CN117226856A - Robot self-calibration method and system based on vision - Google Patents
Robot self-calibration method and system based on vision Download PDFInfo
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Abstract
The application relates to the technical field of robot control, and discloses a vision-based robot self-calibration method and a vision-based robot self-calibration system, wherein a tool center point containing a vision sensor is fixedly arranged at the tail end of a mechanical arm, at least three preset points containing a position detector at the top are arranged in the surrounding environment of the mechanical arm, and the method comprises the following steps: obtaining an initial DH parameter of the mechanical arm, calibrating a tool center point to obtain initial position data of the tool center point, calibrating the DH parameter of the mechanical arm according to the initial position data to obtain a calibrated DH parameter, calculating a tool center point error and an alignment error of the mechanical arm, judging whether the tool center point error is smaller than a tool center point error threshold value and whether the alignment error is smaller than an alignment error threshold value, if so, judging that the calibrated DH parameter is an optimal value, and if not, recalibrating the tool center point and the calibrated DH parameter. By adopting the method, the robot base coordinate system and the hand-eye coordinate system do not need to be calibrated, so that the parameter error identification is more accurate.
Description
Technical Field
The application relates to the technical field of robot control, in particular to a vision-based robot self-calibration method and system.
Background
With the rapid development of robot application technology, on-line programming in the form of manual teaching is difficult to meet complex work demands. In order to realize the off-line programming of the robot and realize high efficiency and accuracy, the absolute positioning accuracy of the robot is improved. Kinematic parameter errors are a major factor affecting the absolute positioning accuracy of robots. To improve the absolute positioning accuracy of the robot, kinematic calibration is imperative, and the kinematic calibration can be generally divided into four steps: the method comprises the steps of (1) establishing a robot mathematical model and an error model, (2) measuring the pose of the tail end of the robot, (3) identifying kinematic error parameters according to measured pose information, and (4) compensating errors. The existing robot kinematics calibration comprises an external calibration method and a self-calibration method. The external calibration (open loop calibration) often needs to use expensive external measurement equipment to measure the pose of the robot, such as a laser tracker, a three-coordinate measuring instrument and the like, has good calibration effect, but has expensive equipment, has requirements on the calibration environment and the site, and is difficult to popularize for the kinematic calibration in the industrial scene; the internal calibration (closed loop calibration) does not need external measuring equipment, and the pose error is solved by using necessary sensors based on equation sets of linear constraint and the like, such as a vision-based kinematic calibration method and the like. The existing vision-based kinematic self-calibration method needs to perform hand-eye transformation and transformation between a world coordinate system and a robot base coordinate system, so that the probability of error occurrence is increased, and the self-calibration process is complicated.
Disclosure of Invention
The embodiment of the application aims to provide a vision-based robot self-calibration method and a vision-based robot self-calibration system, which are used for enabling parameter error identification to be more accurate by adopting a vision calibration method based on fixed point constraint according to an established error model without calibrating a robot base coordinate system and a hand-eye coordinate system.
To solve the above technical problem, a first aspect of the embodiments of the present application provides a vision-based robot self-calibration method, a tool center point is fixedly provided at an end of a mechanical arm, a vision sensor is provided at the tool center point, at least three preset points are provided in a surrounding environment of the mechanical arm, and a position detector is provided at a top of the preset points, including the following steps:
acquiring an initial DH parameter of the mechanical arm;
calibrating a tool center point of the mechanical arm based on the initial DH parameter, adjusting the state of the mechanical arm for a plurality of times, and enabling the tool center point to be always aligned to a preset point position based on the vision sensor to obtain initial position data of the tool center point;
calibrating DH parameters of the mechanical arm according to the initial position data of the tool center point, and adjusting the state of the mechanical arm for a plurality of times to enable the tool center point to be aligned to the at least three preset points respectively, so as to obtain calibrated DH parameters;
calculating a tool center point error and an alignment error of the mechanical arm according to the calibration DH parameters;
and judging whether the tool center point error is smaller than a tool center point error threshold value or not and whether the alignment error is smaller than an alignment error threshold value or not, if so, judging that the DH parameter after the calibration is an optimal value, and if not, recalibrating the tool center point and calibrating the DH parameter.
