CN114521960B - Full-automatic real-time calibration method, device and system of abdominal cavity operation robot - Google Patents
Full-automatic real-time calibration method, device and system of abdominal cavity operation robot Download PDFInfo
- Publication number
- CN114521960B CN114521960B CN202210177629.8A CN202210177629A CN114521960B CN 114521960 B CN114521960 B CN 114521960B CN 202210177629 A CN202210177629 A CN 202210177629A CN 114521960 B CN114521960 B CN 114521960B
- Authority
- CN
- China
- Prior art keywords
- joint motion
- mechanical arm
- nominal
- variable
- motion variable
- 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.)
- Active
Links
Images
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/70—Manipulators specially adapted for use in surgery
- A61B34/77—Manipulators with motion or force scaling
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/30—Surgical robots
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B34/00—Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
- A61B34/30—Surgical robots
- A61B2034/302—Surgical robots specifically adapted for manipulations within body cavities, e.g. within abdominal or thoracic cavities
Abstract
The invention provides a full-automatic real-time calibration method, device and system of an abdominal cavity operation robot, and relates to the technical field of abdominal cavity operation robots. The invention relates to a full-automatic real-time calibration method of an abdominal cavity surgical robot, which comprises the following steps: establishing a rotation amount kinematics model of the mechanical arm; acquiring the terminal pose of the mechanical arm, and determining a nominal joint motion variable of the mechanical arm according to the terminal pose; controlling the mechanical arm to move according to the kinematic parameters to obtain an actual joint motion variable of the mechanical arm; and judging whether the precision of the joint motion variable meets a preset condition or not according to the nominal joint motion variable and the actual joint motion variable, and identifying the kinematic parameters by adopting a genetic algorithm to update the kinematic parameters when the precision of the joint motion variable does not meet the preset condition. According to the technical scheme, the kinematic parameters can be effectively identified, and the motion precision of the mechanical arm is further improved.
Description
Technical Field
The invention relates to the technical field of abdominal cavity surgical robots, in particular to a full-automatic real-time calibration method, a full-automatic real-time calibration device and a full-automatic real-time calibration system of an abdominal cavity surgical robot.
Background
With the development of the medical robot industry, the position of the endoscopic surgical robot is increased to the top row of the surgical robot. The operation mechanical arm is used as an important component of the endoscopic operation robot and has higher motion precision. However, due to the existence of assembly errors caused by manufacturing and assembling of the mechanical arm, flexible errors caused by flexible deformation of the arm rod and the joint, thermal deformation errors caused by temperature change of the mechanical arm operation environment and the like, a certain deviation can be generated between the actual value and the nominal value of the kinematic parameters of the mechanical arm, and if the mechanical arm is still controlled by the nominal kinematic parameters in actual application, the motion precision of the mechanical arm can be reduced.
Disclosure of Invention
The invention solves the problem of how to improve the motion precision of the mechanical arm through calibration.
In order to solve the above problems, the present invention provides a full-automatic real-time calibration method for an abdominal cavity surgical robot, comprising: establishing a rotation amount kinematics model of the mechanical arm; acquiring the terminal pose of the mechanical arm, and determining a nominal joint motion variable of the mechanical arm according to the terminal pose; controlling the mechanical arm to move according to the kinematic parameters to obtain an actual joint motion variable of the mechanical arm; and judging whether the precision of the joint motion variable meets a preset condition or not according to the nominal joint motion variable and the actual joint motion variable, and identifying the kinematic parameters by adopting a genetic algorithm to update the kinematic parameters when the precision of the joint motion variable does not meet the preset condition.
According to the full-automatic real-time calibration method of the abdominal cavity operation robot, the actual values of the kinematic parameters of the mechanical arm are obtained by utilizing the kinematic parameter calibration, the kinematic parameters can be effectively identified, the pose errors are greatly reduced, and the automatic real-time accurate control of the mechanical arm is realized; the genetic algorithm is adopted to complete the overall optimal solution which can be found by the kinematics calibration, the kinematics parameters can be accurately identified, the calibration precision is improved, and further the movement precision of the mechanical arm is improved.
