CN108789404A - A kind of serial manipulator kinematic calibration method of view-based access control model - Google Patents
A kind of serial manipulator kinematic calibration method of view-based access control model Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
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- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
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- B25J9/00—Programme-controlled manipulators
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Abstract
The present invention provides a kind of serial manipulator kinematic calibration method of view-based access control model, is constrained camera optical axis as virtual line, establishes the kinematic error model based on line constraint；It selects a fixed point as characteristic point on the fixed scaling board of robot end, is moved using the visual spatial attention method control machinery arm based on image, characteristic point is made to reach on the optical axis of camera；According to the joint angular data of robot, the nominal position of characteristic point is calculated using positive kinematics, calculates alignment error matrix；Estimate kinematic parameter errors by iterative least square algorithm, actual kinematics parameters are calculated according to the kinematics parameters of name.The present invention is using the optical axis of camera as virtual constraint, calibration can be completed using only the joint angular data of robot, it is at low cost, easy to operate, expensive high-acruracy survey equipment is not needed, there is versatility to serial manipulator calibration, can be widely applied in industry, space, underwater environment improve the absolute fix precision of mechanical arm.
Description
Technical Field
The invention relates to a vision-based serial robot kinematic parameter calibration method, and belongs to the field of robot calibration.
Background
With the increasing application of robots to tasks such as assembly, surgery, cooperation and the like, the positioning accuracy of the tail end of the robot is required to be higher and higher. At present, the position and attitude errors of the tail end of the robot cannot be directly measured, and are usually obtained by indirect calculation through a kinematic model and joint angle data. Due to the influence of factors such as manufacturing tolerance, abrasion, transmission error, installation position, environmental change and the like, deviation exists between an actual kinematic parameter and a nominal value in a robot model, and if the nominal kinematic parameter is used for calculating the terminal pose of the robot, the absolute positioning accuracy of the terminal pose of the robot is reduced. In order to improve the absolute positioning accuracy of the robot, the kinematic parameters of the robot must be effectively calibrated, which is one of the difficulties in the field of robotics research.
Generally, in a robot calibration algorithm, a high-precision measuring device is used for measuring the actual pose of the tail end of the robot, but such measuring devices are very expensive and have a very complex calibration process, and have high technical requirements on installation, debugging and measurement processes. The calibration method based on vision usually uses a camera as a measuring tool to measure the actual terminal pose, and the vision field of the camera and the parameter error of the camera have great influence on the calibration result of the kinematic parameters. In order to avoid using high-precision measuring equipment, a calibration method which is low in cost and easy to operate is used, and the influence of the measuring equipment on a calibration result is reduced, so that the absolute positioning precision of the robot in each application scene is necessarily improved.
The method provided by the invention aims at a typical six-degree-of-freedom industrial mechanical arm, and solves the problem of low positioning precision of the tail end of the robot by defining the optical axis of the camera as a virtual straight line constraint. The vision-based serial robot kinematic parameter calibration method has important reference significance for improving the absolute positioning accuracy of the serial mechanical arm, and can be directly applied to kinematic parameter calibration of the serial mechanical arm.
Disclosure of Invention
The invention aims to provide a serial robot kinematic parameter calibration method based on vision in order to realize that a robot completes kinematic parameter calibration based on camera optical axis virtual constraint.
The purpose of the invention is realized as follows: the method comprises the following steps:
the method comprises the following steps: taking an optical axis of a camera as virtual straight line constraint, and establishing a kinematic error model based on the straight line constraint;
step two: selecting a fixed point on a calibration plate fixed at the tail end of the robot as a characteristic point, and controlling the movement of the mechanical arm by using an image-based visual control method to enable the characteristic point to reach the optical axis of the camera;
step three: calculating the nominal position of the characteristic point based on a positive kinematic model according to the joint angle data of the robot, and calculating a position alignment error matrix;
step four: and estimating the kinematic parameter error by an iterative least square algorithm, and calculating the actual kinematic parameter according to the nominal kinematic parameter to finish the kinematic parameter calibration of the serial robot.
