CN104180753A - Rapid calibration method of robot visual system - Google Patents
Rapid calibration method of robot visual system Download PDFInfo
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- CN104180753A CN104180753A CN201410371760.3A CN201410371760A CN104180753A CN 104180753 A CN104180753 A CN 104180753A CN 201410371760 A CN201410371760 A CN 201410371760A CN 104180753 A CN104180753 A CN 104180753A
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Abstract
The invention relates to a rapid calibration method of a robot visual system, especially to calibration between a camera and a manipulator and calibration between cameras. The method comprises the steps of arranging a calibration plate, setting movement rules of the manipulator, obtaining coordinates of induction points of the calibration plate and coordinates of the corresponding visual system, establishing mapping relations of matrixes according to the coordinates, and solving a transformation matrix.
Description
Technical field
The present invention relates to robot coordinate setting technique field, particularly a kind of quick calibrating method of robotic vision system.
Background technology
At present, in global manufacturing industry, industrial robot has played more and more important effect aborning.In order to make robot can be competent at more complicated work, not only will there be better control system in robot, also needs the variation of perception environment more.Wherein robot vision with its contain much information, information completely becomes most important robot perception function.The precision welding that Yi Yong robot carries out electronic element of circuit board is example, in welding process, robot can utilize the video camera in vision system automatically to locate workpiece or workplace, and evaluation work scene, with respect to the relative position of robot, fulfils assignment with auxiliary robot.
The demarcation of robotic vision system, sets up the transformational relation between robot coordinate system and the image coordinate system of video camera, is one of gordian technique in robot manipulating task process.Yet the shortcoming that existing robotic vision system scaling method ubiquity condition precedent is many, complexity is high, calculated amount is large can not realize the requirement of simple and efficient demarcation in production application.
Summary of the invention
The object of the invention is to solve the deficiencies in the prior art, the quick calibrating method of robotic vision system is provided, this scaling method is simple, information processing capacity is few; Easy to operate.
The technical solution used in the present invention is:
The quick calibrating method of robotic vision system, for being transformed into robot coordinate a robotic vision system; It comprises the following steps:
Step 1, scaling board is set, a plurality of preset point for vision system induction are set on scaling board, scaling board is set up to coordinate;
Step 2, mechanical arm arrange an induction point moving for demarcating mechanical arm; The movement rule of mechanical arm is set according to the position of preset point, and mechanical arm is subject to processing device and controls, and makes the each mobile rear induction point of mechanical arm all be positioned at the top of preset point:
Step 3, mechanical arm start mobile, and the camera head of vision system carries out image taking to mechanical arm simultaneously; Vision system is divided coordinate to display window, calculates the Grid Track of induction point in camera window simultaneously;
Step 4, mechanical arm move to one of them preset point, suspend t second; Vision system is preserved now induction point at the coordinate information of display window; Simultaneously also by the coordinate information storage of preset point;
Step 5, repeating step three, four repeatedly, obtain a plurality of induction points at the coordinate information of display window: (X1, Y1), (X2, Y2), (X3, Y3) ... (Xn, Yn); And the coordinate information of corresponding a plurality of preset point: (x1, y1), (x2, y2) ... (xn, yn);
Step 6, set up coordinate mapping relations:
Try to achieve transition matrix; Obtain the transformational relation of the coordinate of robot vision system and the coordinate of robot coordinate system, thereby the coordinate completing in vision system is demarcated.
Between mechanical arm and robotic vision system, without communication, be connected, at mechanical arm, cover after preset dwell point, robotic vision system automatic acquisition image coordinate, calculates the transformational relation between arm-and-hand system coordinate and robotic vision system coordinate.
Further, when carrying out step 5, the induction point that obtains coordinate information is no less than 3.
Further, when carrying out step 5, obtain the induction point of coordinate information not point-blank.
Further, carrying out step 6 while solving transition matrix, mapping relations changed into:
;
;
Order matrix
;
;
,
;
;
Have: AX=b, AX '=b '; These two matrix equations are adopted respectively to least square method solution matrix X and X ', then obtain matrix
.
When solving approximate transition matrix, first matrix A is carried out to QR decomposition, i.e. A=QR; Wherein Q is orthogonal matrix, and upper triangular matrix during R, has: min||AX-b||=min||QRX-b||=min||RX-Q
-1b||; By least square method, solve again; Certainly can directly adopt MATLAB software to calculate.
The quick calibrating method of robotic vision system, for one of them vision system coordinate conversion is arrived to another vision system coordinate, comprises the following steps:
Step 1, scaling board is set, a plurality of preset point for two vision systems inductions are set on scaling board;
Step 2, provide a mechanical arm, mechanical arm arranges an induction point moving for demarcating mechanical arm; The movement rule of mechanical arm is set according to the position of preset point, and mechanical arm is subject to processing device and controls, and makes the each mobile rear induction point of mechanical arm all be positioned at the top of preset point:
Step 3, mechanical arm start mobile, and the first camera of one of them vision system and the second camera of another vision system are carried out image taking to mechanical arm respectively; The display window of two vision systems is divided respectively coordinate, and calculates the Grid Track of induction point in corresponding display window simultaneously;
Step 4, mechanical arm move to one of them preset point, suspend t second; Camera is preserved now induction point at the coordinate information of window; Simultaneously also by the coordinate information storage of preset point; Then mechanical arm moves to another preset point;
Step 5, repeating step three, four repeatedly, obtain the coordinate of a plurality of induction points in one of them vision system of coordinate information of respective window and be respectively: (R1, T1), (R2, T2), (R3, T3) ... (Rn, Tn); Coordinate in another vision system is respectively: (r1, t1), (r2, t2) ... (tn, tn);
Step 6, set up coordinate mapping relations:
Try to achieve transition matrix; Obtain the transformational relation of coordinate between two vision systems, thereby complete two coordinates in vision system, demarcate.
Further, when carrying out step 5, the induction point that obtains coordinate information is no less than 3.
Further, when carrying out step 5, obtain the induction point of coordinate information not point-blank.
Further, carrying out step 6 while solving transition matrix, mapping relations changed into:
;
;
Order matrix
;
;
;
;
; Have: BZ=m, BZ '=m '; These two matrix equations are adopted respectively to least square method solution matrix m and m ', then obtain matrix
.
The beneficial effect that the present invention obtains is: the present invention adopts the coordinate collection of vision system, then adopt the mode of transition matrix, carry out coordinate system and demarcate conversion, the relation between the automatic Calibration of relation between vision system and mechanical arm and vision system that can realize is rapidly demarcated, reduce artificial participation, there is simple and fast, practical.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of embodiments of the invention 1.
Fig. 2 is the schematic flow sheet of embodiments of the invention 2.
Embodiment
Below in conjunction with accompanying drawing 1 to Fig. 2 and embodiment, the present invention is described further.
Embodiment 1: referring to Fig. 1.
At present mechanical arm is generally all provided with own stepping coordinate system, the stepping program cutting as line etc.; When adopting vision system to control other gearings to coordinate with mechanical arm, the coordinate system of the coordinate system of vision system and mechanical arm need to be united.
The quick calibrating method of robotic vision system, for robot coordinate being transformed into a robotic vision system coordinate, it comprises the following steps:
Step 1, scaling board is set, a plurality of preset point for the induction of vision system camera head are set on scaling board, scaling board is set up to coordinate system; This coordinate system is the coordinate system based on robot device itself.These two coordinate systems are equal to.
Step 2, mechanical arm arrange an induction point moving for demarcating mechanical arm; The movement rule of mechanical arm is set in the coordinate system of mechanical arm according to the position of preset point, makes the each mobile rear induction point of mechanical arm all be positioned at the top of preset point:
Step 3, mechanical arm start mobile, and the camera head of vision system carries out image taking to mechanical arm simultaneously; Vision system is set up coordinate or vision system to display window and is set up its coordinate of coordinate system and be presented in display window, calculates induction point corresponding Grid Track in display window simultaneously;
Step 4, move to one of them preset point when mechanical arm, suspend t second, the t as required sensitivity of perception sets; Although vision system has calculated the Grid Track of induction point in display window, if induction point is always in moving process, can there is error in the coordinate points that Grid Track is corresponding, here arrange after pause step, during time-out, the changes in coordinates scope reading is very little, can be so that vision system captures the coordinate of induction point in display window accurately.Vision system is preserved the now coordinate information of induction point correspondence in display window; Also corresponding preset point is stored at the intrasystem coordinate information of robot coordinate simultaneously; Here suspend t second, be convenient to coordinate acquisition information.
Step 5, repeating step three, four repeatedly, obtain a plurality of induction points at the coordinate information of window: (X1, Y1), (X2, Y2), (X3, Y3) ... (Xn, Yn); And the coordinate information of corresponding a plurality of preset point: (x1, y1), (x2, y2) ... (xn, yn);
Carrying out coordinate timing signal, need to obtain the coordinate correspondence mappings relation of two coordinate systems, and the acquisition of mapping relations can obtain by the conversion of coordinates matrix and mapping point matrix:
Step 6, set up coordinate mapping relations:
Try to achieve transition matrix; Obtain the transformational relation of coordinate between camera and mechanical arm, thereby the coordinate completing in vision system is demarcated.
Further, when carrying out step 5, the induction point that obtains coordinate information is no less than 3.
In order to obtain more accurately transition matrix, the coordinate information that induction point is corresponding is no less than 3.Effect preferred version, the coordinate value of induction point is at 5-10.
Further, when carrying out step 5, obtain the induction point of coordinate information not point-blank.
With the coordinate information of straight line, in mapping process, there is defect, should avoid as far as possible.
Further, carrying out step 6 while solving transition matrix, mapping relations changed into:
;
;
Order matrix
;
;
,
;
;
Have: AX=b, AX '=b '; These two matrix equations are adopted respectively to least square method solution matrix X and X ', then obtain matrix
.
When obtaining transition matrix, because this transition matrix may not be an exact value, therefore need to try to achieve a transition matrix that error is lower; This transition matrix, by splitting, is then tried to achieve transition matrix by least square method.
Embodiment 2: referring to Fig. 2.
The quick calibrating method of robotic vision system, for one of them vision system coordinate conversion is arrived to another vision system coordinate, comprises the following steps:
Step 1, scaling board is set, a plurality of preset point for vision system induction are set on scaling board;
Step 2, provide a mechanical arm, mechanical arm arranges an induction point moving for demarcating mechanical arm; The movement rule of mechanical arm is set according to the position of preset point, and mechanical arm is subject to processing device and controls, and makes the each mobile rear induction point of mechanical arm all be positioned at the top of preset point:
Step 3, mechanical arm start mobile, and the first camera of one of them vision system and the second camera of another vision system are carried out image taking to mechanical arm respectively; The display window of two vision systems is divided respectively coordinate; Or the coordinate of two vision systems is presented at corresponding display window, and calculate the Grid Track of induction point in corresponding display window simultaneously;
Step 4, mechanical arm move to one of them preset point, suspend t second; Pause step is set, and after shooting, changes in coordinates scope is very little, with this automatic decision determine induction point in coordinate.Two vision systems are all preserved now induction point at the coordinate information of corresponding display window; Then mechanical arm moves to another preset point;
Step 5, repeating step three, four repeatedly, obtain a plurality of induction points at the coordinate information of corresponding display window; Coordinate in one of them vision system is respectively: (R1, T1), (R2, T2), (R3, T3) ... (Rn, Tn); Coordinate in another vision system is respectively: (r1, t1), (r2, t2) ... (tn, tn);
Step 6, set up coordinate mapping relations:
Try to achieve transition matrix; Obtain the transformational relation of coordinate between two vision systems, thereby complete two coordinates in vision system, demarcate.
Further, when carrying out step 5, the induction point that obtains coordinate information is no less than 3.
Further, when carrying out step 5, obtain the induction point of coordinate information not point-blank.
Further, carrying out step 6 while solving transition matrix, mapping relations changed into:
;
;
Order matrix
;
;
;
;
; Have: BZ=m, BZ '=m '; These two matrix equations are adopted respectively to least square method solution matrix m and m ', then obtain matrix
.
Below be only the application's preferred embodiment, equivalent technical solutions on this basis still falls into application protection domain.
Claims (6)
1. the quick calibrating method of robotic vision system, for robot coordinate being transformed into a robotic vision system, is characterized in that: it comprises the following steps:
Step 1, scaling board is set, a plurality of preset point of demarcating for vision system are set on scaling board;
Step 2, mechanical arm arrange an induction point moving for demarcating mechanical arm; The movement rule of mechanical arm is set according to the position of preset point, makes the each mobile rear induction point of mechanical arm all be positioned at the top of preset point:
Step 3, mechanical arm start mobile, and the camera head of vision system carries out image taking to mechanical arm simultaneously; Vision system is divided coordinate or vision system to display window and is set up its coordinate of coordinate system and be presented in display window, calculates the Grid Track of induction point in camera window simultaneously;
Step 4, mechanical arm move to one of them preset point, suspend t second; Vision system is preserved now induction point at the coordinate information of display window; Simultaneously also by the coordinate information storage of preset point;
Step 5, repeating step three, four repeatedly, obtain a plurality of induction points at the coordinate information of display window: (X1, Y1), (X2, Y2), (X3, Y3) ... (Xn, Yn); And the coordinate information of corresponding a plurality of preset point: (x1, y1), (x2, y2) ... (xn, yn);
Step 6, set up coordinate mapping relations:
Try to achieve transition matrix; Obtain the transformational relation of the coordinate of robot vision system and the coordinate of robot coordinate system, thereby the coordinate completing in vision system is demarcated.
2. the quick calibrating method of robotic vision system according to claim 1, is characterized in that: when carrying out step 5, the induction point that obtains coordinate information is no less than 3.