Optionally, the establishing a rotational kinematic model of the mechanical arm includes: establishing a positive kinematics model of the mechanical arm according to a momentum model, the positive kinematics model comprising:
wherein, g (theta) represents the motion parameter of the mechanical arm joint as theta i The pose of the tail end of the time, g (0) represents the pose of the tail end corresponding to the zero position of the joint,
is expressed in relation to theta i Corresponding rotation of movement, i =1,21。
According to the full-automatic real-time calibration method of the abdominal cavity operation robot, the positive kinematics model of the mechanical arm is established according to the rotation model, so that the kinematics parameters can be effectively identified, the pose error is greatly reduced, and the automatic real-time accurate control of the mechanical arm is realized.
Optionally, the determining nominal articulation variables for the robotic arm from the end pose comprises: determining the nominal articulation variable according to a first formula, wherein the first formula comprises:
wherein, theta N Representing the nominal joint motion variable, f representing the inverse kinematics equation, and x representing the momentum kinematics parameter.
The full-automatic real-time calibration method of the abdominal cavity operation robot determines the nominal joint motion variable according to the first formula, so that the kinematic parameters can be effectively identified, the pose error is greatly reduced, and the automatic real-time accurate control of the mechanical arm is realized.
Optionally, the acquiring the end pose of the mechanical arm comprises: the pose of a polyhedral target is tracked in real time through a dynamic tracker, and when the mechanical arm moves and keeps a designated pose and the pose of the polyhedral target is not changed within preset time, the current pose is acquired, wherein the polyhedral target is installed at the tail end of the mechanical arm.
According to the full-automatic real-time calibration method of the abdominal cavity operation robot, the real-time tracking of the pose of the tail end of the mechanical arm is realized through the dynamic tracker, and further the automatic real-time accurate control of the mechanical arm can be realized.
Optionally, the determining, according to the nominal joint motion variable and the actual joint motion variable, whether the precision of the joint motion variable meets a preset condition includes: and substituting the nominal joint motion variable and the actual joint motion variable into the rotation kinematic model to obtain two groups of poses, and judging that the precision of the joint motion variable meets a preset condition when the position error of the two groups of poses is not more than 0.5mm and the posture error of the poses is not more than 1 degree.
According to the full-automatic real-time calibration method of the abdominal cavity operation robot, whether the precision of the joint motion variable meets the preset condition or not is judged according to the pose errors corresponding to the nominal joint motion variable and the actual joint motion variable, the precision verification is carried out again until the precision meets the requirement after the kinematic parameters are identified, the calibration progress of the mechanical arm is improved, and then the automatic real-time accurate control of the mechanical arm can be realized.
Optionally, the identifying the kinematic parameters using a genetic algorithm to update the kinematic parameters comprises: constructing an objective function according to the nominal joint motion variables and the actual joint motion variables, wherein the objective function is as follows:
wherein F (theta, x) represents an objective function, x represents a momentum kinematics parameter, and theta i R Representing said actual joint movement variable, theta i N Representing the nominal articulation variables.
The full-automatic real-time calibration method of the abdominal cavity operation robot takes the momentum kinematics parameter as the identification parameter, can describe the influence of all error sources and avoid singularity, improves the calibration progress of the mechanical arm, and further can realize automatic real-time accurate control of the mechanical arm.
Optionally, the identifying the kinematic parameters using a genetic algorithm to update the kinematic parameters further comprises: setting the rotation amount kinematic parameters as chromosomes, setting the target function as a fitness function, and setting the nominal kinematic parameters as initial values of the chromosomes.
The full-automatic real-time calibration method of the abdominal cavity operation robot, disclosed by the invention, adopts a genetic algorithm to complete kinematics calibration, can accurately identify kinematics parameters by a searchable global optimal solution, improves the calibration precision, and further can realize automatic real-time accurate control of the mechanical arm.