Further, the calibrating the tool center point of the mechanical arm based on the initial DH parameter to obtain initial position data of the tool center point includes:
calculating a direction parameter and a position parameter of the tail end of the mechanical arm based on the initial DH parameter;
and calculating initial position data of the tool center point according to the direction parameters and the position parameters of the tail end of the mechanical arm.
Further, the direction data of the tail end of the mechanical armAnd position data->The calculation formula of (2) is as follows:
；
；
wherein,for the transformation matrix from the kth-1 joint to the kth joint of the manipulator, is #>For the conversion matrix of the manipulator base to joint 1, < >>，/>、/>、/>、/>、/>Is the initial DH parameter of the mechanical arm.
Further, the alignment error of the mechanical armThe calculation formula of (2) is as follows:
；
wherein,for the conversion matrix of the manipulator end coordinate system obtained by calibrating the DH parameters according to the j-th calibration pose in the process of calibrating the DH parameters of the manipulator corresponding to the manipulator base coordinate system, the following steps are taken>For the conversion matrix of the end coordinate system of the mechanical arm, which is obtained by calibrating according to the DH parameters, corresponding to the base coordinate system when the ith calibration pose is performed in the process of calibrating the DH parameters of the mechanical arm, the conversion matrix is->，/>For adjusting the DH parameters, the state of the mechanical arm is adjusted to align the tool center point with a preset point for a number of times,/for the calibration of DH parameters>And (5) initial position data for the tool center point.
Further, the initial position data of the tool center pointThe calculation formula of (2) is as follows:
；
wherein,and->And (3) aligning the tool center point with the preset point by adopting the ith pose in the process of calibrating the DH parameters, and carrying out direction data and position data of the tail end of the mechanical arm in the base coordinate system.
Further, according to the conversion matrix of the manipulator end coordinate system corresponding to the base coordinate system obtained by calibrating the DH parametersThe calculation formula of (2) is as follows:
；
；
；
；
wherein,、/>、/>、/>、/>representing DH parameter errors, said calibrated DH parameter being the sum of said initial DH parameter and said DH parameter errors,/o>、/>Respectively representing the position data error and the direction data error of the tail end of the mechanical arm,/for the position data error and the direction data error of the tail end of the mechanical arm>、/>、/>、/>、/>、/>、/>And->And (3) a matrix of 3 XN mechanical arm tail end partial derivatives and DH parameter errors, wherein the DH parameter errors are differences between the initial DH parameters and the calibration DH parameters.
Further, the tool center point error of the mechanical armThe method comprises the following steps:
；
wherein,the direction data of the tail end of the mechanical arm after the h time adjustment in the tool center point calibration process,for the direction data of the tail end of the mechanical arm after h+1th adjustment in the tool center point calibration process,/L->For the position data of the tail end of the mechanical arm after the kth adjustment in the tool center point calibration process, # is given>For the position data of the tail end of the mechanical arm after h+1th adjustment in the tool center point calibration process,/L->,/>The state of the mechanical arm is adjusted in the process of calibrating the tool center point so that the tool center point is aligned to the times of the preset point, and the number of times is +.>Initial position data for the tool center point.
Further, when calculating the tool center point error of the mechanical arm, the direction data of the tail end of the mechanical armAnd position data->The calculation formula of (2) is as follows:
。
correspondingly, a second aspect of the embodiment of the present application provides a vision-based robot self-calibration system, a tool center point is fixedly arranged at the tail end of a mechanical arm, a vision sensor is arranged at the tool center point, at least three preset points are arranged in the surrounding environment of the mechanical arm, and a position detector is arranged at the top of each preset point, and the system comprises:
the initial parameter acquisition module is used for acquiring initial DH parameters of the mechanical arm;
the tool center point calibration module is used for calibrating a tool center point of the mechanical arm based on the initial DH parameter, adjusting the state of the mechanical arm for a plurality of times, and enabling the tool center point to be always aligned to a preset point based on the vision sensor to obtain initial position data of the tool center point;
the DH parameter calibration module is used for calibrating DH parameters of the mechanical arm according to initial position data of the tool center point, and adjusting the state of the mechanical arm for a plurality of times, so that the tool center point is respectively aligned to the at least three preset points to obtain calibrated DH parameters;
the error calculation module is used for calculating a tool center point error and an alignment error of the mechanical arm according to the calibration DH parameter;
and the calibration judging module is used for judging whether the tool center point error is smaller than a tool center point error threshold value or not and whether the alignment error is smaller than an alignment error threshold value or not, if so, judging that the DH parameter after the calibration is an optimal value, and if not, recalibrating the tool center point and calibrating the DH parameter.
