CN115439633A - Calibration method and device and electronic equipment - Google Patents
Calibration method and device and electronic equipment Download PDFInfo
- Publication number
- CN115439633A CN115439633A CN202211167533.XA CN202211167533A CN115439633A CN 115439633 A CN115439633 A CN 115439633A CN 202211167533 A CN202211167533 A CN 202211167533A CN 115439633 A CN115439633 A CN 115439633A
- Authority
- CN
- China
- Prior art keywords
- robot
- point cloud
- acquisition device
- calibration
- calibrated
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 57
- 239000012636 effector Substances 0.000 claims description 26
- 238000012545 processing Methods 0.000 claims description 13
- 238000004590 computer program Methods 0.000 claims description 12
- 230000009466 transformation Effects 0.000 claims description 4
- 239000003550 marker Substances 0.000 description 11
- 238000010586 diagram Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/20—Finite element generation, e.g. wire-frame surface description, tesselation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
- G06T7/85—Stereo camera calibration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30244—Camera pose
Abstract
The disclosure provides a calibration method, a calibration device and electronic equipment, wherein the calibration method comprises the following steps: sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged when the robot is calibrated, and the model parameters of the robot are unchanged when the point cloud acquisition device is calibrated; and determining whether a first preset condition is met, if not, performing the steps of calibrating the robot and the point cloud acquisition device in sequence based on the calibrated external parameters and the calibrated model parameters, and further accurately determining the calibration determination pattern. According to the method and the device, the precision of the robot system can be improved in an iteration calibration mode.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a calibration method, a calibration device, and an electronic device.
Background
The robot system comprises a robot and a point cloud acquisition device, wherein the robot system carries out position positioning based on point cloud data of an object to be processed acquired by the point cloud acquisition device to obtain position information of the object to be processed; and then, controlling the end effector of the robot to move to a target position corresponding to the position information. However, the target position and the ideal position have a certain deviation, so that the accuracy of the robot system is not satisfactory.
Disclosure of Invention
Aspects of the present disclosure provide a calibration method, a calibration device, and an electronic device, so as to solve a problem that the accuracy of a current robot system does not meet requirements.
The first aspect of the embodiments of the present disclosure provides a calibration method, which is applied to a robot system, where the robot system includes a robot and a point cloud collection device, and the calibration method includes: sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged when the robot is calibrated, and the model parameters of the robot are unchanged when the point cloud acquisition device is calibrated; and determining whether a first preset condition is met, and if not, executing the steps of calibrating the robot and the point cloud acquisition device in sequence based on the calibrated external parameters and the calibrated model parameters.
A second aspect of the embodiments of the present disclosure provides a calibration apparatus for executing the calibration method of the first aspect, including:
the calibration module is used for sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged when the robot is calibrated, and the model parameters of the robot are unchanged when the point cloud acquisition device is calibrated;
and the processing module is used for determining whether a first preset condition is met, and if not, executing the steps of calibrating the robot and the point cloud acquisition device in sequence based on the calibrated external parameters and the calibrated model parameters.
A third aspect of the embodiments of the present disclosure provides an electronic device, including: a processor, a memory and a computer program stored on the memory and executable on the processor, the calibration method of the first aspect being implemented when the processor executes the computer program.
A fourth aspect of the embodiments of the present disclosure provides a computer-readable storage medium, where computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, the calibration method of the first aspect is implemented.
A fifth aspect of an embodiment of the present disclosure provides a computer program product, including: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, and the execution of the computer program by the at least one processor causes the electronic device to perform the calibration method of the first aspect.
The embodiment of the disclosure is applied to a calibration scene of a robot system, and comprises the following steps: sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged when the robot is calibrated, and the model parameters of the robot are unchanged when the point cloud acquisition device is calibrated; and determining whether a first preset condition is met, if not, performing the steps of calibrating the robot and the point cloud acquisition device in sequence based on the calibrated external parameters and the calibrated model parameters, and further accurately determining the calibration determination pattern. According to the method and the device, the precision of the robot system can be improved in an iteration calibration mode.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and not to limit the disclosure. In the drawings:
fig. 1 is an application scenario diagram of a calibration method according to an exemplary embodiment of the present disclosure;
fig. 2 is an application scenario diagram of another calibration method provided in an exemplary embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating steps of a calibration method provided in an exemplary embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a calibration method provided by an exemplary embodiment of the present disclosure;
FIG. 5 is a schematic diagram of another calibration method provided in an exemplary embodiment of the present disclosure;
fig. 6 is a block diagram of a calibration apparatus provided in an exemplary embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the present disclosure more apparent, the following embodiments of the present disclosure will be clearly and completely described in conjunction with the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
In the calibration process of the robot system, the point cloud collection device and the robot are usually calibrated separately. For example, the point cloud collection device is calibrated for a plurality of times until the point cloud collection device reaches the calibration precision, and then the robot is calibrated for a plurality of times until the robot reaches the calibration precision. The method can only ensure the respective precision of the cloud acquisition device and the robot, but cannot ensure the precision when the cloud acquisition device and the robot cooperate, and further can influence the execution precision of a robot system.