3. the quick calibrating method of robotic vision system according to claim 2, is characterized in that: when carrying out step 5, obtain the induction point of coordinate information not point-blank.
4. the quick calibrating method of robotic vision system, for by one of them vision system coordinate conversion to another vision system coordinate, it is characterized in that: comprise the following steps:
Step 1, scaling board is set, a plurality of preset point of demarcating for two vision systems are set on scaling board;
Step 2, provide a mechanical arm, mechanical arm arranges an induction point moving for demarcating mechanical arm; The movement rule of mechanical arm is set according to the position of preset point, makes the each mobile rear induction point of mechanical arm all be positioned at the top of preset point:
Step 3, mechanical arm start mobile, and the first camera of one of them vision system and the second camera of another vision system are carried out image taking to mechanical arm respectively; The display window of two vision systems is divided respectively coordinate, or the coordinate of two vision systems is presented at corresponding display window; And calculate the Grid Track of induction point in corresponding display window simultaneously;
Step 4, mechanical arm move to one of them preset point, suspend t second; Camera is preserved now induction point at the coordinate information of window; Simultaneously also by the coordinate information storage of preset point; Then mechanical arm moves to another preset point;
Step 5, repeating step three, four repeatedly, obtain the coordinate of a plurality of induction points in one of them vision system of coordinate information of respective window and be respectively: (R1, T1), (R2, T2), (R3, T3) ... (Rn, Tn); Coordinate in another vision system is respectively: (r1, t1), (r2, t2) ... (tn, tn);
Step 6, set up coordinate mapping relations:
Try to achieve transition matrix; Obtain the transformational relation of coordinate between two vision systems, thereby complete two coordinates in vision system, demarcate.
5. the quick calibrating method of robotic vision system according to claim 4, is characterized in that: when carrying out step 5, the induction point that obtains coordinate information is no less than 3.
6. the quick calibrating method of robotic vision system according to claim 5, is characterized in that: when carrying out step 5, obtain the induction point of coordinate information not point-blank.
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Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1727839A (en) * | 2004-07-28 | 2006-02-01 | 发那科株式会社 | Method of and device for re-calibrating three-dimensional visual sensor in robot system |
CN101285676A (en) * | 2008-06-10 | 2008-10-15 | 北京航空航天大学 | Multi-visual sense sensor calibration method based on one-dimensional target |
JP2010172986A (en) * | 2009-01-28 | 2010-08-12 | Fuji Electric Holdings Co Ltd | Robot vision system and automatic calibration method |
JP2011011321A (en) * | 2009-07-06 | 2011-01-20 | Fuji Electric Holdings Co Ltd | Robot system and calibration method for the same |
CN102848389A (en) * | 2012-08-22 | 2013-01-02 | 浙江大学 | Realization method for mechanical arm calibrating and tracking system based on visual motion capture |
CN103170980A (en) * | 2013-03-11 | 2013-06-26 | 常州铭赛机器人科技有限公司 | Positioning system and positioning method for household service robot |
CN103170973A (en) * | 2013-03-28 | 2013-06-26 | 上海理工大学 | Man-machine cooperation device and method based on Kinect video camera |
CN103363899A (en) * | 2013-07-05 | 2013-10-23 | 科瑞自动化技术(深圳)有限公司 | Calibration device and calibration method for calibrating coordinate system of robot arm |
-
2014
- 2014-07-31 CN CN201410371760.3A patent/CN104180753A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN1727839A (en) * | 2004-07-28 | 2006-02-01 | 发那科株式会社 | Method of and device for re-calibrating three-dimensional visual sensor in robot system |
CN101285676A (en) * | 2008-06-10 | 2008-10-15 | 北京航空航天大学 | Multi-visual sense sensor calibration method based on one-dimensional target |
JP2010172986A (en) * | 2009-01-28 | 2010-08-12 | Fuji Electric Holdings Co Ltd | Robot vision system and automatic calibration method |
JP2011011321A (en) * | 2009-07-06 | 2011-01-20 | Fuji Electric Holdings Co Ltd | Robot system and calibration method for the same |
CN102848389A (en) * | 2012-08-22 | 2013-01-02 | 浙江大学 | Realization method for mechanical arm calibrating and tracking system based on visual motion capture |
CN103170980A (en) * | 2013-03-11 | 2013-06-26 | 常州铭赛机器人科技有限公司 | Positioning system and positioning method for household service robot |
CN103170973A (en) * | 2013-03-28 | 2013-06-26 | 上海理工大学 | Man-machine cooperation device and method based on Kinect video camera |
CN103363899A (en) * | 2013-07-05 | 2013-10-23 | 科瑞自动化技术(深圳)有限公司 | Calibration device and calibration method for calibrating coordinate system of robot arm |
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