Accordingly, a third aspect of the embodiment of the present application provides an electronic device, including: at least one processor; and a memory coupled to the at least one processor; the memory stores instructions executable by the at least one processor to cause the at least one processor to perform any of the vision-based self-calibration methods described above.
Accordingly, a fourth aspect of embodiments of the present application provides a computer-readable storage medium having stored thereon computer instructions which, when executed by a processor, implement the vision-based robot self-calibration method described above.
The technical scheme provided by the embodiment of the application has the following beneficial technical effects:
1. by adopting a visual calibration method based on fixed point constraint, according to the established error model, a robot base coordinate system and a hand-eye coordinate system are not required to be calibrated, so that parameter error identification is more accurate.
2. The fixed point of fixed point constraint adopts a PSD sensor to realize automatic detection, and when the system detects that the TCP is aligned with the PSD center, an instruction is sent to the robot to enable the robot to change the gesture, realignment of the tail end TCP and the fixed point is realized, and therefore automatic calibration of the mechanical arm is realized.
3. According to the kinematic error model, a TCP error formula and a self-calibration error formula required by the self-calibration of the robot are deduced.
4. And selecting reasonable fixed point positions according to the structural characteristics of the robot, and selecting the fixed point positions to be in different areas and different heights so as to enable the whole movement space of the robot to be covered as much as possible in a standard range.
Drawings
FIG. 1 is a flow chart of a vision-based robot self-calibration method provided by an embodiment of the application;
fig. 2a is a front view of a vision-based robot self-calibration principle provided by an embodiment of the present application;
FIG. 2b is a top view of the vision-based robot self-calibration principle provided by an embodiment of the present application;
fig. 3 is a block diagram of a vision-based self-calibration system for a robot according to an embodiment of the present application.
Reference numerals:
1. the device comprises an initial parameter acquisition module, a tool center point calibration module, a DH parameter calibration module, an error calculation module, a calibration judgment module and a DH parameter calibration module.
Detailed Description
The objects, technical solutions and advantages of the present application will become more apparent by the following detailed description of the present application with reference to the accompanying drawings. It should be understood that the description is only illustrative and is not intended to limit the scope of the application. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the present application.
Referring to fig. 1 and 2, a first aspect of the present application provides a vision-based robot self-calibration method, wherein a tool center point (TCP, tool Center Point) is fixedly arranged at an end of a mechanical arm, a vision sensor is arranged at the tool center point, at least three preset points are arranged in a surrounding environment of the mechanical arm, and a position detector, such as a PSD, is arranged at the top of the preset points, and the method comprises the following steps:
step S100, obtaining initial DH parameters of the mechanical arm. The robot DH parameters are parameters describing the robot kinematics model, and are proposed by Denavit-Hartenberg.
And step S200, calibrating a tool center point of the mechanical arm based on the initial DH parameter, adjusting the state of the mechanical arm for a plurality of times, and enabling the tool center point to be always aligned to a preset point position based on the vision sensor to obtain initial position data of the tool center point.
And step S300, calibrating DH parameters of the mechanical arm according to initial position data of the tool center point, and adjusting the state of the mechanical arm for a plurality of times to enable the tool center point to be aligned with at least three preset points respectively, thereby obtaining the calibrated DH parameters.
Step S400, calculating tool center point errors and alignment errors of the mechanical arm according to the calibration DH parameters.
And S500, judging whether the tool center point error is smaller than a tool center point error threshold value and whether the alignment error is smaller than an alignment error threshold value, if so, judging that the calibrated DH parameter is an optimal value, and if not, recalibrating the tool center point and calibrating the DH parameter.
In the above technical scheme, the end of the mechanical arm is fixedly provided with the vision sensor, in the calibration process, the robot is controlled to align the TCP with the cross center of the cross sight of the corresponding preset point location target under different poses, and the cross center of the cross sight is arranged on the sensitive surface of the position detector PSD (Position Sensitive detector), namely, the TCP position of the robot is overlapped with the preset point location. When the line laser passes through the cross center position, the PSD sensor returns a signal, and the joint angle at the moment is saved to identify the motion parameter error. Due to the limited range of cameras, only a small portion of the robot can be tested at any given location of the calibration target. In order to cover more robot volume, calibration targets must be placed at different heights, different areas. Alternatively, at each preset position, the TCP on the control arm is aligned with the center of intersection in 10 different poses.
TCP refers to the intersection of the camera optical axis and the laser plane. When the laser sensor is fixed to the end of the arm, the TCP is a fixed point relative to the end of the arm. When the TCP calibration is carried out, the mechanical arm is controlled to enable the TCP to coincide with a preset point position (the center of the PSD sensor) in different positions. When the TCP at the tail end of the mechanical arm is aligned with the preset point, the coordinates of the preset point are fixed values, and the fixed values can be directly obtained. If the control arm is aligned in multiple states of different poses, the position of the TCP at the end of the arm is unchanged.
Specifically, in step S200, the calibration of the tool center point is performed on the mechanical arm based on the initial DH parameter, so as to obtain initial position data of the tool center point, and the method further includes the following steps:
step S210, calculating the direction parameter and the position parameter of the tail end of the mechanical arm based on the initial DH parameter.
Step S220, calculating initial position data of the tool center point according to the direction parameters and the position parameters of the tail end of the mechanical arm.
In particular, the method comprises the steps of,、/>、/>、/>、/>is the initial DH parameter of the mechanical arm. The direction parameter R and the position parameter T of the tail end of the mechanical arm can be calculated through the parameters. From the direction parameter R and the position parameter T of the end of the manipulator, the initial position data of the tool center point can be deduced based on the following formula.
Further, the direction parameter and the position parameter in step S210 may be calculated as follows. Direction data of mechanical arm tail endAnd position data->The calculation formula of (2) is as follows:
；
；
wherein,is the transformation matrix from the kth joint to the kth joint of the mechanical arm, and is +.>For the conversion matrix of the arm base to the 1 st joint,>，/>、/>、/>、/>、/>is the initial DH parameter of the mechanical arm.
Taking a six-axis serial mechanical arm as an example, the kinematic model represents the relation between the rotation angle of each joint and the pose of the tail end of the robot. For the case where two consecutive joint axes are parallel or nearly parallel,the alignment error of the axes is small, which results in the parameter +.>，/>And->Is very error-prone. To overcome this problem, inWill->While setting to zero, introduce ++>Wind->The shaft rotates slightly.
R and T are the direction and position of the end of the mechanical arm in the base coordinate system, respectively, as represented by the kinematic parameters. As is apparent from the homogeneous transformation matrix, errors in kinematic parameters can cause deviations in the pose of the tail end of the mechanical arm. If the mechanical arm has no accurate kinematic parameters, the absolute positioning accuracy of the mechanical arm is worry. Therefore, it is necessary to recognize the motion parameters and compensate the errors.
Further, alignment error of the mechanical armThe calculation formula of (2) is as follows:
；
wherein,in order to obtain a conversion matrix of a mechanical arm terminal coordinate system corresponding to a mechanical arm base coordinate system according to calibration DH parameters when the j-th calibration pose is performed in the process of calibrating DH parameters of the mechanical arm, the weight is>For the conversion matrix of the corresponding base coordinate system of the mechanical arm terminal coordinate system obtained by calibration according to the calibration DH parameters when the ith calibration pose in the calibration process of DH parameters of the mechanical arm, the following is>，/>For school ofAdjusting the state of the mechanical arm to align the tool center point with a predetermined point when the DH parameter is quasi-DH>Initial position data for the tool center point.