Based on the above problems, the embodiment of the present disclosure obtains the calibrated model parameters of the robot and the external parameters of the point cloud collection device by sequentially calibrating the robot and the point cloud collection device, where the external parameters of the point cloud collection device are not changed when calibrating the robot, and the model parameters of the robot are not changed when calibrating the point cloud collection device; and determining whether the first preset condition is met, if not, performing the step of sequentially calibrating the robot and the point cloud acquisition device based on the calibrated external parameters and the model parameters, further accurately determining a calibration pattern, and performing iterative calibration on the point cloud acquisition device and the robot in a combined manner to improve the precision of the robot system.
In addition, an application scenario of the embodiment of the present disclosure is a robot system shown in fig. 1 and 2, and the robot system shown in fig. 1 includes: point cloud collection system 11 and robot, wherein the robot includes: an end effector 12, a robot base 14, and at least two motion segments 13 mounted between the end effector 12 and the robot base 14. The robot system of fig. 1 further includes a marker reference B. In fig. 1, a point cloud collection device 11 is fixed on an end effector 12 of the robot, and a marker reference B is fixed outside the robot.
The robot system shown in fig. 2 includes: point cloud collection system 21 and robot, wherein the robot includes: an end effector 22, a robot base 24 and at least two motion segments 23 mounted between the end effector 22 and the robot base 24. The robot system of fig. 2 further includes a marker reference B. In fig. 2, the point cloud collection device 21 is fixedly installed outside the robot, and the marker reference B is fixed to the end effector 22 of the robot.
Fig. 1 and fig. 2 are only an exemplary application scenario, and the embodiment of the present disclosure may be applied to any calibration of a robot system. The embodiments of the present disclosure do not limit specific application scenarios.
Fig. 3 is a flowchart illustrating steps of a calibration method according to an exemplary embodiment of the present disclosure. The method specifically comprises the following steps:
s301, calibrating the robot and the point cloud acquisition device in sequence to obtain the calibrated model parameters of the robot and the external parameters of the point cloud acquisition device.
When the robot is calibrated, the external parameters of the point cloud acquisition device are unchanged, and when the point cloud acquisition device is calibrated, the model parameters of the robot are unchanged. Specifically, the robot may be calibrated under the condition that the external parameters of the point cloud acquisition device are not changed, and then the point cloud acquisition device may be calibrated under the condition that the model parameters of the robot are set to be changed. Or calibrating the point cloud acquisition device under the condition that the model parameters of the robot are not changed, and then calibrating the robot under the condition that the external parameters of the point cloud acquisition device are not changed. In a round of calibration process, the sequence of calibration of the robot and the point cloud acquisition device is not limited by the disclosure.
In an optional embodiment, the calibration of the robot and the point cloud collecting device is performed in sequence, and comprises: calibrating the robot by adopting the current external parameters of the point cloud acquisition device to obtain the calibrated model parameters of the robot; and calibrating the external parameter of the point cloud acquisition device by using the calibrated model parameter of the robot to obtain the external parameter of the point cloud acquisition device after calibration, wherein the calibrated external parameter is used for calibrating the robot next time.
Referring to fig. 4, the robot system is calibrated for n rounds, where n is a positive integer. And each round of calibration of the robot system comprises calibration of the robot and the point cloud acquisition device. In fig. 4, the robot is calibrated to obtain a calibrated model parameter M1, and then the point cloud collection device is calibrated by using the calibrated model parameter M1 to obtain a calibrated external parameter W1. It can be understood that each calibration round of the robot system will result in calibrated model parameters and calibrated external parameters. The calibrated external parameter is used for calibrating the robot in the next round of calibration process, when the robot is calibrated in the next round, the corresponding model parameter of the robot is M1, and the calibrated model parameter is M2. Therefore, the calibrated model parameter M1 and the calibrated external parameter W1 obtained by the calibration of the current round can be used for the calibration of the robot system of the next round.
Further, in fig. 4, the external parameter obtained after calibration in the previous calibration round can be used as the current external parameter in the next calibration round. For example, the robot system is calibrated for the second round, the calibrated external parameter W1 is used as the current external parameter, and the robot is calibrated to obtain the calibrated model parameter M2. When the robot is calibrated, the external parameter W1 of the point cloud acquisition device is unchanged. And then, when the calibrated model parameter M2 is used for calibrating the point cloud acquisition device, the model parameter M2 of the robot is unchanged.
In fig. 1 and 2, a first coordinate system (XYZ) of the robot base is established with the robot base as an origin O, where a Z-axis represents a vertical direction. X and Y are located in a horizontal plane, and three coordinate axes are perpendicular to each other. And a second coordinate system (X ' Y ' Z ') of the point cloud acquisition device, wherein the point cloud acquisition device is a coordinate system origin O ', a Z ' axis is the direction of a view field central axis of the point cloud acquisition device, and X ' Y ' is a plane perpendicular to the view field central axis. And a third coordinate system (X "Y" Z ") of the end effector, with a fixed point on the end effector (e.g., the center of the flange) as the origin O" of the coordinate system, the Z "axis being perpendicular to the surface of the flange, the X" axis and the Y "axis being perpendicular to each other and parallel to the surface of the flange.
Specifically, on the basis of fig. 4, for the robot system of fig. 1, the point cloud collecting device 11 is fixed on the end effector 12 of the robot, the calibration standard B is fixedly installed outside the robot, and the robot is calibrated by using the current external reference of the point cloud collecting device, including: based on the current external reference of the point cloud acquisition device, determining a third reference position of a calibration reference object in a first coordinate system of a robot base under the condition that a third preset control parameter is adopted to control the robot to be in a third posture; based on the current external parameters of the point cloud acquisition device, determining a fourth reference position of the calibration reference object in the first coordinate system under the condition that a fourth preset control parameter is adopted to control the robot to be in a fourth pose; and calibrating the model parameters of the robot according to the deviation of the third reference position and the fourth reference position to obtain the calibrated model parameters.
In fig. 1, the external reference of the point cloud collection device 11 indicates a transformation relationship of the second coordinate system (X ' Y ' Z ') of the point cloud collection device 11 with respect to the third coordinate system (X "Y" Z ") of the end effector 12. The end effector 12 drives the point cloud collecting device 11 to move.
Furthermore, the robot's control parameters, which may include motion parameters (e.g., rotation and/or translation) of each motion segment 13, may control the robot's pose, and the control parameters are input parameters to a robot model, such as parameters in a positive kinematic equation, from which the theoretical position of the end effector in the first coordinate system can be calculated by the robot model.
Further, based on the current external reference of the point cloud acquisition device, determining a third reference position of the calibration reference object in the first coordinate system of the robot base under the condition that the robot is controlled to be in a third posture by adopting a third preset control parameter, and the method comprises the following steps: in the third pose, a third reference point cloud of the calibration standard B is acquired by the point cloud acquisition device 12, wherein the third reference point cloud comprises a third camera position of a point on the calibration standard in the second coordinate system (X ' Y ' Z '), and then a third execution position of the calibration standard in a third coordinate system (X "Y" Z ") of the end effector can be determined based on the third camera position and the current external reference. Then, a third theoretical position (theoretical position in the first coordinate system) of the end effector is calculated according to the third preset control parameter and the model parameter of the current robot model, and then, according to the third theoretical position and the third execution position, the position of the calibration standard object B in the first coordinate system (XYZ) of the robot base 14 can be calculated as a third reference position. In addition, the fourth reference position is determined in the same manner under the condition that the control parameter is changed to the fourth preset control parameter. The calibration standard B is fixed and unchanged, so the calculated third reference position and the fourth reference position should be the same, and if the difference is different, the model parameter of the robot may be adjusted by using the difference between the third reference position and the fourth reference position.
Further, calibrating external parameters of the point cloud acquisition device by using the calibrated model parameters of the robot, comprising: controlling a point cloud acquisition device to acquire a third point cloud aiming at a calibration reference object under the condition that a fifth preset control parameter is adopted to control the robot to be in a fifth pose on the basis of the calibrated model parameter of the robot; determining a fifth reference position of the calibration reference object under the first coordinate system according to the third point cloud, the current external reference of the point cloud acquisition device and the calibrated model parameters of the robot; controlling a point cloud acquisition device to acquire a fourth point cloud aiming at a calibration reference object under the condition that a sixth preset control parameter is adopted to control the robot to be in a sixth pose based on the calibrated model parameter of the robot; determining a sixth reference position of the calibration reference object in the first coordinate system according to the fourth point cloud, the current external parameters of the point cloud acquisition device and the calibrated model parameters of the robot; and calibrating the external parameters of the point cloud acquisition device according to the deviation of the fifth reference position and the sixth reference position to obtain calibrated external parameters.
Specifically, after the robot is calibrated, the model parameter of the robot model is a calibrated model parameter, the robot is controlled to be in a fifth pose according to a fifth preset control parameter and a calibrated model parameter, the point cloud acquisition device 11 is controlled to acquire a third point cloud for the calibration standard B in the fifth pose, a fifth execution position of the calibration standard B in a third coordinate system (X "Y" Z ") is determined according to the third point cloud and the current external reference, a theoretical position of the end effector 12 in the first coordinate system can be calculated according to the calibrated model parameter and the fifth preset control parameter, a fifth reference position of the marker standard B in the first coordinate system can be obtained according to the theoretical position and the fifth execution position, a sixth reference position can be determined in the same manner when the control parameter is changed to the sixth preset control parameter, and the position of the marker standard B is unchanged, so that the fifth reference position and the sixth reference position should be the same under an ideal condition, and if the position of the marker standard point cloud is different, the external reference position of the calibration standard point cloud acquisition device is obtained.
In summary, the calibration method can calibrate the robot system shown in fig. 1, so that the calibrated robot system has higher precision.
Alternatively, on the basis of fig. 4, for the robot system of fig. 2, the calibration standard B is fixed on the end effector 22 of the robot, the point cloud collecting device 21 is fixedly installed outside the robot, and the robot is calibrated by using the current external reference of the point cloud collecting device, including: controlling the robot to be in a first pose by adopting a first preset control parameter based on the current robot model of the robot; controlling a point cloud acquisition device to acquire a first point cloud aiming at a calibration reference object under the state that the robot is in a first pose; determining a first reference position of a calibration standard object in a first coordinate system of a robot base according to the first point cloud and current external parameters of a current point cloud acquisition device, wherein the external parameters of the point cloud acquisition device comprise: the transformation relation of a second coordinate system of the point cloud acquisition device relative to the first coordinate system; inputting the first preset control parameter into the current robot model for parameter processing to obtain a first theoretical position of the calibration reference object in a first coordinate system; and calibrating the model parameters of the robot according to the deviation of the first theoretical position and the first reference position to obtain the calibrated model parameters.
When the robot is calibrated, the robot is controlled to be in a first pose by adopting a first preset control parameter under the current robot model, namely the first preset control parameter is input into the robot, and the robot is controlled to be in the first pose. When the robot is in the first pose, a first point cloud is acquired, and the first point cloud represents the position of the marker reference object B in the second coordinate system of the point cloud acquisition device 21. Then, a first reference position of the marking object B in the first coordinate system of the robot base 24 can be determined according to the first point cloud and the current external reference, then, a first preset control parameter is input into the current robot model for parameter processing, and the theoretical position of the end effector in the first coordinate system is obtained. And if the first reference position to which the robot moves is different from the first theoretical position obtained by calculation, calibrating the model parameters of the robot by adopting the difference value of the first reference position and the first theoretical position, so that the model parameters of the robot model are calibrated model parameters.
Further, calibrating external parameters of the point cloud acquisition device by using the calibrated model parameters of the robot, comprising: on the basis of the calibrated model parameters of the robot, a second preset control parameter is adopted to control the robot to be in a second pose; controlling the point cloud acquisition device to acquire a second point cloud aiming at the calibration reference object under the state that the robot is in a second pose; determining a second reference position of the calibration standard object in the first coordinate system according to the second point cloud and the current external parameters of the point cloud acquisition device; inputting a second preset control parameter into the calibrated robot model for parameter processing to obtain a second theoretical position of the calibration reference object in the first coordinate system; and calibrating the external parameter of the point cloud acquisition device according to the deviation of the second theoretical position and the second reference position to obtain the calibrated external parameter.
Specifically, in the calibration of the point cloud acquisition device, the model parameters of the robot model are the calibrated model parameters, and under the calibrated model parameters, the robot is controlled to be in the second pose by adopting the second preset control parameters, that is, the second preset control parameters are input into the robot to control the robot to be in the second pose. When the robot is in the second pose, acquiring second point cloud, determining a second reference position of the marker object B in the first coordinate system of the robot base 24 according to the second point cloud and the current external reference, inputting second preset control parameters into the calibrated robot model for parameter processing, and obtaining a theoretical position of the end effector in the first coordinate system. And if the second reference position obtained by the external parameter calculation is different from the calculated second theoretical position, calibrating the external parameter of the point cloud acquisition device by adopting the difference value of the second reference position and the second theoretical position, so that the external parameter of the point cloud acquisition device is the calibrated external parameter.
In another optional embodiment, calibrating the robot and the point cloud collecting device in sequence includes: calibrating external parameters of the point cloud acquisition device by using current model parameters of the robot; and calibrating the model parameters of the robot by using the calibrated external parameters, wherein the calibrated model parameters are used for calibrating the external parameters of the next point cloud acquisition device.
Referring to fig. 5, in each round of calibration, the point cloud collection device is calibrated by using the current model parameters to obtain calibrated external parameters, and then the robot is calibrated by using the calibrated external parameters to obtain calibrated model parameters. The obtained external parameters after calibration and the model parameters after calibration can be applied to the next round of calibration.
In addition, the calibration method shown in fig. 5 may also be applied to the calibration of the robot system shown in fig. 1 and fig. 2, and the calibration method may refer to the calibration method corresponding to the description of fig. 4, and is also used for calibrating the robot when the point cloud acquisition device is unchanged, and is not described herein again.
S302, determining whether a first preset condition is met.
If so, ending the calibration, otherwise, executing S301 based on the calibrated external parameters and the model parameters.
Referring to fig. 4 to 6, based on the calibrated external parameters and the model parameters, in S301, the calibration sequence of the robot and the point cloud collection device may be the same as or different from the previous calibration sequence.
For example, in fig. 4, in the first round of calibration, the model parameter obtained after the robot is calibrated is M1, and the point cloud acquisition device is calibrated by using the model parameter M1, so as to obtain the external parameter W1 after calibration. And during the second round of calibration, the current model parameter of the robot is M1, the robot is calibrated by adopting the external parameter W1 to obtain a calibrated model parameter M2, in the second round of calibration, the external parameter of the point cloud acquisition device is W1, and the external parameter W2 is obtained after the point cloud acquisition device is calibrated by adopting the model parameter M2. After n rounds of calibration, the model parameter of the robot is Mn, and the external parameter of the point cloud acquisition device is Wn. In fig. 5, after n rounds of calibration, the external parameter of the point cloud collection device is On, and the model parameter of the robot is Pn.
Further, in the present disclosure, the point cloud collection device may be separately calibrated first, and after the point cloud collection device is calibrated to meet a certain requirement, the steps shown in fig. 4 of the present disclosure are executed, and the robot and the point cloud collection device are combined to perform calibration, so that the execution precision of the robot system as a whole is improved.
Specifically, determining whether a first preset condition is met includes: determining the execution precision of the robot system based on the calibrated external parameters and the model parameters; determining whether the execution precision meets a preset precision requirement; or, determining whether the calibration times of the robot system are preset times.
Specifically, the execution accuracy of the robot system is specifically that an actual coordinate of a calibration standard object in a first coordinate system is known, a point cloud acquisition device is used for carrying out point cloud acquisition on the calibration standard object, then a theoretical position of the calibration standard object in the first coordinate system is obtained through external reference of the point cloud acquisition device and calculation of a robot model, then the end effector is controlled to move according to the theoretical position, and a difference value between the actual position where the end effector moves and the actual position of the calibration standard object represents the execution accuracy of the robot system, wherein the larger the difference value is, the lower the execution accuracy is, the smaller the difference value is, and the higher the execution accuracy is. In the present disclosure, the accuracy requirement may be preset, such as setting the difference to be less than 2mm, or less than 3mm.
Optionally, due to different structures of the robot system, for example, due to the influence of the pixels of the point cloud acquisition device, the difference value cannot reach a state of 0, so that different calibration times can be set according to different robot systems, for example, 3 times, and the robot system determines to complete calibration after performing S301 for three times.
Exemplary, referring to tables 1 and 2, the execution accuracy after calibration for different numbers of wheels for the robotic system shown in fig. 1 under different experimental environments is given. The uncalibrated mode is to adopt the method disclosed by the present disclosure for calibration, the difference value is a difference value between the actual position of the control end effector after movement and the actual position of the calibration reference object, and the percentage is the percentage of the number of times of the obtained difference value in the corresponding difference value range in the total number of times after multiple experiments. In table 1, the distances from the robot model A1, the point cloud collecting device B1, and the point cloud collecting device to the marker reference are 300mm to 500mm.
TABLE 1
It can be seen that as the number of iterations (number of calibration rounds) increases in table 1, the smaller the corresponding difference of the robot system, the higher the execution accuracy. After the four times of iterative calibration, the execution precision of the robot system and the execution precision of the robot system after the three times of iterative calibration have smaller changes.
In table 2, the distances from the robot model A2, the point cloud collecting device B2, and the point cloud collecting device to the marker reference are 800mm to 1000mm.
TABLE 2
It can be seen that as the number of iterations (number of calibration rounds) increases in table 2, the smaller the corresponding difference of the robot system, the higher the execution accuracy. With reference to tables 1 and 2, it can be seen that different robot systems have different achievable execution accuracies. Differences of less than 0.6mm can be achieved in table 1 and differences of less than 2.4mm can be achieved in table 2. In conclusion, the iterative calibration can improve the execution precision of the robot system.
The embodiment of the disclosure is applied to a calibration scene of a robot system, and comprises the following steps: sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged when the robot is calibrated, and the model parameters of the robot are unchanged when the point cloud acquisition device is calibrated; and determining whether a first preset condition is met, if not, performing the steps of calibrating the robot and the point cloud acquisition device in sequence based on the calibrated external parameters and the calibrated model parameters, and further accurately determining the calibration determination pattern. According to the method and the device, the precision of the robot system can be improved in an iteration calibration mode.
In the embodiment of the present disclosure, referring to fig. 6, in addition to providing a calibration method, a calibration apparatus 60 is provided to apply the calibration method described above, including:
the calibration module 61 is used for sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged when the robot is calibrated, and the model parameters of the robot are unchanged when the point cloud acquisition device is calibrated;
and the processing module 62 is configured to determine whether a first preset condition is met, and if not, execute the steps of sequentially calibrating the robot and the point cloud acquisition device based on the calibrated external parameters and the calibrated model parameters.
In an alternative embodiment, the calibration module 61 is specifically configured to: calibrating the robot by adopting the current external parameters of the point cloud acquisition device to obtain the calibrated model parameters of the robot; and calibrating the external parameter of the point cloud acquisition device by using the calibrated model parameter of the robot to obtain the external parameter of the point cloud acquisition device after calibration, wherein the calibrated external parameter is used for calibrating the robot next time.
In an alternative embodiment, the calibration standard is fixed on the end effector of the robot, the point cloud collecting device is fixedly installed outside the robot, and the calibration module 61 is specifically configured to: controlling the robot to be in a first pose by adopting a first preset control parameter based on the current robot model of the robot; controlling a point cloud acquisition device to acquire first point cloud aiming at a calibration reference object under the state that the robot is in a first pose; determining a first reference position of a calibration reference object in a first coordinate system of a robot base according to the first point cloud and current external parameters of a current point cloud acquisition device, wherein the external parameters of the point cloud acquisition device comprise: the transformation relation of a second coordinate system of the point cloud acquisition device relative to the first coordinate system; inputting the first preset control parameter into the current robot model for parameter processing to obtain a first theoretical position of the calibration reference object in a first coordinate system; and calibrating the model parameters of the robot according to the deviation of the first theoretical position and the first reference position to obtain the calibrated model parameters.
In an optional embodiment, when the calibration module 61 calibrates the external parameter of the point cloud acquiring device by using the calibrated model parameter of the robot, the calibration module is specifically configured to: on the basis of the calibrated model parameters of the robot, a second preset control parameter is adopted to control the robot to be at a second pose; controlling the point cloud acquisition device to acquire a second point cloud aiming at the calibration reference object under the state that the robot is in a second pose; determining a second reference position of the calibration standard object in the first coordinate system according to the second point cloud and the current external parameters of the point cloud acquisition device; inputting a second preset control parameter into the calibrated robot model for parameter processing to obtain a second theoretical position of the calibration reference object in the first coordinate system; and calibrating the external parameters of the point cloud acquisition device according to the deviation of the second theoretical position and the second reference position to obtain calibrated external parameters.
In an alternative embodiment, the point cloud collecting device is fixed on the end effector of the robot, the calibration standard is fixedly installed outside the robot, and the calibration module 61 is specifically configured to: based on the current external reference of the point cloud acquisition device, determining a third reference position of a calibration reference object in a first coordinate system of a robot base under the condition that a third preset control parameter is adopted to control the robot to be in a third posture; based on the current external parameters of the point cloud acquisition device, determining a fourth reference position of the calibration reference object in the first coordinate system under the condition that a fourth preset control parameter is adopted to control the robot to be in a fourth pose; and calibrating the model parameters of the robot according to the deviation of the third reference position and the fourth reference position to obtain the calibrated model parameters.
In an optional embodiment, the calibration module 61 is specifically configured to, when calibrating the external parameters of the point cloud acquisition device by using the calibrated model parameters of the robot: controlling a point cloud acquisition device to acquire a third point cloud aiming at a calibration reference object under the condition that a fifth preset control parameter is adopted to control the robot to be in a fifth pose based on the calibrated model parameter of the robot; determining a fifth reference position of the calibration reference object in the first coordinate system according to the third point cloud, the current external reference of the point cloud acquisition device and the calibrated model parameters of the robot; controlling a point cloud acquisition device to acquire a fourth point cloud aiming at a calibration reference object under the condition that a sixth preset control parameter is adopted to control the robot to be in a sixth pose based on the calibrated model parameter of the robot; determining a sixth reference position of the calibration reference object in the first coordinate system according to the fourth point cloud, the current external parameters of the point cloud acquisition device and the calibrated model parameters of the robot; and calibrating the external parameters of the point cloud acquisition device according to the deviation of the fifth reference position and the sixth reference position to obtain calibrated external parameters.
In an alternative embodiment, the calibration module 61 is specifically configured to: calibrating external parameters of the point cloud acquisition device by adopting current model parameters of the robot; and calibrating the model parameters of the robot by using the calibrated external parameters, wherein the calibrated model parameters are used for calibrating the external parameters of the next point cloud acquisition device.
In an optional embodiment, the processing module 62 is specifically configured to: determining the execution precision of the robot system based on the calibrated external parameters and the model parameters; determining whether the execution precision meets a preset precision requirement; or, determining whether the calibration times of the robot system are preset times.
The calibration device provided by the embodiment of the disclosure can improve the precision of the robot system in an iterative calibration mode.
In addition, in some of the flows described in the above embodiments and the drawings, a plurality of operations are included in a certain order, but it should be clearly understood that the operations may be executed out of the order presented herein or in parallel, and only for distinguishing between different operations, and the sequence number itself does not represent any execution order. Additionally, the flows may include more or fewer operations, and the operations may be performed sequentially or in parallel. It should be noted that, the descriptions of "first", "second", etc. in this document are used for distinguishing different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit the types of "first" and "second".
Fig. 7 is a schematic structural diagram of an electronic device according to an example embodiment of the present disclosure. As shown in fig. 7, the electronic apparatus 70 includes: a processor 71, and a memory 72 communicatively coupled to the processor 71, the memory 72 storing computer-executable instructions, the electronic device may be the robotic system described above.
The processor executes the computer execution instruction stored in the memory to implement the calibration method provided in any of the above method embodiments, and the specific functions and technical effects that can be implemented are not described herein again.
The embodiment of the present disclosure further provides a computer-readable storage medium, where computer-executable instructions are stored in the computer-readable storage medium, and when the computer-executable instructions are executed by a processor, the computer-executable instructions are used to implement the calibration method provided by any one of the method embodiments.
An embodiment of the present disclosure further provides a computer program product, where the program product includes: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, and the execution of the computer program by the at least one processor causes the electronic device to perform the calibration method provided by any of the above method embodiments.
In the several embodiments provided in the present disclosure, it should be understood that the disclosed system and method may be implemented in other ways. For example, the above-described system embodiments are merely illustrative, and for example, a division of a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, systems or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present disclosure. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above functions may be distributed by different functional modules according to needs, that is, the internal structure of the system is divided into different functional modules to complete all or part of the above described functions. For the specific working process of the system described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice in the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (11)
1. A calibration method is applied to a robot system, the robot system comprises a robot and a point cloud acquisition device, and the calibration method comprises the following steps:
sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged when the robot is calibrated, and the model parameters of the robot are unchanged when the point cloud acquisition device is calibrated;
and determining whether a first preset condition is met, and if not, executing the steps of calibrating the robot and the point cloud acquisition device in sequence based on the calibrated external parameters and the model parameters.
2. The calibration method according to claim 1, wherein the sequentially calibrating the robot and the point cloud collection device to obtain the calibrated model parameters of the robot and the external parameters of the point cloud collection device comprises:
calibrating the robot by using the current external parameters of the point cloud acquisition device to obtain calibrated model parameters of the robot;
and calibrating the external parameter of the point cloud acquisition device by using the calibrated model parameter of the robot to obtain the calibrated external parameter of the point cloud acquisition device, wherein the calibrated external parameter is used for calibrating the robot next time.
3. The calibration method according to claim 2, wherein a calibration reference is fixed on an end effector of the robot, the point cloud collection device is fixedly installed outside the robot, and the calibration of the robot using the current external reference of the point cloud collection device comprises:
controlling the robot to be in a first pose by adopting a first preset control parameter based on the current robot model of the robot;
controlling the point cloud acquisition device to acquire a first point cloud aiming at the calibration reference object in the state that the robot is in the first pose;
determining a first reference position of the calibration reference object in a first coordinate system of a robot base according to the first point cloud and the current external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device comprise: a transformation relationship of a second coordinate system of the point cloud acquisition device relative to the first coordinate system;
inputting the first preset control parameter into a current robot model for parameter processing to obtain a first theoretical position of the calibration reference object in the first coordinate system;
and calibrating the model parameters of the robot according to the deviation between the first theoretical position and the first reference position to obtain calibrated model parameters.
4. The calibration method according to claim 3, wherein the calibrating the external parameters of the point cloud collection device by using the calibrated model parameters of the robot comprises:
on the basis of the calibrated model parameters of the robot, adopting second preset control parameters to control the robot to be in a second pose;
controlling the point cloud acquisition device to acquire a second point cloud aiming at the calibration reference object in the state that the robot is in the second pose;
determining a second reference position of the calibration reference object in the first coordinate system according to the second point cloud and the current external parameters of the point cloud acquisition device;
inputting the second preset control parameter into the calibrated robot model for parameter processing to obtain a second theoretical position of the calibration reference object in the first coordinate system;
and calibrating the external parameter of the point cloud acquisition device according to the deviation between the second theoretical position and the second reference position to obtain the calibrated external parameter.
5. The calibration method according to claim 2, wherein the point cloud collection device is fixed on an end effector of the robot, a calibration reference is fixedly installed outside the robot, and the calibration of the robot using the current external reference of the point cloud collection device comprises:
based on the current external reference of the point cloud acquisition device, determining a third reference position of the calibration reference object in a first coordinate system of a robot base under the condition that a third preset control parameter is adopted to control the robot to be in a third posture;
based on the current external reference of the point cloud acquisition device, determining a fourth reference position of the calibration standard object in the first coordinate system under the condition that a fourth preset control parameter is adopted to control the robot to be a fourth pose;
and calibrating the model parameters of the robot according to the deviation of the third reference position and the fourth reference position to obtain calibrated model parameters.
6. The calibration method according to claim 5, wherein the calibrating the external parameters of the point cloud collection device by using the calibrated model parameters of the robot comprises:
controlling the point cloud acquisition device to acquire a third point cloud aiming at the calibration reference object under the condition that a fifth preset control parameter is adopted to control the robot to be in a fifth pose on the basis of the calibrated model parameter of the robot;
determining a fifth reference position of the calibration reference object under the first coordinate system according to the third point cloud, the current external reference of the point cloud acquisition device and the calibrated model parameters of the robot;
controlling the point cloud acquisition device to acquire a fourth point cloud aiming at the calibration reference object under the condition that the robot is controlled to have a sixth pose by adopting a sixth preset control parameter based on the calibrated model parameter of the robot;
determining a sixth reference position under the first coordinate system according to the fourth point cloud, the current external parameters of the point cloud acquisition device and the calibrated model parameters of the robot;
and calibrating the external reference of the point cloud acquisition device according to the deviation between the fifth reference position and the sixth reference position to obtain the calibrated external reference.
7. The calibration method according to claim 1, wherein the calibrating the robot and the point cloud collecting device in sequence comprises:
calibrating external parameters of the point cloud acquisition device by adopting current model parameters of the robot;
and calibrating the model parameters of the robot by using the calibrated external parameters, wherein the calibrated model parameters are used for calibrating the external parameters of the point cloud acquisition device next time.
8. The calibration method according to any one of claims 1 to 7, wherein the determining whether the first preset condition is met comprises:
determining the execution precision of the robot system based on the calibrated external parameters and the model parameters;
determining whether the execution precision meets a preset precision requirement;
or the like, or, alternatively,
and determining whether the calibration times of the robot system are preset times.
9. A calibration apparatus for performing the calibration method as claimed in any one of claims 1 to 8, applied to a robot system, the robot system comprising a robot and a point cloud collecting apparatus, the calibration apparatus comprising:
the calibration module is used for sequentially calibrating the robot and the point cloud acquisition device to obtain calibrated model parameters of the robot and external parameters of the point cloud acquisition device, wherein the external parameters of the point cloud acquisition device are unchanged during calibration of the robot, and the model parameters of the robot are unchanged during calibration of the point cloud acquisition device;
and the processing module is used for determining whether a first preset condition is met, and if not, executing the steps of calibrating the robot and the point cloud acquisition device in sequence based on the calibrated external parameters and the model parameters.
10. An electronic device, comprising: a processor, a memory and a computer program stored on the memory and executable on the processor, the processor implementing the calibration method as claimed in any one of claims 1 to 8 when executing the computer program.
11. A computer-readable storage medium, wherein computer-executable instructions are stored in the computer-readable storage medium, and when executed by a processor, are configured to implement the calibration method according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211167533.XA CN115439633A (en) | 2022-09-23 | 2022-09-23 | Calibration method and device and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211167533.XA CN115439633A (en) | 2022-09-23 | 2022-09-23 | Calibration method and device and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115439633A true CN115439633A (en) | 2022-12-06 |
Family
ID=84248246
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211167533.XA Pending CN115439633A (en) | 2022-09-23 | 2022-09-23 | Calibration method and device and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115439633A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115984389A (en) * | 2023-03-17 | 2023-04-18 | 梅卡曼德（北京）机器人科技有限公司 | Calibration method, system calibration method, device and electronic equipment |
| CN116188594A (en) * | 2022-12-31 | 2023-05-30 | 梅卡曼德（北京）机器人科技有限公司 | Calibration method, calibration system, calibration device and electronic equipment of camera |
-
2022
- 2022-09-23 CN CN202211167533.XA patent/CN115439633A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116188594A (en) * | 2022-12-31 | 2023-05-30 | 梅卡曼德（北京）机器人科技有限公司 | Calibration method, calibration system, calibration device and electronic equipment of camera |
| CN116188594B (en) * | 2022-12-31 | 2023-11-03 | 梅卡曼德（北京）机器人科技有限公司 | Calibration method, calibration system, calibration device and electronic equipment of camera |
| CN115984389A (en) * | 2023-03-17 | 2023-04-18 | 梅卡曼德（北京）机器人科技有限公司 | Calibration method, system calibration method, device and electronic equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107738254B (en) | Conversion calibration method and system for mechanical arm coordinate system | |
| CN115439633A (en) | Calibration method and device and electronic equipment | |
| CN110640746B (en) | Method, system, equipment and medium for calibrating and positioning coordinate system of robot | |
| CN110640747B (en) | Hand-eye calibration method and system for robot, electronic equipment and storage medium | |
| JP2018169403A (en) | System and method for tying together machine vision coordinate spaces in guided assembly environment | |
| KR20200107789A (en) | Automatic calibration for a robot optical sensor | |
| CN102598896B (en) | Object control system, object control method and program, and rotational center position specification device | |
| CN112318506A (en) | Automatic calibration method, device, equipment, mechanical arm and medium for mechanical arm | |
| CN111590593B (en) | Calibration method, device and system of mechanical arm and storage medium | |
| CN112621743B (en) | Robot, hand-eye calibration method for fixing camera at tail end of robot and storage medium | |
| CN114211484B (en) | Front-end tool pose synchronization method, electronic equipment and storage medium | |
| CN109814434B (en) | Calibration method and device of control program | |
| CN109341718B (en) | Calibration method and device based on multi-view vision | |
| CN114310901B (en) | Coordinate system calibration method, device, system and medium for robot | |
| CN113841384A (en) | Calibration device, chart for calibration and calibration method | |
| CN114310880A (en) | Mechanical arm calibration method and device | |
| CN109597318B (en) | Robot space registration method and device | |
| CN112907683A (en) | Camera calibration method and device for dispensing platform and related equipment | |
| CN114139857A (en) | Workpiece finishing process correcting method, system, storage medium and device | |
| CN111604904B (en) | Robot positioning calibration method and device and electronic equipment | |
| CN107492124B (en) | Plane calibration device of fisheye camera | |
| CN116019562A (en) | Robot control system and method | |
| CN115488888A (en) | Object positioning method, control method and device of robot system and electronic equipment | |
| CN114939867A (en) | Calibration method and system for mechanical arm external irregular asymmetric tool based on stereoscopic vision | |
| CN109916352B (en) | Method and device for acquiring TCP (Transmission control protocol) coordinates of robot |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |