot load torque identification of various configuration.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show The description of example " or " some examples " etc. means specific features, structure, material or the spy for combining the embodiment or example description Point is contained at least one embodiment or example of the present invention.In this manual, to the schematic representation of above-mentioned term not Necessarily refer to identical embodiment or example.Moreover, specific features, structure, material or the feature of description can be any One or more embodiments or example in combine in an appropriate manner.
Although embodiments of the invention have been shown and described above, it is to be understood that above-described embodiment is example Property, it is impossible to limitation of the present invention is interpreted as, one of ordinary skill in the art is not departing from the principle and objective of the present invention In the case of above-described embodiment can be changed within the scope of the invention, change, replace and modification.The scope of the present invention By appended claims and its equivalent limit.

Claims (7)

  1. A kind of 1. industrial robot loading kinetics parameter identification method independent of body kinetic parameter, it is characterised in that Comprise the following steps：
    Step S1, robot body and loading kinetics parameter model are established, wherein, establish industrial robot loading kinetics ginseng Exponential model is as follows：
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    Wherein, τlinkJoint drive power, τ when being moved for robot bodylinkloadJoint drive power during to there is tool load；
    When installation tool loads front and rear execution identical movement locus, i.e. q=q0=q1 Then have：
    <mrow> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>i</mi> <mi>n</mi> <mi>k</mi> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>-</mo> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>i</mi> <mi>n</mi> <mi>k</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>=</mo> <msup> <mi>J</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> <msub> <mi>W</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <msup> <mi>J</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> <msub> <mi>&amp;phi;</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mrow> <msub> <mi>V</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>,</mo> <msub> <mover> <mi>V</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> </mrow> <mo>)</mo> </mrow> <mi>L</mi> <mo>=</mo> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mrow> <mo>(</mo> <mrow> <mi>q</mi> <mo>,</mo> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mo>,</mo> <mover> <mi>q</mi> <mo>&amp;CenterDot;&amp;CenterDot;</mo> </mover> </mrow> <mo>)</mo> </mrow> <msub> <mi>&amp;theta;</mi> <mi>L</mi> </msub> </mrow>
    <mrow> <msub> <mi>W</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> </mrow> </msub> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>F</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>T</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mi>m</mi> <msub> <mover> <mi>v</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>+</mo> <msub> <mover> <mi>&amp;omega;</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>&amp;times;</mo> <mi>s</mi> <mo>+</mo> <msub> <mi>&amp;omega;</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>&amp;times;</mo> <mo>(</mo> <msub> <mi>&amp;omega;</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>&amp;times;</mo> <mi>s</mi> <mo>)</mo> </mtd> </mtr> <mtr> <mtd> <mi>s</mi> <mo>&amp;times;</mo> <msub> <mover> <mi>v</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>+</mo> <msup> <mi>I</mi> <mi>R</mi> </msup> <msub> <mover> <mi>&amp;omega;</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>+</mo> <msub> <mi>&amp;omega;</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>&amp;times;</mo> <mo>(</mo> <msup> <mi>I</mi> <mi>R</mi> </msup> <msub> <mi>&amp;omega;</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>)</mo> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <msub> <mi>&amp;phi;</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>V</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>,</mo> <msub> <mover> <mi>V</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>)</mo> </mrow> <msub> <mi>&amp;theta;</mi> <mi>L</mi> </msub> </mrow>
    <mrow> <msub> <mi>V</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>v</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;omega;</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mi>J</mi> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> </mrow>
    <mrow> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>q</mi> <mo>,</mo> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mo>,</mo> <mover> <mi>q</mi> <mo>&amp;CenterDot;&amp;CenterDot;</mo> </mover> <mo>)</mo> </mrow> <mo>=</mo> <msup> <mi>J</mi> <mi>T</mi> </msup> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> <msub> <mi>&amp;phi;</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <msub> <mi>V</mi> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>,</mo> <msub> <mover> <mi>V</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>e</mi> <mi>e</mi> </mrow> </msub> <mo>)</mo> </mrow> </mrow>
    θL=[m, sx,sy,sz,Ixx,Iyy,Izz]T
    I=3,4,5,6
    Wherein, WloadWhen being connected firmly for load with joint six, for load movement to power caused by robot end, the power is dynamic by what is loaded Mechanics parameter θLV is moved with robot endee,Together decide on, i=3,4,5,6 be to load power using the joint of end 4 Learn parameter to be recognized, kinetic parameter θLDefined in robot end's flange coordinate system,
    Then multi-point sampling meets equation：
    <mrow> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>3</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>4</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>5</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>6</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <mtable> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> </mtable> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>3</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>4</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>5</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;tau;</mi> <mrow> <mi>l</mi> <mi>o</mi> <mi>a</mi> <mi>d</mi> <mo>,</mo> <mi>j</mi> <mn>6</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>3</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>4</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>5</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>6</mn> <mo>,</mo> <mi>s</mi> <mn>1</mn> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <mtable> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> <mtr> <mtd> <mo>.</mo> </mtd> </mtr> </mtable> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>3</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>4</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>5</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>&amp;phi;</mi> <mrow> <mi>L</mi> <mo>,</mo> <mi>j</mi> <mn>6</mn> <mo>,</mo> <mi>s</mi> <mi>n</mi> </mrow> </msub> </mtd> </mtr> </mtable> </mfenced> <msub> <mi>&amp;theta;</mi> <mi>L</mi> </msub> </mrow>
    I.e.：
    Y=ΦLθL
    Step S2, the motion-activated track of computational load dynamic parameters identification, wherein, the motion of loading kinetics parameter identification is adopted With Y=ΦLθLFourier space excitation cycle track：
    <mrow> <msub> <mi>q</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mo>,</mo> <mn>0</mn> </mrow> </msub> <mo>+</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>a</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mi>s</mi> <mi>i</mi> <mi>n</mi> <mo>(</mo> <mrow> <msub> <mi>k&amp;omega;</mi> <mi>f</mi> </msub> <mi>t</mi> </mrow> <mo>)</mo> <mo>+</mo> <msub> <mi>b</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>k</mi> </mrow> </msub> <mi>c</mi> <mi>o</mi> <mi>s</mi> <mo>(</mo> <mrow> <msub> <mi>k&amp;omega;</mi> <mi>f</mi> </msub> <mi>t</mi> </mrow> <mo>)</mo> <mo>)</mo> </mrow> <mo>,</mo> </mrow> 1
    Wherein：qiFor joint i position command, ωfTo encourage track fundamental frequency, k is Fourier space, qi,0, ai,k, bi,kFor in Fu Leaf series parameter,
    Excitation trajectory parameters in above formula are optimized：
    minimize cond(ΦL)
    <mrow> <mi>s</mi> <mo>.</mo> <mi>t</mi> <mo>.</mo> <mfenced open = "{" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> <mo>&amp;le;</mo> <msub> <mi>q</mi> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>&amp;le;</mo> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>i</mi> <mo>,</mo> <mi>m</mi> <mi>i</mi> <mi>n</mi> </mrow> </msub> <mo>&amp;le;</mo> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>&amp;le;</mo> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>i</mi> <mo>,</mo> <mi>m</mi> <mi>a</mi> <mi>x</mi> </mrow> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;&amp;CenterDot;</mo> </mover> <mrow> <mi>i</mi> <mo>,</mo> <mi>min</mi> </mrow> </msub> <mo>&amp;le;</mo> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;&amp;CenterDot;</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> <mo>&amp;le;</mo> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;&amp;CenterDot;</mo> </mover> <mrow> <mi>i</mi> <mo>,</mo> <mi>max</mi> </mrow> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>3</mn> <mo>,</mo> <mn>4</mn> <mo>,</mo> <mn>5</mn> <mo>,</mo> <mn>6</mn> </mrow>
    Wherein, optimization object function cond (ΦL) be constrained to each joint motions for the conditional number of regression matrix in formula (3), optimization and limit System, after obtained Fourier space excitation track will be optimized by emulating further checking working space collisionless, elect load as The motion-activated track of identification；
    Step S3, load torque identification motion is performed according to the motion-activated track, and gather the exercise data in motion process；
    Step S4, obtained according in the robot body and loading kinetics parameter model, and step S3 established in step S1 Exercise data, carry out loading kinetics parameter processing, estimate load parameter.