The invention also provides a full-automatic real-time calibration device of the abdominal cavity operation robot, which comprises: the modeling module is used for establishing a momentum kinematics model of the mechanical arm; the first motion variable module is used for acquiring the tail end pose of the mechanical arm and determining a nominal joint motion variable of the mechanical arm according to the tail end pose; the second motion variable module is used for controlling the mechanical arm to move according to the kinematic parameters and acquiring the actual joint motion variable of the mechanical arm; and the calibration module is used for judging whether the precision of the joint motion variable meets a preset condition or not according to the nominal joint motion variable and the actual joint motion variable, and when the precision of the joint motion variable does not meet the preset condition, identifying the kinematic parameters by adopting a genetic algorithm so as to update the kinematic parameters. Compared with the prior art, the full-automatic real-time calibration device of the abdominal cavity surgical robot and the full-automatic real-time calibration method of the abdominal cavity surgical robot have the same advantages, and are not repeated herein.
The invention also provides a full-automatic real-time calibration system of the abdominal cavity surgical robot, which comprises a computer readable storage medium and a processor, wherein the computer readable storage medium stores a computer program, and the computer program is read by the processor and runs to realize the full-automatic real-time calibration method of the abdominal cavity surgical robot. Compared with the prior art, the full-automatic real-time calibration system of the abdominal cavity surgical robot and the full-automatic real-time calibration method of the abdominal cavity surgical robot have the same advantages, and are not repeated herein.
The invention also provides a computer readable storage medium, which stores a computer program, and when the computer program is read and executed by a processor, the computer program realizes the full-automatic real-time calibration method of the robot for the upper abdominal cavity surgery. Compared with the prior art, the advantages of the computer readable storage medium and the full-automatic real-time calibration method of the abdominal cavity surgical robot are the same, and are not described again.
Drawings
Fig. 1 is a schematic diagram of a full-automatic real-time calibration method of an abdominal cavity surgical robot according to an embodiment of the present invention;
fig. 2 is an exemplary diagram of a full-automatic real-time calibration system of the laparoscopic surgery robot according to an embodiment of the present invention.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
As shown in fig. 1, an embodiment of the present invention provides a full-automatic real-time calibration method for an abdominal cavity surgical robot, including: establishing a rotation amount kinematics model of the mechanical arm; acquiring the terminal pose of the mechanical arm, and determining a nominal joint motion variable of the mechanical arm according to the terminal pose; controlling the mechanical arm to move according to the kinematic parameters to obtain an actual joint motion variable of the mechanical arm; and judging whether the precision of the joint motion variable meets a preset condition or not according to the nominal joint motion variable and the actual joint motion variable, and identifying the kinematic parameters by adopting a genetic algorithm to update the kinematic parameters when the precision of the joint motion variable does not meet the preset condition.
Specifically, in this embodiment, the full-automatic real-time calibration method for the laparoscopic surgery robot includes:
s1: establishing a rotation amount kinematics model of the mechanical arm;
s2: measuring the terminal pose matrix of the mechanical arm through a dynamic tracker, and then reversely solving a nominal joint motion variable theta N ；
S3: controlling the mechanical arm joint to move to a specified position according to the kinematic parameters, and outputting an actual joint motion variable theta R ；
S4: synthesis of N groups of theta N And theta R And verifying whether the precision of the joint motion variable meets the design requirement, if so, finishing the calibration, otherwise, performing the kinematics parameter calibration by adopting a genetic algorithm, feeding back the obtained compensation result to the kinematics parameter in the S3, and controlling the motion of the mechanical arm again.
In the embodiment, the calibration process from S1 to S4 can be completed without human intervention, and as shown in fig. 2, the dynamic tracker, the arm controller and the calibration software can communicate in real time, the dynamic tracker can transmit the target pose to the calibration software, the arm controller can transmit the actual joint motion variable to the calibration software, and the dynamic tracker and the arm controller can jointly judge the time for pose acquisition and arm motion start and stop. And the calibration software judges whether the pose precision of the abdominal cavity operation robot meets the design requirement according to the target pose and the actual joint motion variable, if not, the kinematics parameter identification is completed by using a genetic algorithm, and the identified kinematics parameter is transmitted to the manipulator controller to complete the update of the kinematics parameter in the manipulator controller. The kinematic error model has the advantages of completeness, continuity, non-redundancy and the like, and all model variables have definite physical meanings.
In the embodiment, the actual values of the kinematic parameters of the mechanical arm are obtained by using kinematic parameter calibration, so that the kinematic parameters can be effectively identified, the pose error is greatly reduced, and the automatic real-time accurate control of the mechanical arm is realized; the genetic algorithm is adopted to complete the searchable global optimal solution of the kinematics calibration, the kinematics parameters can be accurately identified, the calibration precision is improved, and the motion precision of the mechanical arm is further improved.
Optionally, the establishing a rotational kinematic model of the mechanical arm includes: establishing a positive kinematics model of the mechanical arm according to a momentum model, the positive kinematics model comprising:
wherein, g (theta) represents the motion parameter of the mechanical arm joint as theta i The pose of the tail end of the time, g (0) represents the pose of the tail end corresponding to the zero position of the joint,
is expressed in relation to theta i Corresponding motion spin.
Specifically, in the present embodiment, in step S1, based on the rotation amount model, a positive kinematic model of the robot arm is constructed:
g (theta) represents the motion parameter of the mechanical arm joint as theta i The pose of the tail end of the time, g (0) represents the pose of the tail end corresponding to the zero position of the joint,
is expressed in relation to theta i Corresponding motion vector, i =1, 2.
Obtained according to lie group lie algebraic formula
As follows (I is an identity matrix, device for selecting or keeping>
Antisymmetric matrix of ω):
wherein:
where v denotes a linear velocity in the ω direction, and ω and r denote a unit vector in the direction of the rotation axis of each joint and coordinates of any point thereon, respectively.
In the embodiment, the positive kinematics model of the mechanical arm is established according to the momentum model, so that the kinematics parameters can be effectively identified, the pose error is greatly reduced, and the automatic real-time accurate control of the mechanical arm is realized.
Optionally, the determining nominal articulation variables for the robotic arm from the end pose comprises: determining the nominal articulation variable according to a first formula, wherein the first formula comprises:
wherein, theta N Representing the nominal joint motion variable, f representing an inverse kinematics solution equation, and x representing a rotational kinematics parameter.
Specifically, in the present embodiment, to facilitate kinematic calibration, the nominal articulation variables:
wherein f represents an inverse kinematics equation and x represents a momentum kinematics parameter.
In the embodiment, the nominal joint motion variable is determined according to the first formula, so that the kinematic parameters can be effectively identified, the pose error is greatly reduced, and the automatic real-time accurate control of the mechanical arm is realized.
Optionally, the acquiring the end pose of the mechanical arm comprises: the pose of a polyhedral target is tracked in real time through a dynamic tracker, and when the mechanical arm moves and keeps a specified pose and the pose of the polyhedral target is not changed within preset time, the current pose is acquired, wherein the polyhedral target is installed at the tail end of the mechanical arm.
Specifically, in this embodiment, in steps S2 and S3, a polyhedral target is mounted at the end of a robot arm, and the target pose is tracked in real time by using a dynamic tracker. Planning N groups of actual joint motion variables theta in each joint motion range of the mechanical arm R When the mechanical arm moves and keeps a certain designated pose, the dynamic tracker detects that the pose of the target is not changed within 2 seconds, and then the target position is acquiredAnd after the pose acquisition of the target poses is finished, the mechanical arm continues to move to the next pose point, and the acquisition of the N groups of terminal poses is finished in a circulating manner. The N groups of terminal poses and the N groups of actual joint motion variables theta are compared R Inputting the data into calibration software, and reversely solving N sets of nominal joint motion variables theta according to N sets of end poses N 。
In this embodiment, the real-time tracking of the pose of the tail end of the mechanical arm is realized through the dynamic tracker, so that the automatic real-time accurate control of the mechanical arm can be realized.
Optionally, the determining, according to the nominal joint motion variable and the actual joint motion variable, whether the precision of the joint motion variable meets a preset condition includes: and substituting the nominal joint motion variable and the actual joint motion variable into the rotation kinematic model to obtain two groups of poses, and judging that the precision of the joint motion variable meets a preset condition when the position error of the two groups of poses is not more than 0.5mm and the posture error of the poses is not more than 1 degree.
Specifically, in this embodiment, the determining whether the accuracy of the joint motion variable satisfies the preset condition according to the nominal joint motion variable and the actual joint motion variable includes: according to N groups theta N And theta R Verifying whether the precision of the joint motion variable meets the design requirement, and if the precision requirement is met, calibrating is not needed, specifically: will theta N And theta R And simultaneously, substituting the two sets of poses into a theoretical kinematic model to obtain two sets of poses, and considering that the precision requirement is met when the position errors of the two sets of poses are not more than 0.5mm and the attitude errors are not more than 1 degree. If the precision requirement is not met, N groups of theta are utilized N And theta R And (5) identifying the kinematic parameters and bringing the identified kinematic parameters back to the step (S3). The kinematic parameters are used for controlling the mechanical arm to move to a random pose point, and theta of the mechanical arm at the moment is acquired and verified N′ And theta R′ Whether the accuracy requirement is met.
If the precision requirement is met, the calibration is finished, and if the precision requirement is not met, the group of theta is calibrated N′ 、θ R′ And N groups theta N 、θ R Merging (i.e. data theta) N′ 、θ R′ And data theta N 、θ R Combined in superposition into a new set of data, e.g. theta N 、θ R Forming a matrix of 2M rows and N columns (M represents the number of mechanical arm joints, namely the number of theta, and N represents the number of planned test pose groups), and dividing theta into theta N′ 、θ R′ And N groups theta N 、θ R After merging, the matrix of 2 × m columns and N rows will become a matrix of 2 × m columns and N +1 rows). Using N +1 groups theta N And theta R And (5) identifying the kinematic parameters, bringing the identified kinematic parameters back to the step (S3), and carrying out precision verification again. Repeating the steps until the precision meets the requirement.
In the embodiment, whether the precision of the joint motion variable meets the preset condition is judged according to the pose errors corresponding to the nominal joint motion variable and the actual joint motion variable, the kinematic parameters are identified, and then the precision is verified again until the precision meets the requirement, so that the calibration progress of the mechanical arm is improved, and the automatic real-time precise control of the mechanical arm can be realized.
Optionally, the identifying the kinematic parameters using a genetic algorithm to update the kinematic parameters comprises: constructing an objective function according to the nominal joint motion variable and the actual joint motion variable, wherein the objective function is as follows:
wherein F (theta, x) represents an objective function, x represents a momentum kinematics parameter, theta i R Representing said actual articulation variable, theta i N Representing the nominal articulation variable.
Specifically, in the present embodiment, in step S4, an objective function is constructed using the sum of squared residuals:
wherein F (theta, x) represents an objective function, x represents a momentum kinematics parameter, and theta i R Representing the actual joint movement variable, theta i N Representing a nominal articulation variable. The method has the advantages that the influence of all error sources can be described by taking the momentum kinematics parameters as the identification parameters, and meanwhile, singularity can be avoided.
The calibration objective function provided by the joint motion variable is utilized, the traditional method that only the position can be used for calibration is broken through, the position and the attitude achieve a high calibration effect at the same time, the problems of matrix ill-condition and attitude singularity identification are effectively solved, the error source identification precision and the stability of the identification result are improved, and the compensation precision is further improved.
In this embodiment, the momentum kinematics parameters are used as identification parameters, so that the influence of all error sources can be described, the singularity can be avoided, the calibration progress of the mechanical arm is improved, and the automatic real-time accurate control of the mechanical arm can be realized.
Optionally, the identifying the kinematic parameters using a genetic algorithm to update the kinematic parameters further comprises: setting the rotation amount kinematic parameters as chromosomes, setting the target function as a fitness function, and setting the nominal kinematic parameters as initial values of the chromosomes.
Specifically, in the present embodiment, the parameter identification of kinematics is completed based on a genetic algorithm, where x is set as a chromosome, and F (θ, x) is set as a fitness function, where a chromosome initial value is a nominal kinematics parameter. Parameters such as initial population scale, mating probability, variation probability, optimal individual coefficient, maximum evolutionary algebra and the like are set according to actual conditions.
In the embodiment, the kinematics calibration is completed by adopting a genetic algorithm, a searchable global optimal solution can accurately identify kinematics parameters, the calibration precision is improved, and then the automatic real-time accurate control of the mechanical arm can be realized.
Another embodiment of the present invention provides a full-automatic real-time calibration device for an abdominal surgery robot, comprising: the modeling module is used for establishing a rotation amount kinematics model of the mechanical arm; the first motion variable module is used for acquiring the tail end pose of the mechanical arm and determining a nominal joint motion variable of the mechanical arm according to the tail end pose; the second motion variable module is used for controlling the mechanical arm to move according to the kinematic parameters and acquiring the actual joint motion variable of the mechanical arm; and the calibration module is used for judging whether the precision of the joint motion variable meets a preset condition or not according to the nominal joint motion variable and the actual joint motion variable, and when the precision of the joint motion variable does not meet the preset condition, identifying the kinematic parameters by adopting a genetic algorithm so as to update the kinematic parameters.
Another embodiment of the present invention provides a full-automatic real-time calibration system for an abdominal cavity surgical robot, which includes a computer readable storage medium storing a computer program and a processor, wherein the computer program is read by the processor and executed to implement the above full-automatic real-time calibration method for an abdominal cavity surgical robot.
Another embodiment of the present invention provides a computer-readable storage medium, which stores a computer program, and when the computer program is read and executed by a processor, the computer program implements a full-automatic real-time calibration method for a robot for abdominal cavity surgery.
Although the present disclosure has been described above, the scope of the present disclosure is not limited thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present disclosure, and these changes and modifications are intended to be within the scope of the present disclosure.
Claims (8)
1. A full-automatic real-time calibration method of an abdominal cavity surgical robot is characterized by comprising the following steps:
establishing a rotation amount kinematics model of the mechanical arm, which specifically comprises the following steps: establishing a positive kinematics model of the mechanical arm according to a momentum model, the positive kinematics model comprising:
wherein, g (theta) represents the motion parameter of the mechanical arm joint as theta i End position of time, g (0) represents offThe tail end pose corresponding to the zero position is adjusted,
is expressed in relation to theta i Corresponding rotational amount of movement, i =1, 2.., 11;
acquiring the terminal pose of the mechanical arm, and determining a nominal joint motion variable of the mechanical arm according to the terminal pose;
controlling the mechanical arm to move according to the kinematic parameters to obtain an actual joint motion variable of the mechanical arm;
judging whether the precision of the joint motion variable meets a preset condition according to the nominal joint motion variable and the actual joint motion variable, which specifically comprises the following steps: verifying whether the precision of the joint motion variable meets the design requirement or not according to the N groups of nominal joint motion variables and the actual joint motion variable, if so, not needing to be calibrated, and when the precision of the joint motion variable does not meet the preset condition, identifying the kinematic parameters by adopting a genetic algorithm so as to update the kinematic parameters, wherein the method specifically comprises the following steps: when the precision requirement is not met, performing kinematic parameter identification by using N sets of nominal joint motion variables and actual joint motion variables, determining a current nominal joint motion variable and a current actual joint motion variable according to the identified kinematic parameters, merging the current nominal joint motion variable and the current actual joint motion variable with the N sets of nominal joint motion variables and the actual joint motion variables if the current nominal joint motion variable and the current actual joint motion variable do not meet the precision requirement, performing kinematic parameter identification by using the N +1 sets of nominal joint motion variables and the actual joint motion variables, and performing precision verification again, and repeating the steps until the precision meets the precision requirement;
wherein an objective function corresponding to the precision of the joint motion variables is constructed by the nominal joint motion variables and the actual joint motion variables, and the objective function is as follows:
wherein F (theta, x) represents the objective function, x represents a momentum kinematics parameter, theta i R Representing said actual articulation variable, theta i N Representing the nominal articulation variables.
2. The fully-automatic real-time calibration method of the laparoscopic surgical robot of claim 1, wherein said determining nominal joint motion variables of the mechanical arm according to the end pose comprises: determining the nominal articulation variable according to a first formula, wherein the first formula comprises:
θ N ＝f(g(θ)，X)
wherein, theta N Representing the nominal joint motion variable, f representing the inverse kinematics equation, and x representing the momentum kinematics parameter.
3. The fully-automatic real-time calibration method of the laparoscopic surgical robot of claim 1, wherein said acquiring the end pose of the mechanical arm comprises: the pose of a polyhedral target is tracked in real time through a dynamic tracker, and when the mechanical arm moves and keeps a designated pose and the pose of the polyhedral target is not changed within preset time, the current pose is acquired, wherein the polyhedral target is installed at the tail end of the mechanical arm.
4. The fully-automatic real-time calibration method of the laparoscopic surgery robot of claim 1, wherein the determining whether the precision of the joint motion variables meets preset conditions according to the nominal joint motion variables and the actual joint motion variables comprises: and substituting the nominal joint motion variable and the actual joint motion variable into the rotation kinematic model to obtain two groups of poses, and judging that the precision of the joint motion variable meets a preset condition when the position error of the two groups of poses is not more than 0.5mm and the posture error of the poses is not more than 1 degree.
5. The fully automatic real-time calibration method of the laparoscopic surgical robot of claim 1, wherein said identifying the kinematic parameters to update the kinematic parameters using a genetic algorithm further comprises: and setting the momentum kinematics parameters as chromosomes, setting the objective function as a fitness function, and setting the nominal kinematics parameters as initial values of the chromosomes.
6. The utility model provides a full-automatic real-time calibration device of abdominal cavity surgical robot which characterized in that includes:
the modeling module is used for establishing a rotation kinematics model of the mechanical arm, and specifically comprises: establishing a positive kinematics model of the mechanical arm according to a momentum model, the positive kinematics model comprising:
wherein, g (theta) represents the motion parameter of the mechanical arm joint as theta i The pose of the tail end of the time, g (0) represents the pose of the tail end corresponding to the zero position of the joint,
is expressed in relation to theta i Corresponding rotational amount of movement, i =1, 2.., 11;
the first motion variable module is used for acquiring the tail end pose of the mechanical arm and determining a nominal joint motion variable of the mechanical arm according to the tail end pose;
the second motion variable module is used for controlling the mechanical arm to move according to the kinematic parameters and acquiring the actual joint motion variable of the mechanical arm;
the calibration module is used for judging whether the precision of the joint motion variable meets a preset condition according to the nominal joint motion variable and the actual joint motion variable, and specifically comprises the following steps: verifying whether the precision of the joint motion variable meets the design requirement or not according to the N groups of nominal joint motion variables and the actual joint motion variable, if so, not needing to be calibrated, and when the precision of the joint motion variable does not meet the preset condition, identifying the kinematic parameters by adopting a genetic algorithm so as to update the kinematic parameters, wherein the method specifically comprises the following steps: when the precision requirement is not met, performing kinematic parameter identification by using N sets of nominal joint motion variables and actual joint motion variables, determining a current nominal joint motion variable and a current actual joint motion variable according to the identified kinematic parameters, merging the current nominal joint motion variable and the current actual joint motion variable with the N sets of nominal joint motion variables and the actual joint motion variables if the current nominal joint motion variable and the current actual joint motion variable do not meet the precision requirement, performing kinematic parameter identification by using the N +1 sets of nominal joint motion variables and the actual joint motion variables, and performing precision verification again, and repeating the steps until the precision meets the requirement;
wherein an objective function corresponding to the precision of the joint motion variables is constructed by the nominal joint motion variables and the actual joint motion variables, and the objective function is as follows:
wherein F (theta, x) represents the objective function, x represents a momentum kinematics parameter, theta i R Representing said actual articulation variable, theta i N Representing the nominal articulation variable.
7. A full-automatic real-time calibration system of a laparoscopic surgery robot, comprising a computer readable storage medium storing a computer program and a processor, wherein the computer program is read and executed by the processor to implement the full-automatic real-time calibration method of the laparoscopic surgery robot as claimed in any one of claims 1 to 5.
8. A computer-readable storage medium, characterized in that it stores a computer program which, when read and executed by a processor, implements a fully automatic real-time calibration method of a laparoscopic surgical robot according to any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210177629.8A CN114521960B (en) | 2022-02-25 | 2022-02-25 | Full-automatic real-time calibration method, device and system of abdominal cavity operation robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210177629.8A CN114521960B (en) | 2022-02-25 | 2022-02-25 | Full-automatic real-time calibration method, device and system of abdominal cavity operation robot |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114521960A CN114521960A (en) | 2022-05-24 |
| CN114521960B true CN114521960B (en) | 2023-04-07 |
Family
ID=81624883
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210177629.8A Active CN114521960B (en) | 2022-02-25 | 2022-02-25 | Full-automatic real-time calibration method, device and system of abdominal cavity operation robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114521960B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4698572A (en) * | 1986-04-04 | 1987-10-06 | Westinghouse Electric Corp. | Kinematic parameter identification for robotic manipulators |
| WO2018205707A1 (en) * | 2017-05-09 | 2018-11-15 | 中国科学院计算技术研究所 | Inverse kinematics solution system for use with robot |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102022989B (en) * | 2010-09-29 | 2012-03-21 | 山东科技大学 | Robot calibration method based on exponent product model |
| CN107053176B (en) * | 2017-04-09 | 2019-07-12 | 北京工业大学 | A kind of error modeling method of six-DOF robot end spaces curvilinear path |
| CN108908335B (en) * | 2018-07-20 | 2023-03-14 | 合肥工业大学 | Robot calibration method based on improved differential evolution algorithm |
| JP6823024B2 (en) * | 2018-09-11 | 2021-01-27 | ファナック株式会社 | Robot calibration system and calibration method |
| CN110757450B (en) * | 2019-09-06 | 2022-05-17 | 南京邮电大学 | Shoulder joint rehabilitation robot parameter calibration method |
-
2022
- 2022-02-25 CN CN202210177629.8A patent/CN114521960B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4698572A (en) * | 1986-04-04 | 1987-10-06 | Westinghouse Electric Corp. | Kinematic parameter identification for robotic manipulators |
| WO2018205707A1 (en) * | 2017-05-09 | 2018-11-15 | 中国科学院计算技术研究所 | Inverse kinematics solution system for use with robot |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114521960A (en) | 2022-05-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zhao et al. | System identification of the nonlinear residual errors of an industrial robot using massive measurements | |
| CN110434851B (en) | 5-degree-of-freedom mechanical arm inverse kinematics solving method | |
| KR102050895B1 (en) | Calibration and programming of robots | |
| WO2020237407A1 (en) | Method and system for self-calibrating robot kinematic parameter, and storage device | |
| CN113386136B (en) | Robot posture correction method and system based on standard spherical array target estimation | |
| CN109176531A (en) | A kind of tandem type robot kinematics calibration method and system | |
| CN112605996B (en) | Model-free collision avoidance control method for redundant mechanical arm | |
| CN111452048B (en) | Calibration method and device for relative spatial position relation of multiple robots | |
| CN107053216A (en) | The automatic calibration method and system of robot and end effector | |
| CN112536797A (en) | Comprehensive compensation method for position and attitude errors of industrial robot | |
| CN112318498A (en) | Industrial robot calibration method considering parameter coupling | |
| WO2024031922A1 (en) | Robot calibration method and device based on equivalent kinematic model | |
| CN113927599A (en) | Absolute precision compensation method, system, device and computer readable storage medium | |
| CN111195915B (en) | Mechanical arm absolute positioning precision calibration method and system based on genetic algorithm | |
| CN114521960B (en) | Full-automatic real-time calibration method, device and system of abdominal cavity operation robot | |
| Tian et al. | A general approach for robot pose error compensation based on an equivalent joint motion error model | |
| KR102269776B1 (en) | Calibration Method of Robot for Interventional treatment | |
| CN110900608B (en) | Robot kinematics calibration method based on optimal measurement configuration selection | |
| JP2003191186A (en) | Method of correcting robot teaching data | |
| CN113211436B (en) | Six-degree-of-freedom series robot error calibration method based on genetic algorithm | |
| CN112847362B (en) | Transfer robot vision servo control method based on image moment | |
| Stölzle et al. | Modelling handed shearing auxetics: Selective piecewise constant strain kinematics and dynamic simulation | |
| CN112847441B (en) | Six-axis robot coordinate offset detection method and device based on gradient descent method | |
| CN116551677A (en) | Joint robot calibration method, computer device, and readable storage medium | |
| CN113246121B (en) | Concentric tube robot control method based on Actor-Critic deep reinforcement learning |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |