CN107369167A - A kind of robot self-calibrating method based on biplane constraint error model - Google Patents

A kind of robot self-calibrating method based on biplane constraint error model Download PDF

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CN107369167A
CN107369167A CN201710595019.9A CN201710595019A CN107369167A CN 107369167 A CN107369167 A CN 107369167A CN 201710595019 A CN201710595019 A CN 201710595019A CN 107369167 A CN107369167 A CN 107369167A
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王晨学
平雪良
徐超
蒋毅
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Jiangnan University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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    • G06T7/20—Analysis of motion
    • G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
    • G06T7/251—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments involving models
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
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Abstract

The present invention relates to a kind of robot self-calibrating method based on biplane constraint error model, for obtaining the real link parameters of robot.Initially set up robot kinematics' model that D H methods are combined with MD H methods；Next establishes robot end's site error model；Then robot biplane constraint error model is established, the model is related to the obligatory point on two faces (being parallel to each other or vertical), the single plane fitted according to theoretical position point, while self level is met, also need to ensure the position relationship of pairwise correlation interplanar, reduce the deviation between the plane and the plane that fits of theoretical position point of physical constraint point composition.By two are parallel to each other or vertical constraint plane carry out contact type measurement, the data for most measuring to obtain at last substitute into biplane constraint error model, the real geometry link parameters of robot are picked out, duplicate measurements constraint plane and are recognized after amendment, until reaching required precision.The inventive method has the characteristics of cost is low, precision is higher.