  2. 2. the industrial robot loading kinetics parameter identification side independent of body kinetic parameter as claimed in claim 1 Method, it is characterised in that described to establish robot body and loading kinetics parameter model including as follows in the step S3 Step：The Fourier space excitation path instructions driving for optimizing to obtain according to step S2, whole identification process is divided into two steps, each Step repeats 3~5 times：
    (1) the unloaded identification motion of robot；
    (2) robot installation load identification motion；
    In each motion process, the cycle gathers and preserves each joint position and torque data.
  3. 3. the industrial robot loading kinetics parameter identification side independent of body kinetic parameter as claimed in claim 1 Method, it is characterised in that in the step S4,
    For Y=ΦLθLShown in linear equation θL, optimal solution can be obtained by weighted least-squares method：
    θL *=(ΦL TW-1ΦL)-1ΦL TW-1Y
    The varivance matrix that wherein weight matrix W is determined by joint moment noise：
    <mrow> <mi>W</mi> <mo>=</mo> <munder> <mrow> <mi>d</mi> <mi>i</mi> <mi>a</mi> <mi>g</mi> </mrow> <mrow> <mi>i</mi> <mo>=</mo> <mi>s</mi> <mn>1</mn> <mo>,</mo> <mi>s</mi> <mn>2...</mn> <mi>s</mi> <mi>n</mi> </mrow> </munder> <mrow> <mo>(</mo> <mi>d</mi> <mi>i</mi> <mi>a</mi> <mi>g</mi> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mrow> <msup> <msub> <mi>&amp;sigma;</mi> <mn>3</mn> </msub> <mn>2</mn> </msup> </mrow> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;sigma;</mi> <mn>4</mn> </msub> <mn>2</mn> </msup> </mrow> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;sigma;</mi> <mn>5</mn> </msub> <mn>2</mn> </msup> </mrow> </mtd> <mtd> <mrow> <msup> <msub> <mi>&amp;sigma;</mi> <mn>6</mn> </msub> <mn>2</mn> </msup> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>)</mo> </mrow> </mrow>
    <mrow> <msup> <msub> <mi>&amp;sigma;</mi> <mi>i</mi> </msub> <mn>2</mn> </msup> <mo>=</mo> <mfrac> <mn>1</mn> <mrow> <mo>(</mo> <mi>M</mi> <mi>K</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>m</mi> </mrow> </msub> <mo>(</mo> <mi>k</mi> <mo>)</mo> <mo>-</mo> <msub> <mover> <mi>x</mi> <mo>&amp;OverBar;</mo> </mover> <mi>i</mi> </msub> <mo>(</mo> <mi>k</mi> <mo>)</mo> <mo>)</mo> </mrow> <mn>2</mn> </msup> </mrow>
    <mrow> <msub> <mover> <mi>x</mi> <mo>&amp;OverBar;</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mn>1</mn> <mi>M</mi> </mfrac> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <msub> <mi>x</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>m</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> </mrow>
    Wherein, M is repeated sampling number, and K is the sampling number of unitary sampling, xi,m(k) it is the repeated sampling process of i joints the m times K-th of sample point data.
  4. 4. the industrial robot loading kinetics parameter identification side independent of body kinetic parameter as claimed in claim 1 Method, it is characterised in that in the step S4,
    Joint velocity, acceleration information are obtained to difference after joint position data frequency-selective filtering, are specifically divided into two sub-steps：
    Joint position filters：
    qi,filtered(k)=filter (qi(0),qi(1),…qi(K))
    Filter posterior joint position data difference：
    <mrow> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>f</mi> <mi>i</mi> <mi>l</mi> <mi>t</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>d</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mi>q</mi> <mrow> <mi>i</mi> <mo>,</mo> <mi>f</mi> <mi>i</mi> <mi>l</mi> <mi>t</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>d</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> <mrow> <mi>&amp;Delta;</mi> <mi>T</mi> </mrow> </mfrac> </mrow>
    <mrow> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;&amp;CenterDot;</mo> </mover> <mi>i</mi> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>i</mi> <mo>,</mo> <mi>f</mi> <mi>i</mi> <mi>l</mi> <mi>t</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>d</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>-</mo> <msub> <mover> <mi>q</mi> <mo>&amp;CenterDot;</mo> </mover> <mrow> <mi>i</mi> <mo>,</mo> <mi>f</mi> <mi>i</mi> <mi>l</mi> <mi>t</mi> <mi>e</mi> <mi>r</mi> <mi>e</mi> <mi>d</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>k</mi> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> <mrow> <mi>&amp;Delta;</mi> <mi>T</mi> </mrow> </mfrac> <mo>.</mo> </mrow>
  5. 5. the industrial robot loading kinetics parameter identification side independent of body kinetic parameter as claimed in claim 1 Method, it is characterised in that in the step S1, industrial robot loading kinetics modeling method, by the gravity of load movement, be used to Property power be equivalent to load the external force of robot end, establish the relational models of loading kinetics parameter and joint motions, further By loading kinetics model linearization, the linear relationship of joint driven torque and loading kinetics parameter is established.
  6. 6. the industrial robot loading kinetics parameter identification side independent of body kinetic parameter as claimed in claim 1 Method, it is characterised in that in the step S2, industrial robot load torque identification excitation Trajectory Design, is with regression matrix condition The minimum target of number, the load torque identification optimal excitation orbit generation method obtained by Optimization Solution.
  7. 7. the industrial robot loading kinetics parameter identification side independent of body kinetic parameter as claimed in claim 1 Method, it is characterised in that loading kinetics parameter processing method, be the pass by frequency-selective filtering to collection in the step S4 Save position data processing, and obtained by Filtering position data difference joint velocity, the processing method of acceleration information and The method of estimation of loading kinetics parameter is fitted by weighted least-squares method.
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CN108595888A (en) * 2018-05-10 2018-09-28 珞石（山东）智能科技有限公司 The emulation platform and method with verification are designed towards industrial robot
CN108638070A (en) * 2018-05-18 2018-10-12 珞石（山东）智能科技有限公司 Robot based on dynamic equilibrium loads weight parameter discrimination method
CN110554643A (en) * 2019-08-16 2019-12-10 深圳华数机器人有限公司 industrial robot drive and control system based on safety force control
CN111037567A (en) * 2019-12-30 2020-04-21 上海新时达机器人有限公司 Six-axis robot tail end load identification method and module
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CN108638070A (en) * 2018-05-18 2018-10-12 珞石（山东）智能科技有限公司 Robot based on dynamic equilibrium loads weight parameter discrimination method
CN110554643A (en) * 2019-08-16 2019-12-10 深圳华数机器人有限公司 industrial robot drive and control system based on safety force control
CN111104563A (en) * 2019-11-11 2020-05-05 武汉科技大学 Kinematic chain isomorphism judgment method based on prime number asymmetric adjacent matrix
CN111104563B (en) * 2019-11-11 2024-04-16 武汉科技大学 Method for determining isomorphism of kinematic chain based on prime number asymmetric adjacency matrix
CN111037567A (en) * 2019-12-30 2020-04-21 上海新时达机器人有限公司 Six-axis robot tail end load identification method and module
CN111037568A (en) * 2019-12-30 2020-04-21 上海新时达机器人有限公司 Four-axis robot tail end load identification method and module
CN112507480A (en) * 2020-11-25 2021-03-16 浙江同善人工智能技术有限公司 Inertial parameter identification method
CN112507480B (en) * 2020-11-25 2024-06-07 浙江同善人工智能技术有限公司 Inertial parameter identification method
CN113910229B (en) * 2021-10-14 2023-01-31 库卡机器人制造（上海）有限公司 Load parameter identification method, identification device, readable storage medium and robot
CN113910229A (en) * 2021-10-14 2022-01-11 库卡机器人制造（上海）有限公司 Load parameter identification method, identification device, readable storage medium and robot
CN113977578A (en) * 2021-10-26 2022-01-28 华东交通大学 Soft measurement method for end force of hydraulic mechanical arm
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CN113977578B (en) * 2021-10-26 2022-10-18 华东交通大学 Soft measurement method for end force of hydraulic mechanical arm
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CN114211502A (en) * 2021-12-31 2022-03-22 北京敏锐达致机器人科技有限责任公司 Robot load identification method and identification device

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Application publication date: 20171124