Mechanism-parameter-calibration method for robotic arm system
10596706 ยท 2020-03-24
Assignee
Inventors
Cpc classification
B25J9/1633
PERFORMING OPERATIONS; TRANSPORTING
B25J9/161
PERFORMING OPERATIONS; TRANSPORTING
G05B2219/39048
PHYSICS
B25J9/1674
PERFORMING OPERATIONS; TRANSPORTING
International classification
Abstract
A mechanism-parametric-calibration method for a robotic arm system is provided, including: controlling the robotic arm to perform a plurality of actions so that one end of the robotic arm moves toward corresponding predictive positioning-points; determining a predictive relative-displacement between each two of the predictive positioning-points; after each of the actions is performed, sensing three-dimensional positioning information of the end of the robotic arm; determining, according to the three-dimensional positioning information, a measured relative-displacement moved by the end of the robotic-arm when each two of the actions are performed; deriving an equation corresponding to the robotic arm from the predictive relative-displacements and the measured relative-displacements; and utilizing a feasible algorithm to find the solution of the equation. When an ambient temperature changes or a stress variation on the robotic arm exceeds a predetermined range, re-obtaining the set of mechanism parametric deviations corresponds to a current robot configuration.
Claims
1. A mechanism-parametric-calibration method for a robotic arm system, wherein the robotic arm system comprises a robotic arm and a measuring instrument, and the mechanism-parametric-calibration method comprises: controlling, according to n mechanism parameter sets, the robotic arm performing n actions so that an end of the robotic arm moves toward n corresponding predictive positioning-points; determining a predictive relative-displacement equation of each two of the n predictive positioning-points; sensing, using the measuring instrument, three-dimensional measured positioning-points corresponding to the end of the robotic arm after the robotic arm performs each of the n actions; determining, according to the n three-dimensional measured positioning-points, a measured relative-displacement moved by the end of the robotic arm when the robotic arm performs each two of the n actions; deriving an optimization equation corresponding to the robotic arm from the predictive relative-displacement equations and the measured relative-displacements; obtaining, by the optimization equation, a set of mechanism parametric deviations of the robotic arm; and calibrating, by the set of mechanism parametric deviations, the n mechanism parameter sets of the robotic arm; wherein the optimization equation for a specific status of the robotic arm is presented as:
N=N.sub.HSN.sub.PRN.sub.MDN.sub.PLN.sub.AT.
2. The mechanism-parametric-calibration method as claimed in claim 1, further comprising: obtaining, by the optimization equation, a plurality of sets of mechanism parametric deviations corresponding to each combination of factors causing the change of stress variation or causing a thermal expansion effect on the robotic arm.
3. The mechanism-parametric-calibration method as claimed in claim 1, wherein the hand systems are geometrically defined from all solutions of inverse kinematics for the robotic arm.
4. The mechanism-parametric-calibration method as claimed in claim 1, wherein different gravity directions are caused by mounting the robotic arm on a platform parallel to the ground in an upright manner, mounting the robotic arm on the platform parallel to the ground in a upside down manner, mounting the robotic arm on a platform perpendicular to the ground, or mounting the robotic arm on a platform that has any angle to the ground.
5. A mechanism-parametric-calibration method for a robotic arm system, the robotic arm system comprising a robotic arm, a calibration block and a measuring instrument, wherein the mechanism-parametric-calibration method comprises: controlling, according to nx mechanism parameter sets corresponding to nx first-direction predictive positioning-points, the robotic arm performing nx actions such that an end of the robotic arm moves toward the nx first-direction predictive positioning-points which are in front of a first precision plane of the calibration block, wherein the first precision plane is perpendicular to a first direction; sensing, using the measuring instrument, a first-direction measured displacement between the first precision plane and the end of the robotic arm when the robotic arm performs each of the nx actions; determining, according to the nx first-direction measured displacement, a first-direction measured relative-displacement moved by the end of the robotic arm when the robotic arm performs each two of the nx actions; determining a first-direction predictive relative-displacement equation of each two of the nx first-direction predictive positioning-points; deriving an optimization equation corresponding to the robotic arm from the first-direction predictive relative-displacement equations and the first-direction measured relative-displacements; obtaining, by the optimization equation, a set of mechanism parametric deviations of the robotic arm; and calibrating, by the set of mechanism parametric deviations, the nx mechanism parameter sets corresponding to the nx first-direction predictive positioning-points of the robotic arm; wherein when an ambient temperature of the robotic arm changes or a stress variation on the robotic arm exceeds a predetermined range, re-obtaining the set of mechanism parametric deviations corresponding to a current robot configuration of the robotic arm by the optimization equation; wherein the factors causing the change of the stress variation of the robotic arm comprise hand systems, positioning regions, gravity directions, and payloads; and wherein when the robotic arm has N.sub.HS hand systems, N.sub.PR positioning regions, N.sub.MD mounting directions, N.sub.PL payloads, and N.sub.AT ambient temperatures, the total number N of sets of mechanism parametric deviations for each robot configurations is obtain by the following equation:
N=N.sub.HSN.sub.PRN.sub.MDN.sub.PLN.sub.AT.
6. The mechanism-parametric-calibration method as claimed in claim 5, further comprising: obtaining, by the optimization equation, a plurality of sets of mechanism parametric deviations corresponding to each combination of factors causing the change of stress variation or causing a thermal expansion effect on the robotic arm.