Description

A kind of robot self-calibrating method based on biplane constraint error model
Technical field
The present invention relates to a kind of robot self-calibrating method, more particularly to a kind of machine based on biplane constraint error model Device people's self-calibrating method.
Background technology
1. robot localization precision is to weigh an important indicator of its service behaviour, at present, domestic and international manufacturer production goes out Due to the factor such as manufacturing, installing, most absolute fix precision is not high for the robot come, can not meet high finishing and offline compile The needs of journey, therefore, the various factors for causing robot localization error is analyzed, it is absolute to improve robot most possibly Positioning precision has become the core content in robot technology research.
2. in order to reduce the factors such as cost, many researchers propose robot kinematics' error based on plane restriction Model, the positioning precision of robot is improved to a certain extent.However, the scaling method based on plane restriction, its precision is not only The flatness of constraint plane is only dependent upon, research shows, the plane that physical constraint point is formed fits flat with theoretical position point Face can have certain deviation, and the deviation can impact to the identification of kinematics parameters, and therefore, Robot calibration precision can enter one Step improves.
3. being directed to above-mentioned technical situation, the present invention proposes a kind of robot self-calibration based on biplane constraint error model Method.
The content of the invention
For above-mentioned the shortcomings of the prior art：General closed planar constraint error model is only by single constraint plane Obligatory point is established, and causes the plane that the plane that physical constraint point is formed fits with theoretical position point relatively large deviation, this hair to be present It is bright provide it is a kind of based on biplane constraint error model robot self-calibrating method, this method need two are parallel to each other or Vertical constraint plane carries out contact type measurement, and error model is related to the obligatory point on two faces, therefore according to theoretical position The single plane that point fits, while self level is ensured, it is also necessary to meet the perpendicular or parallel pass with correlation plane System, therefore the deviation between the plane and the plane that fits of theoretical position point of physical constraint point composition is reduced, further carry High stated accuracy.
Technical solution of the present invention step is as follows：
(1) robot kinematics' model is established
Establish robot kinematics' model that D-H methods are combined with MD-H methods, the conversion by coordinate system i-1 to coordinate system i Process description is Ai, Ai=f (αi-1,ai-1,di,θi, β), then robot end's coordinate system n relative to basis coordinates system pose square Battle array0TnFor：
0Tn=A0·A1·...·An
(2) robot end's site error model is established
According to the thought of differential transform to AiTotal differential is carried out, obtains the adjacent coordinates as caused by connecting rod geometric parameter error Differential perturbation homogeneous matrix dA between systemi：
δAiDifferential transforms of the joint coordinate system i relative to coordinate system i-1, then the reality between adjacent two connecting rod of robot Border homogeneous coordinate transformationThat is Ai+AiδAi, then robot end's coordinate system is relative to the actual neat of basis coordinates system Secondary transformation matrix TRFor：
Above formula is deployed, and omits High Order Perturbation item, following formula is obtained after abbreviation：
Wherein, Δ P=[dPx dPy dPz]TIt is robot location's error matrix, J is the micro- of 3 × (4n+1) link parameters Divide conversion Jacobian matrix, Δ X=[Δ α Δ a Δ θ Δ d Δs β]TFor the link parameters error matrix of (4n+1) × 1；
(3) robot kinematics' error model based on biplane constraint is established
If, can be by robot just for the nominal position value of i-th of contact point on constraint plane I Kinematics directly calculates, JpiFor the Jacobian matrix of the opening position, can be calculated by joint angle angle value, physical location Pi R =Pi N+JpiΔ X, the then bias vector between adjacent two contact point：
Wherein,ΔJpi=Jpi-Jpi-1；
Similarly,So by two adjacent bias vectors Can build one perpendicular to plane I nominal normal vector：
Constraint plane II is perpendicular with constraint plane I (parallel),For the nominal position value of i-th of contact point, then by Two adjacent bias vectors can build one perpendicular to plane II nominal normal vector：
If plane I is vertical with plane II, then：
If plane I is parallel with plane II, then：
(4) driving robot measures respectively to related constraint plane
Driving robot carries out contact type measurement respectively to constraint plane I, II, when measurement head exports activation signal, stands Current each joint angle angle value is recorded, and next obligatory point is measured, after gathering a number of point, is then had：
H Δs X+S=0
Wherein,It can then produce 3N equation；
(5) robot links parameter identification
By improved least square method, robot kinematics' parameter error is recognized, it is as follows:
Δ X=- (HTH+μI)-1HTS
(6) demarcation checking
Robot kinematics' parameter offset that identification obtains in step (5) is updated in robot controller software, Again teaching several points, compare whether robot theory terminal position is constrained in a plane, if it is not, then continue step (4), (5), (6), until meeting the required precision reached required for system.
The beneficial effects of the invention are as follows：A kind of robot based on biplane constraint error model provided by the invention is marked certainly Determine method, further increase stated accuracy.By two are parallel to each other or vertical constraint plane carry out contact type measurement, Robot biplane constraint error model is established, the model is related to the obligatory point on two faces, therefore according to theoretical position point The single plane fitted, while self level is ensured, it is also necessary to meet the perpendicular or parallel relation with correlation plane, The deviation between the plane and the plane that fits of theoretical position point of physical constraint point composition is thus reduced, improves demarcation essence Degree.
Other features and advantages of the present invention will illustrate in the following description, partly become from specification it is aobvious and It is clear to, or relatively understands afterwards by implementing the present invention, and with other method.
Brief description of the drawings
The embodiment of the present invention is described further below in conjunction with the accompanying drawings.
Fig. 1 is demarcation site schematics；
Fig. 2 is biplane obligatory point schematic diagram；
Fig. 3 is the robot self-calibrating method flow chart based on biplane constraint error model.
Embodiment
The preferred embodiments of the present invention are illustrated below in conjunction with accompanying drawing, it will be appreciated that described herein preferred real Apply example to be merely to illustrate and explain the present invention, be not intended to limit the present invention.
Referring to accompanying drawing 1~3, the robot self-calibrating method of the invention based on biplane constraint error model, including with Under several steps：
(1) robot kinematics' model is established
Establish robot kinematics' model that D-H methods are combined with MD-H methods, the conversion by coordinate system i-1 to coordinate system i Process description is Ai, Ai=f (αi-1,ai-1,di,θi,βi), then robot end's coordinate system n relative to basis coordinates system pose square Battle array0TnFor：
0Tn=A0·A1·...·An
(2) robot end's site error model is established
According to the thought of differential transform to AiTotal differential is carried out, obtains the adjacent coordinates as caused by connecting rod geometric parameter error Differential perturbation homogeneous matrix dA between systemi：
δAiDifferential transforms of the joint coordinate system i relative to coordinate system i-1, then the reality between adjacent two connecting rod of robot Border homogeneous coordinate transformationThat is Ai+AiδAi, then robot end's coordinate system is relative to the actual neat of basis coordinates system Secondary transformation matrix TRFor：
Above formula is deployed, and omits High Order Perturbation item, following formula is obtained after abbreviation：
Wherein, Δ P=[dPx dPy dPz]TIt is robot location's error matrix, J is the micro- of 3 × (4n+1) link parameters Divide conversion Jacobian matrix, Δ X=[Δ α Δ a Δ θ Δ d Δs β]TFor the link parameters error matrix of (4n+1) × 1；
(3) robot kinematics' error model based on biplane constraint is established
If, can be by robot just for the nominal position value of i-th of contact point on constraint plane I Kinematics directly calculates, JpiFor the Jacobian matrix of the opening position, can be calculated by joint angle angle value, physical location Pi R =Pi N+JpiΔ X, the then bias vector between adjacent two contact point：
Wherein,ΔJpi=Jpi-Jpi-1；
Similarly,So by two adjacent bias vectors Can build one perpendicular to plane I nominal normal vector：
Constraint plane II is perpendicular with constraint plane I (parallel),For the nominal position value of i-th of contact point, then by Two adjacent bias vectors can build one perpendicular to plane II nominal normal vector：
If plane I is vertical with plane II, then：
If plane I is parallel with plane II, then：
(4) driving robot measures respectively to related constraint plane
Driving robot carries out contact type measurement respectively to constraint plane I, II, when measurement head exports activation signal, stands Current each joint angle angle value is recorded, and next obligatory point is measured, after gathering a number of point, is then had：
H Δs X+S=0
Wherein,It can then produce 3N equation；
(5) robot links parameter identification
By improved least square method, robot kinematics' parameter error is recognized, it is as follows：
Δ X=- (HTH+μI)-1HTS
Thus, all link parameters errors of robot can be picked out.
(6) demarcation checking
Robot kinematics' parameter offset that identification obtains in step (5) is updated in robot controller software, Again teaching several points, compare whether robot theory terminal position is constrained in a plane, if it is not, then continue step (4), (5), (6), until meeting the required precision reached required for system.
Although above-mentioned the embodiment of the present invention is described with reference to accompanying drawing, model not is protected to the present invention The limitation enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme those skilled in the art are not Need to pay various modifications or deformation that creative work can make still within protection scope of the present invention.

Claims (3)

  1. A kind of 1. robot self-calibrating method based on biplane constraint error model, it is characterised in that：Comprise the following steps：
    (1) robot kinematics' model is established
    Establish robot kinematics' model that D-H methods are combined with MD-H methods, the conversion process by coordinate system i-1 to coordinate system i It is described as Ai, Ai=f (αi-1,ai-1,di,θi, β), then robot end's coordinate system n relative to basis coordinates system position auto―control0Tn For：
    0Tn=A0·A1·...·An
    (2) robot end's site error model is established
    According to the thought of differential transform to AiTotal differential is carried out, is obtained between the adjacent coordinates system as caused by connecting rod geometric parameter error Differential perturbation homogeneous matrix dAi：
    <mrow> <msub> <mi>dA</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mo>&amp;part;</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> </mrow> <mrow> <mo>&amp;part;</mo> <msub> <mi>&amp;alpha;</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </mrow> </mfrac> <msub> <mi>&amp;Delta;&amp;alpha;</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>+</mo> <mfrac> <mrow> <mo>&amp;part;</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> </mrow> <mrow> <mo>&amp;part;</mo> <msub> <mi>a</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </mrow> </mfrac> <msub> <mi>&amp;Delta;a</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> <mo>+</mo> <mfrac> <mrow> <mo>&amp;part;</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> </mrow> <mrow> <mo>&amp;part;</mo> <msub> <mi>&amp;theta;</mi> <mi>i</mi> </msub> </mrow> </mfrac> <msub> <mi>&amp;Delta;&amp;theta;</mi> <mi>i</mi> </msub> <mo>+</mo> <mfrac> <mrow> <mo>&amp;part;</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> </mrow> <mrow> <mo>&amp;part;</mo> <msub> <mi>d</mi> <mi>i</mi> </msub> </mrow> </mfrac> <msub> <mi>&amp;Delta;d</mi> <mi>i</mi> </msub> <mo>+</mo> <mfrac> <mrow> <mo>&amp;part;</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> </mrow> <mrow> <mo>&amp;part;</mo> <mi>&amp;beta;</mi> </mrow> </mfrac> <mi>&amp;Delta;</mi> <mi>&amp;beta;</mi> <mo>=</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> <msub> <mi>&amp;delta;A</mi> <mi>i</mi> </msub> </mrow>
    δAiIt is differential transforms of the joint coordinate system i relative to coordinate system i-1, then the reality between adjacent two connecting rod of robot is homogeneous Coordinate transformThat is Ai+AiδAi, then robot end's coordinate system relative to basis coordinates system actual homogeneous transformation Matrix TRFor：
    <mrow> <mi>T</mi> <mo>+</mo> <mi>d</mi> <mi>T</mi> <mo>=</mo> <munderover> <mo>&amp;Pi;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> <mo>+</mo> <msub> <mi>dA</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&amp;Pi;</mo> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mrow> <mo>(</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> <mo>+</mo> <msub> <mi>A</mi> <mi>i</mi> </msub> <msub> <mi>&amp;delta;A</mi> <mi>i</mi> </msub> <mo>)</mo> </mrow> </mrow>
    Above formula is deployed, and omits High Order Perturbation item, following formula is obtained after abbreviation：
    <mrow> <mi>&amp;Delta;</mi> <mi>P</mi> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mrow> <msub> <mi>dP</mi> <mi>x</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>dP</mi> <mi>y</mi> </msub> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <msub> <mi>dP</mi> <mi>z</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;alpha;</mi> <mi>x</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>a</mi> <mi>x</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;theta;</mi> <mi>x</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>d</mi> <mi>x</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;beta;</mi> <mi>x</mi> </msub> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;alpha;</mi> <mi>y</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>a</mi> <mi>y</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;theta;</mi> <mi>y</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>d</mi> <mi>y</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;beta;</mi> <mi>y</mi> </msub> </msub> </mtd> </mtr> <mtr> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;alpha;</mi> <mi>z</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>a</mi> <mi>z</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;theta;</mi> <mi>z</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>d</mi> <mi>z</mi> </msub> </msub> </mtd> <mtd> <msub> <mi>J</mi> <msub> <mi>&amp;beta;</mi> <mi>z</mi> </msub> </msub> </mtd> </mtr> </mtable> </mfenced> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mi>&amp;Delta;</mi> <mi>&amp;alpha;</mi> </mtd> </mtr> <mtr> <mtd> <mi>&amp;Delta;</mi> <mi>a</mi> </mtd> </mtr> <mtr> <mtd> <mi>&amp;Delta;</mi> <mi>&amp;theta;</mi> </mtd> </mtr> <mtr> <mtd> <mi>&amp;Delta;</mi> <mi>d</mi> </mtd> </mtr> <mtr> <mtd> <mi>&amp;Delta;</mi> <mi>&amp;beta;</mi> </mtd> </mtr> </mtable> </mfenced> <mo>=</mo> <mi>J</mi> <mi>&amp;Delta;</mi> <mi>X</mi> </mrow>
    Wherein, Δ P=[dPx dPy dPz]TIt is robot location's error matrix, J is the differential transform of 3 × (4n+1) link parameters Jacobian matrix, Δ X=[Δ α Δ a Δ θ Δ d Δs β]TFor the link parameters error matrix of (4n+1) × 1；
    (3) robot kinematics' error model based on biplane constraint is established
    IfFor the nominal position value of i-th of contact point on constraint plane I, robot positive motion can be passed through Learn and directly calculate, JpiFor the Jacobian matrix of the opening position, can be calculated by joint angle angle value, physical location Pi R=Pi N+ JpiΔ X, the then bias vector between adjacent two contact point：
    <mrow> <msubsup> <mi>&amp;Delta;P</mi> <mi>i</mi> <mi>R</mi> </msubsup> <mo>=</mo> <msubsup> <mi>P</mi> <mi>i</mi> <mi>R</mi> </msubsup> <mo>-</mo> <msubsup> <mi>P</mi> <mrow> <mi>i</mi> <mo>-</mo> <mn>1</mn> </mrow> <mi>R</mi> </msubsup> <mo>=</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <mrow> <msubsup> <mi>&amp;Delta;x</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>N</mi> </msubsup> </mrow> </mtd> <mtd> <mrow> <msubsup> <mi>&amp;Delta;y</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>N</mi> </msubsup> </mrow> </mtd> <mtd> <mrow> <msubsup> <mi>&amp;Delta;z</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>N</mi> </msubsup> </mrow> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mo>+</mo> <msub> <mi>&amp;Delta;J</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> </msub> <mi>&amp;Delta;</mi> <mi>X</mi> </mrow>
    Wherein,ΔJpi=Jpi-Jpi-1；
    Similarly,So can structure by two adjacent bias vectors Build one perpendicular to plane I nominal normal vector：
    <mrow> <msub> <mi>&amp;Delta;M</mi> <mi>i</mi> </msub> <mo>=</mo> <msubsup> <mi>&amp;Delta;P</mi> <mi>i</mi> <mi>R</mi> </msubsup> <mo>&amp;times;</mo> <msubsup> <mi>&amp;Delta;P</mi> <mrow> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>R</mi> </msubsup> <mo>=</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>n</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>n</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>n</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mo>+</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>J</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>J</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>J</mi> <mrow> <mi>p</mi> <mi>i</mi> </mrow> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mi>&amp;Delta;</mi> <mi>X</mi> </mrow>
    Constraint plane II is perpendicular with constraint plane I (parallel),For the nominal position value of i-th of contact point, then by adjacent Two bias vectors can build one perpendicular to plane II nominal normal vector：
    <mrow> <msub> <mi>&amp;Delta;N</mi> <mi>i</mi> </msub> <mo>=</mo> <msubsup> <mi>&amp;Delta;Q</mi> <mi>i</mi> <mi>R</mi> </msubsup> <mo>&amp;times;</mo> <msubsup> <mi>&amp;Delta;Q</mi> <mrow> <mi>i</mi> <mo>+</mo> <mn>1</mn> </mrow> <mi>R</mi> </msubsup> <mo>=</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>n</mi> <mrow> <mi>q</mi> <mi>i</mi> </mrow> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>n</mi> <mrow> <mi>q</mi> <mi>i</mi> </mrow> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>n</mi> <mrow> <mi>q</mi> <mi>i</mi> </mrow> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mo>+</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>J</mi> <mrow> <mi>q</mi> <mi>i</mi> </mrow> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>J</mi> <mrow> <mi>q</mi> <mi>i</mi> </mrow> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>J</mi> <mrow> <mi>q</mi> <mi>i</mi> </mrow> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mi>&amp;Delta;</mi> <mi>X</mi> </mrow>
    If plane I is vertical with plane II, then：
    <mrow> <msub> <mi>&amp;Delta;M</mi> <mi>i</mi> </msub> <mo>&amp;CenterDot;</mo> <msub> <mi>&amp;Delta;N</mi> <mi>i</mi> </msub> <mo>=</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>s</mi> <mi>i</mi> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>s</mi> <mi>i</mi> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>s</mi> <mi>i</mi> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mo>+</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>h</mi> <mi>i</mi> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>h</mi> <mi>i</mi> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>h</mi> <mi>i</mi> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mi>&amp;Delta;</mi> <mi>X</mi> <mo>=</mo> <mn>0</mn> </mrow>
    If plane I is parallel with plane II, then：
    <mrow> <msub> <mi>&amp;Delta;M</mi> <mi>i</mi> </msub> <mo>&amp;times;</mo> <msub> <mi>&amp;Delta;N</mi> <mi>i</mi> </msub> <mo>=</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>s</mi> <mi>i</mi> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>s</mi> <mi>i</mi> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>s</mi> <mi>i</mi> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mo>+</mo> <msup> <mfenced open = "[" close = "]"> <mtable> <mtr> <mtd> <msubsup> <mi>h</mi> <mi>i</mi> <mi>x</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>h</mi> <mi>i</mi> <mi>y</mi> </msubsup> </mtd> <mtd> <msubsup> <mi>h</mi> <mi>i</mi> <mi>z</mi> </msubsup> </mtd> </mtr> </mtable> </mfenced> <mi>T</mi> </msup> <mi>&amp;Delta;</mi> <mi>X</mi> <mo>=</mo> <mn>0</mn> </mrow>
    (4) driving robot measures respectively to related constraint plane
    Driving robot carries out contact type measurement respectively to constraint plane I, II, when measurement head exports activation signal, remembers immediately The current each joint angle angle value of record, and next obligatory point is measured, after gathering a number of point, then have：
    H Δs X+S=0
    Wherein,3N can then be produced Equation；
    (5) robot links parameter identification
    By improved least square method, robot kinematics' parameter error is recognized, it is as follows：
    Δ X=- (HTH+μI)-1HTS
    (6) demarcation checking
    Robot kinematics' parameter offset that identification obtains in step (5) is updated in robot controller software, again Teaching several points, compare whether robot theory terminal position is constrained in a plane, if it is not, then continue step (4), (5), (6), until meeting the required precision reached required for system.
  2. 2. a kind of robot self-calibrating method based on biplane constraint error model according to claim 1, its feature It is：Error model is simultaneously related to the obligatory point in two planes.
  3. 3. a kind of robot self-calibrating method based on biplane constraint error model according to claim 1 and 2, it is special Sign is：It is that stated accuracy is ensured by the flatness, perpendicularity and the depth of parallelism of constraint plane.
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Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108406771A (en) * 2018-03-09 2018-08-17 江南大学 A kind of plane restriction error model and robot self-calibrating method
CN108638060A (en) * 2018-05-03 2018-10-12 大连理工大学 Nuisance parameter analyzes elimination method in multi-freedom robot parameter calibration
CN108759822A (en) * 2018-04-12 2018-11-06 江南大学 A kind of mobile robot 3D positioning systems
CN109773786A (en) * 2018-12-29 2019-05-21 南京埃斯顿机器人工程有限公司 A kind of industrial robot plane precision scaling method
CN110370271A (en) * 2019-04-30 2019-10-25 杭州亿恒科技有限公司 The joint transmission ratio error calibration method of industrial serial manipulator
CN110722562A (en) * 2019-10-28 2020-01-24 华中科技大学 Space Jacobian matrix construction method for machine ginseng number identification
CN110757450A (en) * 2019-09-06 2020-02-07 南京邮电大学 Shoulder joint rehabilitation robot parameter calibration method

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6754370B1 (en) * 2000-08-14 2004-06-22 The Board Of Trustees Of The Leland Stanford Junior University Real-time structured light range scanning of moving scenes
CN104608129A (en) * 2014-11-28 2015-05-13 江南大学 Planar constraint based robot calibration method
CN105066808A (en) * 2015-07-14 2015-11-18 安徽工业大学 Simple calibration device for kinematic parameter of industrial robot and calibration method thereof

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6754370B1 (en) * 2000-08-14 2004-06-22 The Board Of Trustees Of The Leland Stanford Junior University Real-time structured light range scanning of moving scenes
CN104608129A (en) * 2014-11-28 2015-05-13 江南大学 Planar constraint based robot calibration method
CN105066808A (en) * 2015-07-14 2015-11-18 安徽工业大学 Simple calibration device for kinematic parameter of industrial robot and calibration method thereof

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
董慧颖等: "一种基于平面精度的机器人标定方法及仿真", 《中国机械工程》 *
齐飞: "基于平面约束的工业机器人误差补偿技术研究", 《信息科技辑》 *

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108406771B (en) * 2018-03-09 2021-03-16 江南大学 Robot self-calibration method
CN108406771A (en) * 2018-03-09 2018-08-17 江南大学 A kind of plane restriction error model and robot self-calibrating method
CN108759822A (en) * 2018-04-12 2018-11-06 江南大学 A kind of mobile robot 3D positioning systems
CN108759822B (en) * 2018-04-12 2021-04-30 江南大学 Mobile robot 3D positioning system
CN108638060A (en) * 2018-05-03 2018-10-12 大连理工大学 Nuisance parameter analyzes elimination method in multi-freedom robot parameter calibration
CN108638060B (en) * 2018-05-03 2021-09-28 大连理工大学 Method for analyzing and rejecting redundant parameters in multi-degree-of-freedom machine ginseng number calibration
CN109773786A (en) * 2018-12-29 2019-05-21 南京埃斯顿机器人工程有限公司 A kind of industrial robot plane precision scaling method
CN109773786B (en) * 2018-12-29 2022-04-19 南京埃斯顿机器人工程有限公司 Industrial robot plane precision calibration method
CN110370271A (en) * 2019-04-30 2019-10-25 杭州亿恒科技有限公司 The joint transmission ratio error calibration method of industrial serial manipulator
CN110757450A (en) * 2019-09-06 2020-02-07 南京邮电大学 Shoulder joint rehabilitation robot parameter calibration method
CN110757450B (en) * 2019-09-06 2022-05-17 南京邮电大学 Shoulder joint rehabilitation robot parameter calibration method
CN110722562B (en) * 2019-10-28 2021-03-09 华中科技大学 Space Jacobian matrix construction method for machine ginseng number identification
CN110722562A (en) * 2019-10-28 2020-01-24 华中科技大学 Space Jacobian matrix construction method for machine ginseng number identification

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