The invention also includes such structural features:
1. the establishing of the kinematic error model in the first step is specifically as follows:
(1) establishing a kinematic model of the serial robot based on an improved DH method to obtain a transformation matrix from a robot base coordinate to an end effector;
(2) establishing a kinematic error model of the serial robot to obtain a terminal pose error vectorAnd kinematic parameter error vectorA linear relationship therebetween, wherein Δ PeAnd Δ ReRespectively representing small translation and rotation errors of the tail end of the robot;
(3) using the optical axis of the camera as virtual straight line constraint, establishing an error model based on the virtual straight line constraint to obtain an alignment error matrix E and a kinematic parameter error vectorThe relationship between them.
2. The visual control based on the image in the second step is specifically as follows:
(1) a calibration plate is arranged at the tail end of the robot, a point location characteristic point on the calibration plate is selected, and the calibration plate is completely positioned in the visual field of the camera;
(2) the vision control method based on the image is composed of an image characteristic outer ring and a robot control inner ring, an expected image characteristic is that a characteristic point arrives on an optical axis of a camera, and according to deviation of the expected image characteristic and current image characteristic acquired by the camera, image coordinate deviation is carried out through a terminal pose adjusting strategyInto deviations of the robot ends
(3) According to the terminal pose deviation of the robotAnd calculating the expected pose of the tail end, and controlling the robot to reach the expected pose through the inner ring controlled by the robot.
3. The position alignment error matrix calculation in the third step is specifically as follows:
(1) after the characteristic points reach the optical axis of the camera, the joint angle of the robot at the moment is recorded, and the nominal position of the tail end of the robot is calculated based on the positive kinematics model
(2) Controlling the robot to move, enabling the characteristic points to sequentially reach a plurality of positions on the optical axis, and calculating the nominal position of the tail end of the robot at each position;
(3) selecting a plurality of optical axis vectors for measurement, respectively moving the characteristic points to a plurality of position points on each optical axis, and calculating a position alignment error matrix E according to the nominal position of the tail end of the mechanical arm at each position:
E(i,j,k)＝[μk×](v(j,k)-v(i,k))
wherein: p is the number of position points on each optical axis, q is the number of optical axes, mukIs an optical axial quantity, v(i,k)And v(j,k)Are respectively a pointAndto the constraint vector mukThe distance of (c).
4. The kinematic parameter identification in the step four is specifically as follows:
(1) fitting the optical axis vector mu by using a least square method according to the nominal position of the characteristic point at each position on the optical axisk；
(2) Solving kinematic parameter errors by using an iterative least square method based on a kinematic error modelAnd calculating the actual kinematic parameters
Compared with the prior art, the invention has the beneficial effects that: the invention utilizes the optical axis of the camera as the virtual straight line constraint to calibrate the kinematic parameters of the serial robot, can complete calibration only by using the optical axis of the camera and the joint angle data of the mechanical arm, does not need other expensive high-precision measuring instruments or specific calibration equipment, and has low cost and easy operation. The established kinematic error model based on the straight line constraint has robustness on lower camera depth measurement precision, other camera parameters are not required to be calibrated except for the image coordinates of the central point of the optical axis of the camera, and the influence of the camera parameter error on the kinematic parameter calibration result is reduced. The method has important reference significance for improving the absolute positioning accuracy of the serial mechanical arm, and can be directly applied to the kinematic parameter calibration of the serial mechanical arm in various fields.