7. The mechanism-parametric-calibration method as claimed in claim 5, wherein the hand systems are geometrically defined from all solutions of inverse kinematics for the robotic arm.
8. The mechanism-parametric-calibration method as claimed in claim 5, wherein different gravity directions are caused by mounting the robotic arm on a platform parallel to the ground in an upright manner, mounting the robotic arm on the platform parallel to the ground in a upside down manner, mounting the robotic arm on a platform perpendicular to the ground, or mounting the robotic arm on a platform that has any angle to the ground.
9. The mechanism-parametric-calibration method as claimed in claim 5, further comprising: when a first-direction pitch between an out-of-range first-direction predictive positioning-point and the first precision plane exceeds a maximum sensing distance of the measuring instrument in the first direction, controlling the robotic arm so that the end of the robotic arm moves toward the out-of-range first-direction predictive positioning-point which is in front of a second precision plane of the calibration block to sense the first-direction measured displacement between the end of the robotic arm and the second precision plane, wherein the second precision plane is perpendicular to the first direction; and determining the first-direction measured relative-displacements according to a first-direction displacement parameter and the first-direction measured displacements, wherein the first precision plane and the second precision plane are the first-direction displacement parameter apart.
10. The mechanism-parametric-calibration method as claimed in claim 5, wherein the optimization equation is
11. The mechanism-parametric-calibration method as claimed in claim 5, further comprising: controlling, according to ny mechanism parameter sets corresponding to ny second-direction predictive positioning-points, the robotic arm performing ny actions so that the end of the robotic arm moves toward the ny second-direction predictive positioning-points which are in front of a third precision plane of the calibration block, wherein the third precision plane is perpendicular to a second direction; sensing, using the measuring instrument, a second-direction measured displacement between the third precision plane and the end of the robotic arm when the robotic arm performs each of the ny actions; determining, according to the ny second-direction measured displacement, a second-direction measured relative-displacement moved by the end of the robotic arm when the robotic arm performs each two of the ny actions; determining a second-direction predictive relative-displacement equation of each two of the ny second-direction predictive positioning-points; and deriving the optimization equation corresponding to the robotic arm from the first-direction predictive relative-displacement equations, the first-direction measured relative-displacements, the second-direction predictive relative-displacement equations and the second-direction measured relative-displacements.
12. The mechanism-parametric-calibration method as claimed in claim 11, wherein the optimization equation is
13. The mechanism-parametric-calibration method as claimed in claim 11, further comprising: when a first-direction pitch between an out-of-range first-direction predictive positioning-point and the first precision plane exceeds the maximum sensing distance of the measuring instrument in the first direction, controlling the robotic arm so that the end of the robotic arm moves toward the out-of-range first-direction predictive positioning-point which is in front of a second precision plane of the calibration block to sense the first-direction measured displacement between the end of the robotic arm and the second precision plane, wherein the second precision plane is perpendicular to the first direction; when a second-direction pitch between an out-of-range second-direction predictive positioning-point and the third precision plane exceeds the maximum sensing distance of the measuring instrument in the second direction, controlling the robotic arm so that the end of the robotic arm moves toward the out-of-range second-direction predictive positioning-point which is in front of a fourth precision plane of the calibration block to sense the second-direction measured displacement between the end of the robotic arm and the fourth precision plane, wherein the fourth precision plane is perpendicular to the second direction; determining the first-direction measured relative-displacements according to a first-direction displacement parameter and the first-direction measured displacements; and determining the second-direction measured relative-displacements according to a second-direction displacement parameter and the second-direction measured displacements, wherein the first precision plane and the second precision plane are the first-direction displacement parameter apart; and wherein the third precision plane and the fourth precision plane are the second-direction displacement parameter apart.
14. The mechanism-parametric-calibration method as claimed in claim 5, further comprising: controlling, according to ny mechanism parameter sets corresponding to ny second-direction predictive positioning-points, the robotic arm performing ny actions so the end of the robotic arm moves toward the ny second-direction predictive positioning-points which are in front of a third precision plane of the calibration block, wherein the third precision plane is perpendicular to the second direction; controlling, according to nz mechanism parameter sets corresponding to nz third-direction predictive positioning-points, the robotic arm performing nz actions so the end of the robotic arm moves toward the nz third-direction predictive positioning-points which are in front of a fifth precision plane of the calibration block, wherein the fifth precision plane is perpendicular to a third direction; sensing, using the measuring instrument, a second-direction measured displacement between the third precision plane and the end of the robotic arm when the robotic arm performs each of the ny actions; determining, according to the ny second-direction measured displacements, a second-direction measured relative-displacement moved by the end of the robotic arm when the robotic arm performs each two of the ny actions; sensing, using the measuring instrument, a third-direction measured displacement between the fifth precision plane and the end of the robotic arm when the robotic arm performs each of the nz actions; determining, according to the nz third-direction measured displacement, a third-direction measured relative-displacement moved by the end of the robotic arm when the robotic atm performs each two of the nz actions; determining a second-direction predictive relative-displacement equation of each two of the ny second-direction predictive positioning-points and determining a third-direction predictive relative-displacement equation of each two of the nz third-direction predictive positioning-points; and deriving the optimization equation corresponding to the robotic arm from the first-direction predictive relative-displacement equations, the first-direction measured relative-displacements, the second-direction predictive relative-displacement equations, the second-direction measured relative-displacements, the third-direction predictive relative-displacement equations and the third-direction measured relative-displacements.