Further, initial position data of tool center pointThe calculation formula of (2) is as follows:
；
wherein,and->And (3) aligning the tool center point with a preset point by adopting the ith pose in order to calibrate DH parameters, and aligning the direction data and the position data of the tail end of the mechanical arm in a base coordinate system.
Further, according to the conversion matrix of the corresponding base coordinate system of the mechanical arm terminal coordinate system obtained by calibration DH parameter calibrationThe calculation formula of (2) is as follows:
；
；
；
；
wherein,、/>、/>、/>、/>indicating DH parameter error, calibrating DH parameter as sum of initial DH parameter and DH parameter error, +.>、/>Respectively representing position data error and direction data error of the end of the mechanical arm, < >>、/>、/>、/>、/>、/>、/>And->Matrix of DH parameter error of partial derivative of 3 XN mechanical arm endThe difference is the difference between the initial DH parameter and the calibrated DH parameter.
Further, tool center point error of the robotic armThe method comprises the following steps:
；
wherein,for the direction data of the end of the mechanical arm after the h time adjustment in the tool center point calibration process, < + >>For the direction data of the tail end of the mechanical arm after h+1th adjustment in the tool center point calibration process, +.>For the position data of the end of the mechanical arm after the kth adjustment in the tool center point calibration process, +.>For the position data of the tail end of the mechanical arm after h+1th adjustment in the tool center point calibration process, +.>,/>The method comprises the steps of adjusting the state of a mechanical arm in the process of calibrating a tool center point to enable the tool center point to be aligned with a preset point for times,/-DEG>Is the initial position data of the tool center point.
Further, when calculating the tool center point error of the mechanical arm, the direction data of the tail end of the mechanical armAnd position data/>The calculation formula of (2) is as follows:
。
when the TCP calibration is carried out, the direction data and the position data of the tail end of the mechanical arm obtained in the previous calculation process are needed to be used, and h represents the h-th mechanical arm pose adjustment aiming at the same preset point position in the TCP calibration process.
Correspondingly, referring to fig. 3, a second aspect of the embodiment of the present application provides a vision-based robot self-calibration system, a tool center point is fixedly arranged at the tail end of a mechanical arm, a vision sensor is arranged at the tool center point, at least three preset points are arranged in the surrounding environment of the mechanical arm, and a position detector is arranged at the top of each preset point, including:
an initial parameter obtaining module 1, configured to obtain an initial DH parameter of the mechanical arm;
the tool center point calibration module 2 is used for calibrating the tool center point of the mechanical arm based on the initial DH parameter, adjusting the state of the mechanical arm for a plurality of times, and enabling the tool center point to be always aligned to a preset point position based on the vision sensor to obtain initial position data of the tool center point;
the DH parameter calibration module 3 is used for calibrating DH parameters of the mechanical arm according to initial position data of the tool center point, and adjusting the state of the mechanical arm for a plurality of times to enable the tool center point to be aligned to at least three preset points respectively, so as to obtain calibrated DH parameters;
an error calculation module 4 for calculating a tool center point error and an alignment error of the mechanical arm according to the calibrated DH parameter;
and the calibration judging module 5 is used for judging whether the tool center point error is smaller than the tool center point error threshold value and whether the alignment error is smaller than the alignment error threshold value, if so, judging that the calibrated DH parameter is an optimal value, and if not, recalibrating the tool center point and calibrating the DH parameter.
Each module in the vision-based robot self-calibration system can be refined into a specific functional unit according to the steps in the vision-based robot self-calibration method, and corresponding specific steps are executed, and are not repeated here.
In addition, a third aspect of the embodiment of the present application further provides an electronic device, including: at least one processor; and a memory coupled to the at least one processor; the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the vision-based robot self-calibration method.
In addition, a fourth aspect of the embodiment of the present application further provides a computer readable storage medium, on which computer instructions are stored, which when executed by a processor, implement the vision-based robot self-calibration method described above.
The embodiment of the application aims to protect a vision-based robot self-calibration method and a vision-based robot self-calibration system, wherein a tool center point is fixedly arranged at the tail end of a mechanical arm, a vision sensor is arranged at the tool center point, at least three preset points are arranged in the surrounding environment of the mechanical arm, and a position detector is arranged at the top of each preset point, and the method comprises the following steps: the method comprises the steps of obtaining initial DH parameters of a mechanical arm, calibrating tool center points of the mechanical arm based on the initial DH parameters, adjusting the states of the mechanical arm for multiple times, enabling tool center points to be always aligned with a preset point based on a vision sensor to obtain initial position data of the tool center points, calibrating the DH parameters of the mechanical arm according to the initial position data of the tool center points, adjusting the states of the mechanical arm for multiple times to enable the tool center points to be aligned with at least three preset points respectively to obtain calibrated DH parameters, calculating tool center point errors and alignment errors of the mechanical arm according to the calibrated DH parameters, judging whether the tool center point errors are smaller than a tool center point error threshold value and whether the alignment errors are smaller than an alignment error threshold value, if yes, judging that the calibrated DH parameters are optimal values, and if not, recalibrating the tool center points and the calibrated DH parameters. The technical scheme has the following effects:
1. by adopting the visual calibration method based on fixed point constraint, according to the established error model, a robot base coordinate system and a hand-eye coordinate system are not required to be calibrated, the influence of errors of the base coordinate system calibration and the hand-eye calibration on kinematic errors is reduced, and parameter error identification is more accurate.
2. The fixed point of fixed point constraint adopts a PSD sensor to realize automatic detection, when the system detects that the TCP is aligned with the PSD center, an instruction is sent to the robot, so that the robot changes the gesture, realignment between the tail end TCP and the fixed point is realized, and therefore automatic calibration of the mechanical arm is realized, and the operation is simple and convenient.
3. According to the structural characteristics of the robot, reasonable fixed point positions are selected, the fixed point positions are selected to be located in different areas and at different heights, so that the whole movement space of the robot is covered as much as possible in a calibration range, only 3-4 fixed points are selected for calibration, a large site is not needed, and the popularization of the kinematic calibration in an industrial scene is facilitated.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a system for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present application and not for limiting the same, and although the present application has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the application without departing from the spirit and scope of the application, which is intended to be covered by the claims.
Claims (10)
1. The robot self-calibration method based on vision is characterized in that a tool center point is fixedly arranged at the tail end of a mechanical arm, a vision sensor is arranged at the tool center point, at least three preset point positions are arranged in the surrounding environment of the mechanical arm, and a position detector is arranged at the top of each preset point position, and the method comprises the following steps:
acquiring an initial DH parameter of the mechanical arm;
calibrating a tool center point of the mechanical arm based on the initial DH parameter, adjusting the state of the mechanical arm for a plurality of times, and enabling the tool center point to be always aligned to a preset point position based on the vision sensor to obtain initial position data of the tool center point;
calibrating DH parameters of the mechanical arm according to the initial position data of the tool center point, and adjusting the state of the mechanical arm for a plurality of times to enable the tool center point to be aligned to the at least three preset points respectively, so as to obtain calibrated DH parameters;
calculating a tool center point error and an alignment error of the mechanical arm according to the calibration DH parameters;
and judging whether the tool center point error is smaller than a tool center point error threshold value or not and whether the alignment error is smaller than an alignment error threshold value or not, if so, judging that the DH parameter after the calibration is an optimal value, and if not, recalibrating the tool center point and calibrating the DH parameter.
2. The vision-based robot self-calibration method according to claim 1, wherein the calibrating the tool center point of the mechanical arm based on the initial DH parameter to obtain initial position data of the tool center point comprises:
calculating a direction parameter and a position parameter of the tail end of the mechanical arm based on the initial DH parameter;
and calculating initial position data of the tool center point according to the direction parameters and the position parameters of the tail end of the mechanical arm.
3. The vision-based robotic self-calibration method of claim 2, wherein,
direction data of the tail end of the mechanical armAnd position data->The calculation formula of (2) is as follows:
；
；
wherein,for the transformation matrix from the kth-1 joint to the kth joint of the manipulator, is #>For the conversion matrix of the manipulator base to joint 1, < >>，/>、/>、/>、/>、/>Is the initial DH parameter of the mechanical arm.
4. The method for vision-based robotic self-calibration of claim 3,
alignment error of the mechanical armThe calculation formula of (2) is as follows:
；
wherein,in order to calibrate the DH parameter of the mechanical arm according to the DH parameter of the j-th calibration pose in the calibration process, the conversion matrix of the mechanical arm terminal coordinate system corresponding to the mechanical arm base coordinate system is obtained,for the conversion matrix of the end coordinate system of the mechanical arm, which is obtained by calibrating according to the DH parameters, corresponding to the base coordinate system when the ith calibration pose is performed in the process of calibrating the DH parameters of the mechanical arm, the conversion matrix is->，/>For adjusting the DH parameters, the state of the mechanical arm is adjusted to align the tool center point with a preset point for a number of times,/for the calibration of DH parameters>And (5) initial position data for the tool center point.
5. The vision-based robotic self-calibration method of claim 4, wherein,
initial position data of the tool center pointThe calculation formula of (2) is as follows:
；
wherein,and->And (3) aligning the tool center point with the preset point by adopting the ith pose in the process of calibrating the DH parameters, and carrying out direction data and position data of the tail end of the mechanical arm in the base coordinate system.
6. The vision-based robotic self-calibration method of claim 5, wherein,
the conversion matrix of the manipulator end coordinate system corresponding to the base coordinate system is calibrated according to the calibration DH parametersThe calculation formula of (2) is as follows:
；
；
；
；
wherein,、/>、/>、/>、/>representing DH parameter errors, said calibrated DH parameter being the sum of said initial DH parameter and said DH parameter errors,/o>、/>Respectively representing the position data error and the direction data error of the tail end of the mechanical arm,、/>、/>、/>、/>、/>、/>and->And (3) a matrix of 3 XN mechanical arm tail end partial derivatives and DH parameter errors, wherein the DH parameter errors are differences between the initial DH parameters and the calibration DH parameters.
7. The method for vision-based robotic self-calibration of claim 3,
tool center point error of the mechanical armThe method comprises the following steps:
；
wherein,for the direction data of the tail end of the mechanical arm after the h time adjustment in the tool center point calibration process, +.>For the direction data of the tail end of the mechanical arm after h+1th adjustment in the tool center point calibration process,/L->For the position data of the tail end of the mechanical arm after the kth adjustment in the tool center point calibration process, # is given>For the position data of the tail end of the mechanical arm after h+1th adjustment in the tool center point calibration process,/L->,/>The state of the mechanical arm is adjusted in the process of calibrating the tool center point so that the tool center point is aligned to the times of the preset point, and the number of times is +.>Initial position data for the tool center point.
8. The vision-based robotic self-calibration method of claim 7,
in a tool for calculating the mechanical armWhen the heart point is in error, the direction data of the tail end of the mechanical armAnd position data->The calculation formula of (2) is as follows:
。
9. the utility model provides a robot is from calibration system based on vision, its characterized in that, the arm end has set firmly the instrument central point, instrument central point department is equipped with vision sensor, be provided with at least three in the surrounding environment of arm and predetermine the position, predetermine the position top and be provided with the position detector, include:
the initial parameter acquisition module is used for acquiring initial DH parameters of the mechanical arm;
the tool center point calibration module is used for calibrating a tool center point of the mechanical arm based on the initial DH parameter, adjusting the state of the mechanical arm for a plurality of times, and enabling the tool center point to be always aligned to a preset point based on the vision sensor to obtain initial position data of the tool center point;
the DH parameter calibration module is used for calibrating DH parameters of the mechanical arm according to initial position data of the tool center point, and adjusting the state of the mechanical arm for a plurality of times, so that the tool center point is respectively aligned to the at least three preset points to obtain calibrated DH parameters;
the error calculation module is used for calculating a tool center point error and an alignment error of the mechanical arm according to the calibration DH parameter;
and the calibration judging module is used for judging whether the tool center point error is smaller than a tool center point error threshold value or not and whether the alignment error is smaller than an alignment error threshold value or not, if so, judging that the DH parameter after the calibration is an optimal value, and if not, recalibrating the tool center point and calibrating the DH parameter.
10. An electronic device, comprising: at least one processor; and a memory coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the vision-based robotic self-calibration method of any one of claims 1-8.
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