Drawings
FIG. 1 is a schematic view of the location of feature points on a calibration plate of the present invention;
FIG. 2 is a schematic diagram of the image-based vision control method of the present invention;
FIG. 3 is a block diagram of the image-based vision control of the present invention;
fig. 4 is a position diagram of the characteristic point of the present invention on the optical axis.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The invention provides a serial robot kinematic parameter calibration method based on vision. Aiming at the problems that the absolute positioning accuracy of the robot is lower at present and the requirement on the positioning accuracy of the robot is higher and higher in more and more application fields, the method for calibrating the kinematic parameters of the robot is provided; in addition, aiming at the problems that the prior robot kinematic parameter calibration method needs expensive high-precision measuring instruments or special calibration equipment, the calibration result is influenced by measuring instruments and the like, the vision-based kinematic parameter calibration method is designed. Firstly, taking a camera optical axis as virtual straight line constraint, and establishing a kinematic error model based on straight line constraint on the basis of establishing a kinematic model of a robot by using an improved DH method; then, selecting a fixed point on a calibration plate fixed at the tail end of the robot as a characteristic point, controlling the movement of the mechanical arm by using an image-based visual control method, enabling the characteristic point to reach the optical axis of the camera, selecting a plurality of optical axes, enabling the characteristic point to sequentially reach a plurality of positions on the optical axis on each optical axis, and recording the joint angle of the robot at each position; and finally, calculating the nominal position of the feature point by using positive kinematics according to the joint angle data of the robot, calculating an alignment error matrix, estimating the kinematic parameter error by using an iterative least square algorithm based on a kinematic error model, and calculating the actual kinematic parameter according to the nominal kinematic parameter. The invention uses the optical axis of the camera as virtual constraint, can finish calibration only by using joint angle data of the robot, has the characteristics of low cost and easy operation, does not need expensive high-precision measuring equipment, has universality for calibration of the series robot, and can be widely applied to industrial, space and underwater environments to improve the absolute positioning precision of the mechanical arm.
The invention adopts the following technical scheme:
the serial robot kinematic parameter calibration method based on vision comprises the steps of establishing a kinematic error model, vision control based on images, position alignment error matrix calculation and kinematic parameter identification. Wherein:
the method comprises the following steps: taking an optical axis of a camera as virtual straight line constraint, and establishing a kinematic error model based on the straight line constraint;
step two: selecting a fixed point on a calibration plate fixed at the tail end of the robot as a characteristic point, and controlling the movement of the mechanical arm by using an image-based visual control method to enable the characteristic point to reach the optical axis of the camera;
step three: calculating the nominal position of the characteristic point by using positive kinematics according to the joint angle data of the robot, and calculating a position alignment error matrix;
step four: and estimating the kinematic parameter error by an iterative least square algorithm, and calculating the actual kinematic parameter according to the nominal kinematic parameter to finish the kinematic parameter calibration of the serial robot.
The establishment of the kinematic error model in the first step is specifically as follows:
(1) establishing a kinematic model of the serial robot based on an improved DH method to obtain a transformation matrix from a robot base coordinate to an end effector;
(2) establishing a kinematic error model of the serial robot to obtain a terminal pose error vectorAnd kinematic parameter error vectorA linear relationship therebetween, wherein Δ PeAnd Δ ReRespectively representing small translation and rotation errors of the tail end of the robot;
(3) using the optical axis of the camera as virtual straight line constraint, establishing an error model based on the virtual straight line constraint to obtain an alignment error matrix E and a kinematic parameter error vectorThe relationship between them.
The image-based visual control in the second step is specifically as follows:
(1) a calibration plate is arranged at the tail end of the robot, a point location characteristic point on the calibration plate is selected, and the calibration plate is completely positioned in the visual field of the camera;
(2) base ofThe vision control method for the image consists of an image characteristic outer ring and a robot control inner ring, wherein the expected image characteristic is that a characteristic point arrives on an optical axis of a camera, and according to the deviation between the expected image characteristic and the current image characteristic acquired by the camera, the image coordinate deviation is adjusted through a terminal pose adjusting strategyInto deviations of the robot ends
(3) According to the terminal pose deviation of the robotAnd calculating the expected pose of the tail end, and controlling the robot to reach the expected pose through the inner ring controlled by the robot.
The calculation of the position alignment error matrix in the third step is specifically as follows:
(1) after the characteristic points reach the optical axis of the camera, recording the joint angle of the robot at the moment;
(2) controlling the robot to move to make the characteristic points reach multiple positions on the optical axis in sequence, and calculating the nominal position of the tail end of the robot at each position according to the joint angle
(3) Selecting a plurality of optical axis vectors for measurement, respectively moving the characteristic points to a plurality of position points on each optical axis, and calculating an alignment error matrix E according to the nominal position of the tail end of the mechanical arm at each position:
E(i,j,k)＝[μk×](v(j,k)-v(i,k))
wherein p is the number of position points on each optical axis, q is the number of optical axes, mukIs an optical axial quantity, v(i,k)And v(j,k)Are respectively a pointAndto the constraint vector mukThe distance of (c).
The kinematic parameter identification in the fourth step is specifically as follows:
(1) fitting the optical axis vector mu by using a least square method according to the nominal position of the characteristic point at each position on the optical axisk；
(2) Solving kinematic parameter errors by using an iterative least square method based on a kinematic error modelAnd calculating the actual kinematic parameters
An embodiment of the present invention is given below with specific numerical values:
(1) establishing a kinematic error model
Defining the link parameter vector as:parameter vector of connecting rod approximately parallel to previous joint axisParameter vectors of other linksWherein, ai,di,αi,θi,βiIs the ith (i ═ 1)And 2,3,4,5,6) kinematic parameters of the connecting rods are respectively the length of the connecting rod, the offset distance of the connecting rod, the rotating angle of the connecting rod, the joint angle and the rotating angle of the connecting rod parallel to the joint shaft.
Suppose the actual kinematic parameter vector of the robot isHaving a nominal value ofKinematic parameter error vectorA robot kinematic error model can be obtained based on the improved DH model:
wherein, Δ PeAnd Δ ReRespectively representing slight translational and rotational errors of the robot tip,andrespectively, the Jacobian of errors with respect to position and attitude.
Defining the k optical axis constraint vector as mukLet the ith actual position of the feature point on the optical axis be Pe (i,k)The corresponding joint angle of the robot is thetae (i,k). The name meaning position of the characteristic point calculated according to the kinematics name meaning parameter is set asThe difference between the nominal position and the actual position of the feature point is:
wherein,0R6' is the nominal pose transformation matrix of the robot arm base to tip.
With reference to figure 1 of the drawings,is the origin of coordinates of the camera and,andcharacteristic point of the optical axis quantity mukIn the actual position of the upper part of the body,andis a corresponding nominal position, Pe (i,k)Andrespectively expressed as:
wherein s is(i,k)Is a point Pe (i,k)To the origin of the camera coordinatesThe vertical distance of (d); s'(i,k)Is a pointTo the origin of the camera coordinatesPerpendicular distance of v(i,k)Is a pointTo the constraint vector mukThe distance of (c).
Define operator [ mu ]k×]Comprises the following steps:apparently [ mu ] ofk×]μk0. The difference between the nominal position and the actual position of the feature point is obtained by transformation:
two different positions P on the virtual constrainte (i,k)And Pe (j,k)Respectively substituting the equations, and obtaining the difference of the two equations:
definition E(i,j,k)In order to be able to correct the alignment error,is a relative alignment error Jacobian matrix:
E(i,j,k)＝[μk×](v(j,k)-v(i,k))
to obtainSelecting q optical axes for measurement, moving the characteristic points to p position points on each optical axis respectively, and constructing a position alignment error matrix E and a regression matrix phi:
obtaining the error vector of the solution kinematic parameterKinematic error model of (2):
(2) image-based visual control
Referring to fig. 2, the characteristic point on the robot end calibration plate is FpCurrent position P of feature pointfAnd the optical axis mukD, and the image coordinates of the feature points are (u)f,vf) The image coordinate of the center point of the optical axis is (u)0,v0) The purpose of visual control is to make PfMove to position point P 'on the optical axis'fAt this time, d → 0, uf→u0,vf→v0。
Referring to fig. 3, the image-based vision control block diagram is composed of an outer ring of image features and an inner ring of robot position control, the control target is to make the image coordinates (u) of the feature pointsf,vf) Image coordinates (u) from the center point of the optical axis0,v0) And (c) overlapping, using the current image acquired by the camera as visual feedback, wherein the deviation of the current actual coordinate and the expected coordinate of the feature point in the image coordinate is (u)f-u0,vf-v0) And converting the image coordinate deviation into the deviation of the tail end of the mechanical arm under a base coordinate system according to a tail end pose adjusting strategy, so as to realize the conversion from the image space deviation to the Cartesian space deviation. In the robot control inner loop, an expected pose is calculated according to the feedback robot terminal pose deviation, an expected joint angle is calculated according to inverse kinematics, and the robot is controlled to move to an expected position and posture by using a joint position controller of the robot. In the terminal pose adjustment strategy, a transformation matrix from image deviation to Cartesian space deviation is as follows:
wherein,is the deviation of the actual position of the characteristic point under the base coordinate system from the expected position,is a rotation matrix from the camera coordinate system to the robot base coordinate system,the position deviation of the feature point in the camera coordinate system can be calculated according to a camera model, (u)0,v0) Can be obtained by camera calibration, kx,kyIs a constant coefficient.
In the position control inner ring, due to the existence of kinematic parameter errors, the mechanical arm cannot be moved to a desired position according to inverse kinematics, and the mechanical arm needs to be controlled to move in a small increment mode, so that the characteristic point is gradually close to the optical axis until the distance between the characteristic point and the optical axis reaches an acceptable error range. And setting k as a normal number smaller than 1, wherein the actual motion increment of the tail end of the mechanical arm is as follows:
(3) position alignment error matrix calculation
Referring to fig. 4, the feature points sequentially arrive at the optical axis μkA joint angle theta of the robot at each position is recorded, and a nominal position of the feature point under the base coordinate system is calculated based on a positive kinematic model of the robotTransformation matrix for robot base coordinate system to end coordinate system0TnWherein:
wherein n is the number of connecting rods of the robot,i-1Tifor a link whose joint axis is approximately parallel to the previous joint axis, for a transformation matrix between the (i-1) th coordinate system and the (i) th coordinate system:
transformation matrix of other linksi-1TiComprises the following steps:
selecting multiple optical axis vectors, sequentially arriving the feature points at multiple position points on each optical axis, and calculating the nominal positions of the feature points at each positionA position alignment error matrix E is calculated.
(4) Kinematic parameter identification
According to calculationNominal position of a feature point on an optical axisObtaining the optical axial quantity mu in the error model by least square fittingk. Let the nominal value coordinate of the position i (i ≦ s) on the k-th optical axis be (x)i,yi,zi) The linear equation for the optical axis k is:
wherein, the parameter x0,y0M, n are:
from the regression matrix Φ and the measurement matrix E calculated above, the kinematic parameter error vectors are estimated using the iterative least squares method based on the error modelEstimate of the t-th iterationComprises the following steps:
where Φ (t) and E (t) are updated separately for each iterationThe regression matrix and the measurement matrix are calculated, and lambda (t) is a penalty factor:
wherein h is generally a constant between 2 and 10, and λ (0) is a constant between 0.001 and 0.1.
From estimated kinematic parameter errors of the tandem robotCalculating actual kinematic parameters
In conclusion, the invention belongs to the field of robot calibration, and relates to a serial robot kinematic parameter calibration method based on vision. The invention comprises the following steps: taking an optical axis of a camera as virtual straight line constraint, and establishing a kinematic error model based on the straight line constraint; selecting a fixed point on a calibration plate fixed at the tail end of the robot as a characteristic point, and controlling the movement of the mechanical arm by using an image-based visual control method to enable the characteristic point to reach the optical axis of the camera; calculating the nominal position of the characteristic point by using positive kinematics according to the joint angle data of the robot, and calculating an alignment error matrix; and estimating the kinematic parameter error by an iterative least square algorithm, and calculating the actual kinematic parameter according to the nominal kinematic parameter. The invention uses the optical axis of the camera as virtual constraint, can finish calibration only by using joint angle data of the robot, has the characteristics of low cost and easy operation, does not need expensive high-precision measuring equipment, has universality for calibration of the series robot, and can be widely applied to industrial, space and underwater environments to improve the absolute positioning precision of the mechanical arm.
Claims (5)
1. A serial robot kinematic parameter calibration method based on vision is characterized in that: the method comprises the following steps:
the method comprises the following steps: taking an optical axis of a camera as virtual straight line constraint, and establishing a kinematic error model based on the straight line constraint;
step two: selecting a fixed point on a calibration plate fixed at the tail end of the robot as a characteristic point, and controlling the movement of the mechanical arm by using an image-based visual control method to enable the characteristic point to reach the optical axis of the camera;
step three: calculating the nominal position of the characteristic point based on a positive kinematic model according to the joint angle data of the robot, and calculating a position alignment error matrix;
step four: and estimating the kinematic parameter error by an iterative least square algorithm, and calculating the actual kinematic parameter according to the nominal kinematic parameter to finish the kinematic parameter calibration of the serial robot.
2. The vision-based serial robot kinematic parameter calibration method according to claim 1, characterized in that: the establishing of the kinematic error model in the first step is specifically as follows:
(1) establishing a kinematic model of the serial robot based on an improved DH method to obtain a transformation matrix from a robot base coordinate to an end effector;
(2) establishing a kinematic error model of the serial robot to obtain a terminal pose error vectorAnd kinematic parameter error vectorA linear relationship therebetween, wherein Δ PeAnd Δ ReRespectively representing small translation and rotation errors of the tail end of the robot;
(3) using the optical axis of the camera as virtual straight line constraint, establishing an error model based on the virtual straight line constraint to obtain an alignment error matrix E and a kinematic parameter error vectorThe relationship between them.
3. The vision-based serial robot kinematic parameter calibration method according to claim 2, characterized in that: the visual control based on the image in the second step is specifically as follows:
(1) a calibration plate is arranged at the tail end of the robot, a point location characteristic point on the calibration plate is selected, and the calibration plate is completely positioned in the visual field of the camera;
(2) the vision control method based on the image is composed of an image characteristic outer ring and a robot control inner ring, an expected image characteristic is that a characteristic point arrives on an optical axis of a camera, and according to deviation of the expected image characteristic and current image characteristic acquired by the camera, image coordinate deviation is carried out through a terminal pose adjusting strategyInto deviations of the robot ends
(3) According to the terminal pose deviation of the robotAnd calculating the expected pose of the tail end, and controlling the robot to reach the expected pose through the inner ring controlled by the robot.
4. The vision-based serial robot kinematic parameter calibration method according to claim 3, characterized in that: the position alignment error matrix calculation in the third step is specifically as follows:
(1) after the characteristic points reach the optical axis of the camera, the joint angle of the robot at the moment is recorded, and the nominal position of the tail end of the robot is calculated based on the positive kinematics model
(2) Controlling the robot to move, enabling the characteristic points to sequentially reach a plurality of positions on the optical axis, and calculating the nominal position of the tail end of the robot at each position;
(3) selecting a plurality of optical axis vectors for measurement, respectively moving the characteristic points to a plurality of position points on each optical axis, and calculating a position alignment error matrix E according to the nominal position of the tail end of the mechanical arm at each position:
E(i,j,k)＝[μk×](v(j,k)-v(i,k))
wherein: p is the number of position points on each optical axis, q is the number of optical axes, mukIs an optical axial quantity, v(i,k)And v(j,k)Are respectively a pointAndto the constraint vector mukThe distance of (c).
5. The vision-based serial robot kinematic parameter calibration method according to claim 4, characterized in that: the kinematic parameter identification in the step four is specifically as follows:
(1) fitting the optical axis vector mu by using a least square method according to the nominal position of the characteristic point at each position on the optical axisk；
(2) Solving kinematic parameter errors by using an iterative least square method based on a kinematic error modelAnd calculating the actual kinematic parameters
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| CN115026814A (en) * | 2022-06-01 | 2022-09-09 | 中科苏州智能计算技术研究院 | Camera automatic calibration method for mechanical arm motion space reconstruction |
| CN115890654A (en) * | 2022-10-09 | 2023-04-04 | 北京微链道爱科技有限公司 | Depth camera automatic calibration algorithm based on three-dimensional feature points |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4675499A (en) * | 1985-01-31 | 1987-06-23 | Shibuya Kogyo Co., Ltd. | Laser beam machining robot |
| CN101096101A (en) * | 2006-06-26 | 2008-01-02 | 北京航空航天大学 | Robot foot-eye calibration method and device |
| CN104608129A (en) * | 2014-11-28 | 2015-05-13 | 江南大学 | Planar constraint based robot calibration method |
| CN106017339A (en) * | 2016-06-06 | 2016-10-12 | 河北工业大学 | Three-dimensional measurement method for projecting non-uniform stripes in non-complete constraint system |
| CN106061427A (en) * | 2014-02-28 | 2016-10-26 | 索尼公司 | Robot arm apparatus, robot arm control method, and program |
| CN107214703A (en) * | 2017-07-11 | 2017-09-29 | 江南大学 | A kind of robot self-calibrating method of view-based access control model auxiliary positioning |
-
2018
- 2018-05-25 CN CN201810510980.8A patent/CN108789404B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4675499A (en) * | 1985-01-31 | 1987-06-23 | Shibuya Kogyo Co., Ltd. | Laser beam machining robot |
| CN101096101A (en) * | 2006-06-26 | 2008-01-02 | 北京航空航天大学 | Robot foot-eye calibration method and device |
| CN106061427A (en) * | 2014-02-28 | 2016-10-26 | 索尼公司 | Robot arm apparatus, robot arm control method, and program |
| CN104608129A (en) * | 2014-11-28 | 2015-05-13 | 江南大学 | Planar constraint based robot calibration method |
| CN106017339A (en) * | 2016-06-06 | 2016-10-12 | 河北工业大学 | Three-dimensional measurement method for projecting non-uniform stripes in non-complete constraint system |
| CN107214703A (en) * | 2017-07-11 | 2017-09-29 | 江南大学 | A kind of robot self-calibrating method of view-based access control model auxiliary positioning |
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| CN109571477A (en) * | 2018-12-17 | 2019-04-05 | 西安工程大学 | A kind of improved robot vision and conveyer belt composite calibration method |
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| CN111360812B (en) * | 2018-12-26 | 2022-11-29 | 中国科学院沈阳自动化研究所 | Industrial robot DH parameter calibration method and calibration device based on camera vision |
| CN110125944A (en) * | 2019-05-14 | 2019-08-16 | 中国地质大学（武汉） | A kind of mechanical arm teaching system and method |
| CN110480658A (en) * | 2019-08-15 | 2019-11-22 | 同济大学 | A kind of six-joint robot control system merging vision self-calibration |
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| CN111912310A (en) * | 2020-08-10 | 2020-11-10 | 深圳市智流形机器人技术有限公司 | Calibration method, device and equipment |
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| CN112975913A (en) * | 2021-03-10 | 2021-06-18 | 清华大学 | Self-calibration method and system for cable-driven parallel mechanism |
| CN113733088A (en) * | 2021-09-07 | 2021-12-03 | 河南大学 | Mechanical arm kinematics self-calibration method based on binocular vision |
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| CN113977574B (en) * | 2021-09-16 | 2023-02-14 | 南京邮电大学 | Mechanical arm point constraint control method |
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| CN114161411A (en) * | 2021-11-18 | 2022-03-11 | 浙江大学 | Vision-based multi-legged robot kinematic parameter calibration method |
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