15. The mechanism-parametric-calibration method as claimed in claim 14, wherein the optimization equation is
16. The mechanism-parametric-calibration method as claimed in claim 14, further comprising: when a first-direction pitch between an out-of-range first-direction predictive positioning-point and the first precision plane exceeds the maximum sensing distance of the measuring instrument in the first direction, controlling the robotic arm so that the end of the robotic arm moves toward the out-of-range first-direction predictive positioning-point which is in front of a second precision plane of the calibration block to sense the first-direction measured displacement between the end of the robotic arm and the second precision plane, wherein the second precision plane is perpendicular to the first direction; when a second-direction pitch between an out-of-range second-direction predictive positioning-point and the third precision plane exceeds the maximum sensing distance of the measuring instrument in the second direction, controlling the robotic arm so that the end of the robotic arm moves toward the out-of-range second-direction predictive positioning-point which is in front of a fourth precision plane of the calibration block to sense the second-direction measured displacement between the end of the robotic arm and the fourth precision plane, wherein the fourth precision plane is perpendicular to the second direction; when a third-direction pitch between an out-of-range third-direction predictive positioning-point and the fifth precision plane exceeds the maximum sensing distance of the measuring instrument in the third direction, controlling the robotic arm so that the end of the robotic arm moves toward the out-of-range third-direction predictive positioning-point which is in front of a sixth precision plane of the calibration block to sense the third-direction measured displacement between the end of the robotic arm and the sixth precision plane, wherein the sixth precision plane is perpendicular to the third direction; determining the first-direction measured relative-displacements according to a first-direction displacement parameter and the first-direction measured displacements; and determining the second-direction measured relative-displacements according to a second-direction displacement parameter and the second-direction measured displacements; and determining the third-direction measured relative-displacements according to a third-direction displacement parameter and the third-direction measured displacements, wherein the first precision plane and the second precision plane are the first-direction displacement parameter apart; wherein the third precision plane and the fourth precision plane are the second-direction displacement parameter apart; and wherein the fifth precision plane and the sixth precision plane are the third-direction displacement parameter apart.
17. The mechanism-parametric-calibration method as claimed in claim 5, wherein the measuring instrument comprises a measuring instrument used for sensing one-dimensional displacements, a measuring instrument used for sensing two-dimensional displacements, or a measuring instrument used for sensing three-dimensional displacements.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
(1) The present disclosure can be more fully understood by reading the subsequent detailed description and examples with references made to the accompanying drawings, wherein:
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DETAILED DESCRIPTION OF THE INVENTION
(14) The following description is of the best-contemplated mode of carrying out the present disclosure. This description is made for the purpose of illustrating the general principles of the present disclosure and should not be taken in a limiting sense. The scope of the present disclosure is best determined by reference to the appended claims
(15) Terms used in this disclosure: Ppredictive positioning-point of the mathematical model Smechanism parameter set Nabsolute measured positioning-point Pposition deviation Sset of mechanism parametric deviations P.sub.k, k=1, . . . , npredictive positioning-points S.sub.k, k=1, . . . , nmechanism parameter sets corresponding to the predictive positioning-points P.sub.i,j, i=1, . . . , n1, j=i+1, . . . , npredictive relative-displacement M.sub.k, k=1, . . . , nthree-dimensional measured positioning-point M.sub.i,j, i=1, . . . , n1, j=i+1, . . . , nmeasured relative-displacement G(S.sub.i,S.sub.j,S)predictive relative-displacement equation g.sub.x(S.sub.i,S.sub.j,S)first-direction predictive relative-displacement equation g.sub.y(S.sub.i,S.sub.j,S)second-direction predictive relative-displacement equation g.sub.z(S.sub.i,S.sub.j,S)third-direction predictive relative-displacement xS.sub.k, k=1, . . . , nxmechanism parameter sets corresponding to the first-direction predictive positioning-points yS.sub.k, k=1, . . . , nymechanism parameter sets corresponding to the second-direction predictive positioning-points zS.sub.k, k=1, . . . , nzmechanism parameter sets corresponding to the third-direction predictive positioning-points xP.sub.k, k=1, . . . , nxfirst-direction predictive positioning-points yP.sub.k, k=1, . . . , nzsecond-direction predictive positioning-points zP.sub.k, k=1, . . . , nzthird-direction predictive positioning-points xP.sub.i,j, i=1, . . . , nx1, j=i+1, . . . , nxfirst-direction predictive relative-displacement yP.sub.i,j, i=1, . . . , ny1, j=i+1, y1,second-direction predictive relative-displacement zP.sub.i,j, i=1, . . . , nz1, j=i+1, z1,third-direction predictive relative-displacement G(xS.sub.i,xS.sub.j,S)three-dimensional predictive relative displacement equation corresponding to the first-direction predictive positioning-points g.sub.x(xS.sub.i,xS.sub.j,S)first-direction predictive relative-displacement equations corresponding to the first-direction predictive positioning-points g.sub.y(xS.sub.i,xS.sub.j,S)second direction predictive relative-displacement equations corresponding to the first-direction predictive positioning-points g.sub.z(xS.sub.i,xS.sub.j,S)third direction predictive relative-displacement equations corresponding to the first-direction predictive positioning-points G(yS.sub.i,yS.sub.j,S)three-dimensional predictive relative-displacement equation corresponding to the second-direction predictive positioning-points g.sub.x(yS.sub.i,yS.sub.j,S)first-direction predictive relative-displacement equations corresponding to the second-direction predictive positioning-points g.sub.y(yS.sub.i,yS.sub.j,S)second-direction predictive relative-displacement equations corresponding to the second-direction predictive positioning-points g.sub.z(yS.sub.i,yS.sub.j,S)third-direction predictive relative-displacement equations corresponding to the second-direction predictive positioning-points G(zS.sub.i,zS.sub.jS)three-dimensional predictive relative-displacement equation corresponding to the third-direction predictive positioning-points g.sub.x(zS.sub.i,zS.sub.j,S)first-direction predictive relative-displacement equations corresponding to the third-direction predictive positioning-points g.sub.y(zS.sub.i,zS.sub.j,S)second-direction predictive relative-displacement equations corresponding to the third-direction predictive positioning-points g.sub.z(zS.sub.i,zS.sub.j,S)third-direction predictive relative-displacement equations corresponding to the third-direction predictive positioning-points xMx.sub.i,j, i=1, . . . , nx1, j=i+1, . . . , nxfirst-direction measured relative-displacement corresponding to the first-direction predictive positioning-points xP.sub.i and xP.sub.j yMy.sub.i,j, i=1, . . . , ny1, j=i+1, . . . , nysecond-direction measured relative-displacements corresponding to the second-direction predictive positioning-points yP.sub.i and yP.sub.j zMz.sub.i,j, i=1, . . . , nz1, j=i+1, . . . , nzthird-direction measured relative-displacement corresponding to the second-direction predictive positioning-points zP.sub.i and zP.sub.j xMx.sub.k, k=1, . . . , nxfirst-direction measured displacement yMy.sub.k, k=1, . . . , nysecond-direction measured displacement zMz.sub.k, k=1, . . . , nzthird-direction measured displacement Dx, Dy, Dzfirst-direction displacement parameter, second-direction displacement parameter, third-direction displacement parameter
(16)
(17) In
PF(S+S)
(18) Wherein the mechanism parameter set S is, but not limited thereto, a set of the size (arm length) of mechanical links, the connection orientations and angles between joint axes, the amount of joint variables, and other geometric variables of the robotic arm 21, and the set of mechanism parametric deviations S is prepared for compensating for the mechanism parameter set S after calibration.
(19) In
P.sub.kF(S.sub.k+S),k=1, . . . ,n
(20) Wherein the mechanism parameter sets S.sub.1S.sub.n comprise the size (arm length) of mechanical links the connection orientations and angles between joint axes, the amount of joint variables, and other geometric variables.
(21) In
(22) In
(23)
(24) In
(25) In
M.sub.i,j=M.sub.jM.sub.i,i=1, . . . ,n1,j=i+1, . . . ,n
(26) That is, the three-dimensional positioning information includes the three-dimensional measured positioning-points M.sub.1M.sub.i,j and the measured relative-displacements M.sub.i,j.
(27) In
(28) Then the calibrating calculation unit 241 of the processing unit 24 calculates the optimization equation corresponding, to the robotic arm 21 according to the predictive relative-displacement equations G(S.sub.1,S.sub.j,S) and the measured relative-displacements M.sub.i,j, and the optimization equation is represented below:
(29)
(30) Then the processing unit 24 of the robotic arm system 20 utilizes an optimization algorithm and the optimization equation to obtain a set of mechanism parametric deviations S. Finally, the processing unit 24 of the robotic arm system 20 uses the set of mechanism parametric deviations S to calibrate the mechanism parameter sets S.sub.1S.sub.n of the robotic arm 21.
(31) It should be noted that, among the choices of the optimization algorithm of the robotic arm system 20, the processing unit 24 can be adopted an optimization algorithm a non-linear equation. Because the predictive relative-displacement equation G(S.sub.1,S.sub.j,S) used for calculating the predictive relative-displacement P.sub.i,j of the robotic arm 21 is almost equivalent to the robot non-linear mathematical model, the approximation error of the predictive relative-displacement equation G(S.sub.1,S.sub.j,S) is extremely small. Accordingly, the optimization convergence effect of the set of mechanism parametric deviations S obtained by the optimization equation of the robotic arm system 20 is greater than the optimization convergence effect of the set of mechanism parametric deviations S obtained by the optimization equation of the robotic arm system 10.
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(34) In
(35) In
(36) In
(37) In
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Wherein g.sub.x(xS.sub.i,xS.sub.j,S), g.sub.y(xS.sub.i,xS.sub.j,S) and g.sub.z(xS.sub.i,xS.sub.j,S) are respectively a first-direction predictive relative-displacement equation, a second-direction predictive relative-displacement equation, and a third-direction predictive relative-displacement equation corresponding to the two first-direction predictive positioning-points xP.sub.i and xP.sub.j.
(39) In
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Wherein g.sub.x(yS.sub.i,yS.sub.j,S), g.sub.y(yS.sub.i,yS.sub.j,S) and g.sub.z(yS.sub.i,yS.sub.j,S) are respectively a first-direction predictive relative-displacement equation, a second-direction predictive relative-displacement equation, and a third-direction predictive relative-displacement equation corresponding to the two second-direction predictive positioning-points yP.sub.i and yP.sub.j.
(41) In
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Wherein g.sub.x(zS.sub.i,zS.sub.j,S), g.sub.y(zS.sub.i,zS.sub.j,S) and g.sub.z(zS.sub.i,zS.sub.j,S) are respectively a first-direction predictive relative-displacement equation, a second-direction predictive relative-displacement equation, and a third-direction predictive relative-displacement equation corresponding to the two third-direction predictive positioning-points zP.sub.i and zP.sub.j.
(43) In
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(45) Then the processing unit 44 of the robotic arm system 40 utilizes an optimization algorithm and the optimization equation to obtain a set of optimal mechanism parametric deviations S. Finally, the processing unit 44 of the robotic arm system 40 uses the set of optimal mechanism parametric deviations S to calibrate the mechanism parameter sets xS.sub.1xS.sub.nx corresponding to the first-direction predictive positioning-points xP.sub.1xP.sub.nx, the mechanism parameter sets yS.sub.1yS.sub.ny corresponding to the second-direction predictive positioning-points yP.sub.1yP.sub.ny and the mechanism parameter sets zS.sub.1zS.sub.nz corresponding to the third-direction predictive positioning-points zP.sub.1zP.sub.nz of the robotic arm 41.
(46) In another embodiment of the present disclosure, the robotic arm system 40 performs only one-dimensional measurement and calculation and obtains a corresponding optimization equation . The one dimension comprises the X-direction, Y-direction or Z-direction. E.g. the robotic arm system 40 only performs X-direction measurement and calculation. In this case, the calibrating calculation unit 441 of the processing unit 44 calculates the optimization equation of the robotic arm 41 according to the first-direction predictive relative-displacement equations g.sub.x(xS.sub.i,xS.sub.j,S) and the first-direction measured relative-displacements xMx.sub.i,j corresponding to the first-direction predictive positioning-points. The optimization equation is represented below:
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(48) In this case, the processing unit 44 of the robotic arm system 40 also utilizes an optimization algorithm and the optimization equation of X-direction to obtain a set of optimal mechanism parametric deviations S. Finally, the processing unit 44 of the robotic arm system 40 uses the set of optimal mechanism parametric deviations S to calibrate the mechanism parameter sets xS.sub.1xS.sub.nx corresponding to the first-direction predictive positioning-points xP.sub.1xP.sub.nx of the robotic arm 41.
(49) In another embodiment of the present disclosure, the robotic arm system 40 performs measurement and calculation in only two dimensions and obtains a corresponding optimization equation . The two dimensions may comprise the X-direction and Y-direction, the Y-direction and Z-direction, or the X-direction and Z-direction. E.g. the robotic arm system 40 performs measurement and calculation in only first and second directions (the X-direction and Y-direction). In this case, the calibrating calcination unit 441 of the processing unit 44 calculates an optimization equation of the robotic arm 41 according to the first-direction predictive relative-displacement equations g.sub.x(xS.sub.i,xS.sub.j,S) and the first-direction measured relative-displacements xMx.sub.i,j corresponding to the first-direction predictive positioning-points and the second-direction predictive relative-displacement equation g.sub.y(yS.sub.i,yS.sub.j,S) and the second-direction measured relative-displacements yMy.sub.i,j corresponding to the second-direction predictive positioning-points. The optimization equation is represented below:
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(51) In this case, the processing unit 44 of the robotic arm system 40 also utilizes an optimization algorithm, and the optimization equation of X-direction and Y-direction to obtain a set of optimal mechanism parametric deviations S. Finally, the processing unit 44 of the robotic arm system 40 uses the set of optimal mechanism parametric deviations S to calibrate the mechanism parameter sets xS.sub.1xS.sub.nx corresponding to the first-direction predictive positioning-points xP.sub.1xP.sub.nx and the mechanism parameter sets yS.sub.1yS.sub.ny corresponding to the second-direction predictive positioning-points yP.sub.1yP.sub.ny of the robotic arm 41.
(52) It should be noted that, in the chokes of the optimization algorithm of the robotic arm system 40, the processing unit 44 adopts the optimization algorithm with a non-linear equation. Because the first-direction predictive relative-displacement equations g.sub.x(xS.sub.i,xS.sub.j,S), the second-direction predictive relative-displacement equation g.sub.y(yS.sub.i,yS.sub.j,S) and the third-direction predictive relative-displacement equation g.sub.z(zS.sub.i,zS.sub.j,S) used for calculating the robotic arm 41 are almost equivalent to the robot non-linear mathematical model, approximation errors of g.sub.x(xS.sub.i,xS.sub.j,S), g.sub.y(yS.sub.i,yS.sub.j,S) and g.sub.z(zS.sub.i,zS.sub.j,S) are extremely small. Accordingly, the optimization convergence effect of the set of mechanism parametric deviations S obtained by the optimization equation of the robotic arm system 40 is greater than the optimization convergence effect of the set of mechanism parametric deviations S obtained by the optimization equation of the robotic arm system 10.
(53) Finally, it should be noted that the optimization algorithm utilized in the robotic arm system 20 and the robotic arm system 40 comprises the Least-Squares method, Gradient-Descent method, Gauss-Newton method or Levenberg-Marquardt method, but the present disclosure is not limited thereto.
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(58) Accordingly, the calibration calculation unit 541 of the processing unit 54 calculates the first-direction predictive relative-displacement equations g.sub.x(xS.sub.i,xS.sub.j,S) corresponding to the first-direction predictive positioning-points.
(59) In
(60) The calibration calculation unit 541 determines, according to the first-direction measured displacements xMx.sub.k, a first-direction measured relative-displacement xMx.sub.i,j, i=1, . . . , nx1, j=i+1, . . . , nx moved by the end of the robotic arm 51 while performing each two of the actions.
(61) In
(62) In
xMx.sub.i,j=xMx.sub.jxMx.sub.i+Dx.Math.i=1, . . . ,nx1,j=i+1, . . . ,nx
Wherein if the first-direction measured displacements xMx.sub.i and xMx.sub.j are measured by the same precision plane (e.g. both measured by the first precision plane C1), then the value of Dx is 0. If the first-direction measured displacements xMx.sub.i and xMx.sub.j are measured by two parallel precision planes (e.g. measured by the first precision plane C1 and the second precision plane C2), then Dx is a first-direction relative displacement between the two parallel precision planes.
(63) In
(64) When a first-direction pitch between an out-of-range first-direction predictive positioning-point xP.sub.k and the first precision plane C1 exceeds the maximum sensing range of the measuring instrument 55 in the first direction, the processing unit 54 controls the robotic arm 51 so that the end of the robotic arm 51 moves toward the out-of-range first-direction predictive positioning-point xP.sub.k which is in front of the second precision plane C2 of the calibration block 56 to sense the first-direction measured displacement xMx.sub.i,j between the end of the robotic arm 51 and the first precision plane C1. Through the method of adding a boundary plane, the first-direction measured relative-displacement xMx.sub.i,j corresponding to the first-direction predictive positioning-points xP.sub.i and xP.sub.j is not limited to the sensing range of the measuring instrument 55.
(65) Unlike the measuring, instrument 25 illustrated in
(66) In the same manner, the measuring instrument 55 of the robotic arm system 50 measures, through the third precision plane C3 and the fourth precision plane C4, the second-direction predictive positioning-points yP.sub.k, k=1, . . . , ny (yP.sub.1yP.sub.ny) to obtain the second-direction measured relative-displacements yMy.sub.i,j, i=1, . . . , ny1, j=i+1, . . . , ny corresponding to the second-direction predictive positioning-points yP.sub.i and yP.sub.j. The processing unit 54 obtains the second-direction predictive relative-displacement equation g.sub.y(yS.sub.i,yS.sub.j,S) according to the mechanism parameter sets yS.sub.1yS.sub.ny.
(67) Similarly, the processing unit 54 obtains the third-direction predictive relative-displacement equation g.sub.z(xS.sub.1,zS.sub.j,S) according to the mechanism parameter sets zS.sub.1zS.sub.nz. The measuring instrument 55 also measures, through the fifth precision plane C5 and the sixth precision plane C6, the third-direction predictive positioning-points zP.sub.k, k=1, . . . , nz (zP.sub.1zP.sub.nz) to obtain the third-direction measured relative-displacements zMz.sub.i,j, i=1, . . . , nz1, j=i+1, . . . , nz corresponding to the third-direction predictive positioning-points zP.sub.1 and zP.sub.j.
(68) Then the calibration calculation unit 541 of the processing unit 54 calculates an optimization equation according to g.sub.x(xS.sub.i,xS.sub.j,S), xMx.sub.i,j, g.sub.y(yS.sub.i,yS.sub.j,S), yMy.sub.i,j, g.sub.z(zS.sub.i,zS.sub.j,S) and zMz.sub.i,j.
(69) Then the processing unit 54 of the robotic arm system 50 also utilizes an optimization algorithm and the optimization equation to obtain a set of optimal mechanism parametric deviations S. Finally, the processing unit 54 of the robotic arm system 50 uses the set of optimal mechanism parametric deviations S to calibrate the mechanism parameter sets xP.sub.1xS.sub.nx corresponding to the first-direction predictive positioning-points xP.sub.1xP.sub.nx, the mechanism parameter sets yS.sub.1yS.sub.ny corresponding to the second-direction predictive positioning-points yP.sub.1yP.sub.ny and the mechanism parameter sets zS.sub.1zS.sub.nz corresponding to the third-direction predictive positioning-points zP.sub.1zP.sub.nz of the robotic arm 51.
(70)
(71) In
(72) Because the first-direction predictive positioning-points xP.sub.4 and xP.sub.5 with respect to the first precision plane C1 are located out of sensing range of the measuring instrument 55, the measuring instrument 55 measures the first-direction measured displacements xMx.sub.4,xMx.sub.5 between the end of the robotic arm 51 and the second precision plane C2. The processing unit 54 respectively determines the first-direction measured relative-displacement xMx.sub.5,4 (i.e. xMx.sub.xxMx.sub.41) corresponding to the first-direction predictive relative-displacement xP.sub.4,5 according to the first-direction measured displacements xMx.sub.4 and xMx.sub.6.
(73) In
xMx.sub.i,j=xMx.sub.jxMx.sub.i+Dx,i=1,2,3,j=4,5
(74)
(75) In
(76) Similarly, using the same measuring method used in
(77)
(78) In step S804, the processing unit 44 of the robotic arm system 40 controls the robotic arm 41 so that the robotic arm 41 moves toward random distinct first-direction predictive positioning-points xP.sub.k in front of the X-direction first boundary plane. At this moment the measuring instrument 45 measures the first-direction predictive positioning-points xP.sub.k in front of the X-direction first boundary plane to obtain corresponding X-direction measured displacements xMx.sub.k, and the mechanism parameter sets xS.sub.k corresponding to the first-direction predictive positioning-points xP.sub.k are stored.
(79) In step S805, the processing unit 44 of the robotic arm system 40 controls the robotic arm 41 so that the robotic arm 41 moves toward, random distinct first-direction predictive positioning-points xP.sub.k in front of the X-direction second boundary plane. At this moment, the measuring instrument 45 measures the first-direction predictive positioning-points xP.sub.k in front of the X-direction second boundary plane to obtain corresponding X-direction measured displacements xMx.sub.k, and the mechanism parameter sets xS.sub.k corresponding to the first-direction predictive positioning-points xP.sub.k are stored. In step S806, the processing unit 44 of the robotic arm system 40 obtains first-direction predictive relative-displacement equations g.sub.x(xS.sub.1,xS.sub.j,S) corresponding to the first-direction predictive positioning-points and determines X-direction measured relative-displacement xMx.sub.i,j according to the X-direction measured displacements xMx.sub.1xMx.sub.nx. Then the method proceeds to step S807.
(80) In step S807, the robotic arm system 40 or the manipulator of the robotic arm system 40 determines whether to perform a Y-direction measurement or not. If yes, the method proceeds to step S808. Otherwise, the method proceeds to step S8012. In step S808, the processing unit 44 of the robotic system 40 controls the posture of the robotic arm 41 so that the measuring instrument 45 is facing the Y-direction boundary planes.
(81) In step S809, the processing unit 44 of the robotic arm system 40 controls the robotic arm 41 so that the robotic arm 41 moves toward random distinct second-direction predictive positioning-points yP.sub.k in front of the Y-direction first boundary plane. At this moment, the measuring instrument 45 measures the second-direction predictive positioning-points yP.sub.k in front of the Y-direction first boundary plane to obtain corresponding Y-direction measured displacements yMy.sub.k, and the mechanism parameter sets yS.sub.k corresponding to the second-direction predictive positioning-points yP.sub.k are stored.
(82) In step S810, the processing unit 44 of the robotic arm system 40 controls the robotic arm 41 so that the robotic arm 41 moves toward random distinct second-direction predictive positioning-points yP.sub.k in front of the Y-direction second boundary plane. At this moment, the measuring instrument 45 measures the second-direction predictive positioning-points yP.sub.k in front of the Y-direction second boundary plane to obtain corresponding Y-direction measured displacements yMy.sub.k, and the mechanism parameter sets yS.sub.k corresponding to the second-direction predictive positioning-points yP.sub.k are stored. In step S811, the processing unit 44 of the robotic arm system 40 obtains second-direction predictive relative-displacement equations g.sub.y(yS.sub.i,yS.sub.j,S) corresponding to the second-direction predictive positioning-points and determines Y-direction measured relative-displacement yMy.sub.i,j according to the Y-direction measured displacements yMy.sub.1yMy.sub.ny. Then the method proceeds to step S812.
(83) In step S812, the robotic arm system 40 or the manipulator of the robotic arm system 40 determines whether to perform a Z-direction measurement or not. If yes, the method proceeds to step S813. Otherwise, the method proceeds to step S8017. In step S813, the processing unit 44 of the robotic system 40 controls the posture of the robotic arm 41 so that the measuring instrument 45 faces the Z-direction boundary planes.
(84) In step S814, the processing unit 44 of the robotic arm system 40 controls the robotic arm 41 so that the robotic arm 43 moves toward random distinct third-direction predictive positioning-points zP.sub.k in front of the Z-direction first boundary plate. At this moment, the measuring instrument 45 measures the third-direction predictive positioning-points zP.sub.k in front of the Z-direction first boundary plane to obtain corresponding Z-direction measured displacements zMz.sub.k, and the mechanism parameter sets zS.sub.k corresponding to the third-direction predictive positioning-points zP.sub.k are stored.
(85) In step S815, the processing unit 44 of the robotic arm system 40 controls the robotic arm 41 so that the robotic arm 41 moves toward random distinct second-direction predictive positioning-points zP.sub.k in front of the Z-direction second boundary plane. At this moment, the measuring instrument 45 measures the third-direction predictive positioning-points zP.sub.z in front of the Z-direction second boundary plane to obtain corresponding Z-direction measured displacements yMy.sub.k, and the mechanism parameter sets zS.sub.k corresponding to the third-direction predictive positioning-points zP.sub.k are stored. In step S816, the processing unit 44 of the robotic arm system 40 obtains third-direction predictive relative-displacement equations g.sub.z(zS.sub.i,zS.sub.j,S) corresponding to the third-direction predictive positioning-points and determines Z-direction measured relative-displacement zMz.sub.i,j according to the Z-direction measured displacements zMz.sub.1zMz.sub.nz. Then the method proceeds to Step S817.
(86) In step S817, the processing unit 44 of the robotic arm system 40 calculates an optimization equation of the robotic arm 41 according to xMx.sub.i,j, yMy.sub.i,j, zMz.sub.i,j, g.sub.x(xS.sub.i,xS.sub.j,S), g.sub.y(yS.sub.i,yS.sub.j,S), g.sub.z(zS.sub.i,zS.sub.j,S). In step S818, the processing unit 44 of the robotic arm system 40 utilizes an optimization algorithm and the optimization equation to obtain a set of optimal mechanism parametric deviations S.
(87) Finally, in step S819, the processing unit 44 of the robotic arm system 40 uses the set of optimal mechanism parametric deviations S to calibrate the mechanism parameter sets xS.sub.1xS.sub.nx corresponding to the first-direction predictive positioning-points xP.sub.1xP.sub.nx, the mechanism parameter sets yS.sub.1yS.sub.ny corresponding to the second-direction predictive positioning-points yP.sub.1yP.sub.ny and the mechanism parameter sets zS.sub.1zS.sub.nz corresponding to the third-direction predictive positioning-points zP.sub.1zP.sub.nz of the robotic arm 41.
(88) As described above, because the factors that affects the set of mechanism parametric deviations S might include the mechanism transmission error, the load stress variation, and the ambient temperature changes, which means when a robot configuration of the robotic arm system changes, different sets of mechanism parametric deviations S should be provided for better positioning accuracy. In other words, another set of mechanism parametric deviations S can be presented as:
SS(rConfig)
Wherein rConfig is related to a specific status of the robotic arm (such as having a specific hand system, a specific positioning region, a specific mounting (gravity) direction, a specific payload, a specific ambient temperature, or the like). It should be noted that all factors that might cause stress variation or result in different thermal expansion effects should be considered, it is not limited to the factors as described above.
(89) Furthermore, because different status of the robotic arm requires different sets of mechanism parametric deviations S(rConfig), the calibrating calculation unit 241 of the processing unit 24 may calculate a new optimization equation .sub.rConfig for the new sets of mechanism parametric deviations S(rConfig). Wherein the new optimization equation .sub.rConfig is represented as:
(90)
(91) When the processing unit 14 determines the robot configuration changes, the processing unit 14 needs to obtain different sets of mechanism parametric deviations S for the calibration. For example, when fee status of the robotic arm is varied so that the stress of the robotic arm exceeds a predetermined range, which means the robotic arm is operated in another robot configuration, the processing unit 114 uses another set of mechanism parametric deviations S. Or when the temperature of the operating environment changes, which means the size of the robotic arm might have different thermal expansion effect, the processing unit 14 must also use another set of mechanism parametric deviations S for the calibration. Furthermore, the calibration method used herein can be the method as described above or the method recited in the prior art, and it will not be described here to streamline the description.
(92) The embodiments as described below provide different examples of the robot configuration. In robotics analysis, there might be multiple solutions of inverse kinematics for a robot pose. That means the robot can reach a specific position in a workspace by several different geometrical hand systems. For example,
(93) Furthermore,
(94) As described, even though the robotic arms shown in
(95)
(96) Furthermore, different mounting directions might also cause different stress variations on the robotic arm. For example,
(97) In addition, different payloads may also cause different stress variations. For example, when tool and/or load of work piece hanging on the robotic arm are changed, the payload will be changed accordingly. Therefore, when the robotic arms perform different operations with different payloads, even though the robotic arms is operated in the same positioning region, the processing unit 14 still have to use different sets of mechanism parametric deviations S to calibrate the robotic arms.
(98) In another situation, because the robotic arms made of different materials have different rigidities, that causes the amount of droop might be different even under the same payload condition, and different materials have different stress variation. For this reason, when the robotic arms are made of different materials, different sets of mechanism parametric deviations S are also necessary.
(99) Furthermore, when the temperature of the operating environment is changed, different sets of mechanism parametric deviations S will be required in response to different thermal expansion effects, wherein the sets of mechanism parametric deviations S corresponding to some specific temperatures can be obtained in advance, and then when the temperature of the operating environment changes, new sets of mechanism parametric deviations S can be obtained by using interpolation or other methods based on the obtained sets of mechanism parametric deviations S. For example, different sets of mechanism parametric deviations S for 0 C., 50 C. and 100 C. can be obtain in advance, and when the temperature of the operating environment is 25 C., a new set of mechanism parametric deviations S can be obtained by using interpolation based on the sets of mechanism parametric deviations S of 0 C. and 50 C.
(100) In conclusion, since the factors as described above will cause different stress variation or thermal expansion effects, the set of mechanism parametric deviations S will change with different robot configurations and have corresponding values. For example, when robotic arm has N.sub.HS hand systems, N.sub.PR sets of positioning regions, N.sub.MD mounting directions, N.sub.PL payloads, and N.sub.AT ambient temperatures, the processing unit 14 may obtain the total number N=N.sub.HSN.sub.PRN.sub.MDN.sub.PLN.sub.AT sets of mechanism parametric deviations S for each robot configurations. Wherein the factors as described can be selectively set by the users, and when the factors are not selected, the number corresponding to those factors are set to 1. For example, when a specific robotic arm set by the user has two sets of hand systems, three positioning regions and two sets of payloads, the total number of the sets of mechanism parametric deviations S is 23121=12.
(101) It should be noted that the requirement of different sets of mechanism parametric deviations S(rConfig) for the robotic arm can also be applied to any conventional calibration method of the robotic arm system, it is not limited to the method as described in the present invention.
(102) While the present disclosure has been described by way of example and in terms of preferred embodiment, it is to be understood that the present disclosure is not limited thereto. On the contrary, it is intended to cover various modifications and similar arrangements (as would be apparent to a person skilled in the art). Therefore, the scope of the appended claims should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements.