CN118046421A - Automatic acquisition method and system for actual moment of joint of surgical robot - Google Patents
Automatic acquisition method and system for actual moment of joint of surgical robot Download PDFInfo
- Publication number
- CN118046421A CN118046421A CN202410453128.7A CN202410453128A CN118046421A CN 118046421 A CN118046421 A CN 118046421A CN 202410453128 A CN202410453128 A CN 202410453128A CN 118046421 A CN118046421 A CN 118046421A
- Authority
- CN
- China
- Prior art keywords
- moment
- motor
- surgical robot
- stroke
- sectional
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 238000012360 testing method Methods 0.000 claims abstract description 51
- 238000004364 calculation method Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 12
- 230000035772 mutation Effects 0.000 claims description 9
- 238000005070 sampling Methods 0.000 claims description 8
- 230000001502 supplementing effect Effects 0.000 claims description 6
- 238000009499 grossing Methods 0.000 description 11
- 230000002159 abnormal effect Effects 0.000 description 6
- 230000000087 stabilizing effect Effects 0.000 description 6
- 238000004070 electrodeposition Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000001914 filtration Methods 0.000 description 3
- 238000006073 displacement reaction Methods 0.000 description 2
- 230000005484 gravity Effects 0.000 description 2
- 238000000691 measurement method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000002411 adverse Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013480 data collection Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/0095—Means or methods for testing manipulators
-
- 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
-
- 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
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01L—MEASURING FORCE, STRESS, TORQUE, WORK, MECHANICAL POWER, MECHANICAL EFFICIENCY, OR FLUID PRESSURE
- G01L5/00—Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes
- G01L5/0028—Force sensors associated with force applying means
- G01L5/0042—Force sensors associated with force applying means applying a torque
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Surgery (AREA)
- Robotics (AREA)
- Animal Behavior & Ethology (AREA)
- Public Health (AREA)
- Heart & Thoracic Surgery (AREA)
- Medical Informatics (AREA)
- Molecular Biology (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- General Health & Medical Sciences (AREA)
- Biomedical Technology (AREA)
- Veterinary Medicine (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mechanical Engineering (AREA)
- Manipulator (AREA)
Abstract
The invention discloses an automatic acquisition method and system of actual moment of a joint of a surgical robot, comprising the following steps: and acquiring a positive limit position and a negative limit position of a motion stroke of the surgical robot joint and a test stroke of a corresponding motor, measuring a stable moment and a critical moment by switching motor modes, and correcting and fitting to obtain an actual output moment of the surgical robot joint to be tested. The invention obtains the relation between the joint position and the motor torque by testing the stable torque data of each sectional stroke of the surgical robot joint in the whole test stroke, and can eliminate various errors caused by theory and actual existence, improve the accuracy of data acquisition and be applicable to products of different types compared with the mode of calculating the torque/current required by the motor at each position of the joint in the prior art.
Description
Technical Field
The invention relates to the technical field of medical instruments, in particular to a surgical robot, and especially relates to an automatic acquisition method and system of joint actual moment of the surgical robot.
Background
Surgical robotic systems typically include a surgical robot or movable arm containing a plurality of links coupled together by one or more joints that are actively controlled by motors to manipulate an instrument. The connecting rod connected with the joint can be driven to move by changing the rotation position of the joint, and the surgical instrument can move in multiple degrees of freedom through the cooperation of multiple joints. Therefore, the correlation between the joint position and the motor moment needs to be obtained in advance, so that accurate control on each joint is facilitated.
In practice, each joint often needs to overcome the effects of gravity or other drag forces and friction forces. In order to improve the operation experience, a user can operate the joints to move with very small force, and the moment/current value required by the motor to overcome the resistance can be obtained by acquiring the corresponding resistance value of each joint at each position. For example, when acquiring the joint torque data of the mechanical arm (joint torque, which refers to the vector sum of all the torques generated between the connecting rods), three modes of motor current estimation, joint torsion amplitude estimation and strain gauge measurement are adopted. The method comprises the steps of adopting a mode of estimating motor current and joint torsion amplitude to compensate driving friction force by selecting a proper friction force model, calculating moment/current required by a motor for overcoming the friction force at each position of a joint, wherein in the actual application process, various errors exist between theory and actual, such as joint size, part weight and the like, so that data obtained by calculation of robot dynamics cannot completely coincide with the actual, and a final effect is poor; the method of directly measuring by using the strain gauge does not need to compensate the friction force any more, but the operation efficiency is low, the time consumption is relatively high, the data quantity obtained by the measurement method is discrete, the whole test stroke cannot be covered, and in practical application, the areas in all the test strokes may not be consistent, so that due to the limitation of the measurement method, the data of the abrupt change area is difficult to collect, or the data collection amount of the abrupt change area is small, and the practical situation cannot be simulated well according to the curve fitted by the data.
In addition, in an ideal state, the joint motor of the surgical robot also needs to add 'power assistance' according to the control direction of the user, namely, extra thrust is added in the control direction of the user, so that the active thrust is reduced by the user, and better experience is obtained. In order to achieve the aim, the critical moment of the motor of each joint of the surgical robot in the balanced state needs to be collected, when the critical moment is located, the stability of the joint position can be ensured, the assistance can be provided for a user in the control direction, and the user can realize the operation when applying extremely small thrust to the joint. However, no corresponding torque acquisition method is provided in the prior art.
Disclosure of Invention
The invention aims to overcome the defects in the prior art and provides an automatic acquisition method and system for the actual moment of a joint of a surgical robot.
The aim of the invention is achieved by the following technical scheme:
an automatic acquisition method of actual moment of a joint of a surgical robot comprises the following steps:
Step S1: acquiring a positive limit position and a negative limit position of a movement stroke of a surgical robot joint, recording a motor stroke for controlling the surgical robot joint to move between the positive limit position and the negative limit position as a test stroke, and equally dividing the test stroke into a group of sectional strokes; when the motor is respectively positioned at the starting position or the ending position of the test stroke, the surgical robot joint correspondingly moves to the positive limit position or the negative limit position respectively;
Step S2: the motor is controlled to be switched to be in a CSP mode, the sectional strokes are sequentially operated from the initial position, whether the surgical robot joint is in a stable state or not is judged in real time, the current moment of the motor in the stable state of the surgical robot joint is collected and recorded as the stable moment operated in the sectional strokes, and the stable moment of the motor on all the sectional strokes in the whole test stroke is obtained after the final position of the test stroke is reached;
Step S3: the motor is controlled to be switched to be in a CST mode, the motor is repeatedly controlled to run the sectional strokes from the initial position, the initial moment of the motor is set to be the stable moment of the current sectional stroke measured in the step S2 before each sectional stroke runs, the unit moment is continuously increased on the basis of the stable moment according to the running direction of the motor on the test stroke until the joint position changes, and the difference value between the current moment of the motor and the unit moment is recorded as a critical moment;
step S4: and (3) fitting the critical moment after the step (S3), and simultaneously correcting the abrupt change data to obtain the processed output moment data.
Preferably, in the step S2 and the step S3, before each segment stroke is operated, the motor first determines whether the motor reaches the end position of the test stroke, and if not, the motor is controlled to operate the current segment stroke.
Preferably, in step S2, the motor is controlled to sequentially run the sectional travel from the end position to reversely drive the surgical robot joint, whether the surgical robot joint is in a stable state is judged in real time, a current moment of the motor in the stable state of the surgical robot joint is collected and recorded as a reverse stable moment running in the sectional travel, and the reverse stable moment and the forward stable moment recorded before are summed and averaged to form a corrected stable moment.
Preferably, in step S2, after each of the sectional strokes is finished, the motor is controlled to form a stop state so as to reduce an error in determining whether the surgical robot joint is in a stable state.
Preferably, in the step S2, the running speed of the motor is monitored in real time in the motor stop state, when the running speed is less than the stop speed threshold v, stopping, performing the next segment of the segment stroke,
The calculation formula of the pause speed threshold v is as follows:
v= acc*rec*2bit/360/t；
wherein: acc: system accuracy;
rec: a motor reduction ratio;
bit: encoder bits;
t: the run-length sampling time is segmented.
Preferably, a process of correcting mutation data is also included between the step S2 and the step S3.
Preferably, in the step S3, the unit torque that is continuously increased is a minimum unit torque that can be operated by the motor.
Preferably, in the step S3, the method further includes a critical moment supplementing process, wherein the critical moment supplementing process includes that the motor is controlled to record critical moment supplementing data after increasing x pulses each time on the basis of the critical moment, and a calculation formula of the number x of pulses added each time is as follows:
1≤x≤acc*rec*2bit/360；
Wherein: acc: the system precision is the self-contained data of the system;
rec: a motor reduction ratio;
bit: encoder bits.
The invention also discloses an automatic acquisition system of the actual moment of the joint of the surgical robot, which comprises:
The motor stroke acquisition unit is used for acquiring a positive limit position and a negative limit position of a movement stroke of the surgical robot joint, recording the motor stroke for controlling the surgical robot joint to move between the positive limit position and the negative limit position as a test stroke, and equally dividing the test stroke into a group of sectional strokes; when the motor is respectively positioned at the starting position or the ending position of the test stroke, the surgical robot joint correspondingly moves to the positive limit position or the negative limit position respectively;
The stable moment acquisition unit is used for controlling the motor to be switched to be in a CSP mode, sequentially running the sectional strokes from the initial position, judging whether the surgical robot joint is in a stable state in real time, acquiring the current moment of the motor in the stable state of the surgical robot joint, recording the current moment as the stable moment running in the sectional strokes, and acquiring the stable moment of the motor on all the sectional strokes in the whole test stroke after reaching the end position of the test stroke;
the critical moment acquisition unit is used for controlling the motor to be switched to be in a CST mode, repeatedly controlling the motor to sequentially run the sectional strokes from the initial position, setting the initial moment of the motor as the stable moment of the current sectional stroke measured in the step S2 before each sectional stroke runs, continuously increasing the unit moment on the basis of the stable moment according to the running direction of the motor on the test stroke until the joint position changes, and recording the difference value between the current moment of the motor and the unit moment as the critical moment;
And the moment data processing unit is used for fitting the critical moment after the step S3 and correcting the abrupt change data at the same time to obtain the processed output moment data.
The invention also discloses a surgical robot, which comprises a surgical robot joint and a motor for controlling the movement of the surgical robot joint, wherein the controller of the motor is preset with output torque data obtained by the automatic acquisition method of the actual torque of the surgical robot joint so as to control the motor to output the torque at the current position in the corresponding running direction.
The beneficial effects of the invention are mainly as follows:
1. By testing the stable moment data of each sectional travel of the surgical robot joint in the whole test travel, all actual moment data of the joint in the whole travel range, namely the moment of the gravity overcome by the corresponding position of the motor, can be automatically acquired, the problem that the theory and the reality do not accord with each other through the calculation of the dynamics of the robot is avoided, meanwhile, a more fitting actual curve can be fitted according to the actual condition of parts, the accuracy of data acquisition is improved, and the method is applicable to products of different types;
2. The data of the surgical robot joint in two running directions can be collected at the same time, and a curve with higher accuracy can be obtained; the running distance of each sectional travel, the pause stabilizing time after each acquisition, the number of the acquired sectional travel in each running direction and the like can be selected in a calibration range according to actual requirements, so that the flexibility of the acquisition work is further improved;
3. On the basis of the stable moment, continuously increasing a unit moment according to the running direction of the motor on a test stroke and monitoring the joint position in real time to obtain the critical moment of each sectional stroke, and on the premise of ensuring the stability of operation, adding additional thrust in the control direction of an operator so as to save the thrust of the user and obtain better experience;
4. the motor is controlled to record the supplementary data of the critical moment after increasing x pulses each time on the basis of the critical moment, so that the integrity and the accuracy of data acquisition are ensured;
5. Aiming at abnormal data, abrupt change data and abrupt change areas, different processing modes are adopted, so that the data accords with actual results as far as possible, meanwhile, when a curve is fitted, a polynomial is adopted to fit the curve, and the curve is used as a formula for finally calculating real-time moment, so that the accuracy of data acquisition is further improved.
Drawings
The technical scheme of the invention is further described below with reference to the accompanying drawings:
fig. 1: the flow diagram of the invention;
fig. 2: the invention processes the schematic diagram when the abnormal data exists;
fig. 3: the invention processes the schematic diagram when the mutation data exists and the processed curve;
fig. 4: schematic representation of the treatment of the invention in the presence of mutated regions.
Detailed Description
The present invention will be described in detail below with reference to specific embodiments shown in the drawings. The embodiments are not limited to the present invention, and structural, methodological, or functional modifications of the invention from those skilled in the art are included within the scope of the invention.
As shown in fig. 1, the invention discloses an automatic acquisition method of actual moment of a surgical robot joint, which comprises the following steps:
Step S1: acquiring a positive limit position and a negative limit position of a movement stroke of a surgical robot joint, recording a motor stroke for controlling the surgical robot joint to move between the positive limit position and the negative limit position as a test stroke, and equally dividing the test stroke into a group of sectional strokes; when the motor is respectively positioned at the starting position or the ending position of the test stroke, the surgical robot joint correspondingly moves to the positive limit position or the negative limit position respectively;
Step S2: the motor is controlled to be switched to be in a CSP mode, the sectional strokes are sequentially operated from the initial position, whether the surgical robot joint is in a stable state or not is judged in real time, the current moment of the motor in the stable state of the surgical robot joint is collected and recorded as the stable moment operated in the sectional strokes, and the stable moment of the motor on all the sectional strokes in the whole test stroke is obtained after the final position of the test stroke is reached;
Step S3: the motor is controlled to be switched to be in a CST mode, the motor is repeatedly controlled to run the sectional strokes from the initial position, the initial moment of the motor is set to be the stable moment of the current sectional stroke measured in the step S2 before each sectional stroke runs, the unit moment is continuously increased on the basis of the stable moment according to the running direction of the motor on the test stroke until the joint position changes, and the difference value between the current moment of the motor and the unit moment is recorded as a critical moment;
step S4: and (3) fitting the critical moment after the step (S3), and simultaneously correcting the abrupt change data to obtain the processed output moment data.
Each step is explained in detail next.
The operation robot joint with different models has different operation ranges, so that the positive limit position and the negative limit position of the joint with current acquired data are required to be obtained in advance, the position of the motor when the joint is positioned at the positive limit position and the negative limit position is obtained in advance through experiments, and then the test stroke of the motor is obtained, wherein when the motor is positioned at one end point (such as the starting position of the motor) of the test stroke, the joint is positioned at the positive limit position; the joint is in a negative limit position when the motor is at the other end of the test stroke (e.g., the end position of the motor). And vice versa.
The test runs are equally divided into a set of segment runs. The running distance of each sectional travel can be selected in a calibration range according to actual requirements. And controlling the motor to sequentially run the sectional strokes from the starting position and finally reaching the ending position.
In the application, motors controlling the switching of the articulation of the surgical robot are provided with a CSP mode and a CST mode. The core idea is as follows: under the motor CSP mode, the stable joint can be immobilized, and the mechanical analysis shows that the moment provided by the motor is exactly equal to the resistance at the moment, and the moment value of the motor at the moment is read, so that the stable moment at the current joint position can be obtained. In the motor CST mode, the moment can be increased or reduced on the basis of the stable moment, and the critical moment of the motor can be obtained when the stable state of the joint is damaged, wherein the critical moment is the most labor-saving stable moment which can be used as the output moment.
In step S2 of the present invention, the motor is controlled to switch in CSP mode, the sectional strokes are sequentially operated from the initial position, before each stroke starts, it is determined whether the motor reaches the end position of the test stroke, if not, the motor is controlled to operate the current sectional stroke, after each sectional stroke is completed, it is determined whether the operation state is in a stable state in real time by the number of motor pulses until the stable state is reached, the current motor moment is collected as the stable moment in the sectional stroke, and then the steps are repeated until the end position of the test stroke is reached, and the stable moment of all sectional strokes in the test stroke is obtained. The steady state of the motor refers to a state having steady state parameters when operating in this state, such as: output power, rotational speed, current, temperature, etc. In the step S2, the "real-time determination of whether the surgical robot joint is in a stable state" refers to determining that the operation state is in a stable state when the pulse number is monitored to be stable and unchanged.
In a preferred embodiment, the step S2 further includes a reverse stabilizing moment collecting step, wherein the motor is controlled to sequentially run the sectional travel from the end position to reversely drive the surgical robot joint, whether the surgical robot joint is in a stable state is judged in real time, the current moment of the motor in the stable state of the surgical robot joint is collected and recorded as a reverse stabilizing moment running in the sectional travel, and the reverse stabilizing moment and the stabilizing moment are summed and averaged to form a corrected stabilizing moment.
Because the motion directions are different, the resistances are different, and the average value is more accurate after the moment values from the positive limit position to the negative limit position and from the negative limit position to the positive limit position are acquired and then fitted into two curves.
To ensure complete stability of the system, in step S2, after each of the segment strokes is finished, the motor is controlled to form a stop state to reduce the error in judging whether the surgical robot joint is in a stable state. Monitoring the running speed of the motor in real time in a pause state, ending the pause when the running speed is smaller than the pause speed threshold v, carrying out the sectional travel of the next section,
The calculation formula of the pause speed threshold v is as follows:
v= acc*rec*2bit/360/t；
wherein: acc: system accuracy;
rec: a motor reduction ratio;
bit: encoder bits;
t: segmenting travel sampling time;
v: pause speed threshold in pulses/second.
In step S3 of the present invention, the motor is controlled to switch to be in the CST mode, the motor is controlled to sequentially run the sectional strokes from the initial position, before each sectional stroke runs, the initial torque of the motor is set to be the stable torque of the current sectional stroke measured in step S2, and the unit torque is continuously increased on the basis of the stable torque according to the running direction of the motor on the test stroke until the joint position changes, then the difference between the current torque of the motor and the unit torque is recorded as the critical torque, the continuously increased unit torque is the minimum unit torque that the motor can run, and the accuracy of the critical torque collection is improved to the greatest extent.
Since in said step S3 the joint position has changed before the test of the critical moment, when the motor is at the critical moment, indicating that the critical value of the joint displacement has been exceeded, the data before displacement can be recorded as supplementary data for the accuracy of the further test results, in some embodiments.
In step S3, after obtaining the critical moment for each segment stroke, the motor is controlled to record the supplementary data of the critical moment after increasing x pulses each time on the basis of the critical moment, and the calculation formula of the pulse number x increased each time is as follows:
1≤x≤acc*rec*2bit/360；
Wherein: acc: the system precision is the self-contained data of the system;
rec: a motor reduction ratio;
bit: encoder bits.
The smaller the value of the pulse number x is set, the more supplementary data is collected, the more the test result is fit to the actual situation, and when the pulse number x=1 is increased each time, the supplementary data at all positions can be measured.
After the motion of the two running directions is ensured to be stable, the driving force of the motor is mainly used for overcoming the resistance, so that the data error of the two running directions is not very large, in other embodiments, the data in one running direction can be collected and then a curve is fitted, for example, the control joint is moved from the positive electrode position to the negative electrode position in a segmented mode or the control joint is moved from the negative electrode position to the positive electrode position in a segmented mode, and the data such as the stable moment, the critical moment and the supplementary data of each segmented stroke in the running direction are recorded, so that the collection time is shortened, and the collection efficiency is improved.
In step S4 of the present invention, all data collected by all the sectional strokes are processed, including removing abnormal data, correcting abrupt change data and processing abrupt change regions, and processed output torque data is obtained, wherein "all data collected by all the sectional strokes" refers to stable torque, critical torque and all supplementary data obtained by the motor in each running sectional stroke.
The abnormal data refers to data having a positive or negative sign that does not match other data, and as shown in fig. 2, other data are smaller than 0 (negative number) except for the salient point with the left side larger than 0 (positive number), so that the data at the salient point with the left side larger than 0 (positive number) are abnormal data, and the abnormal data are directly removed in the processing process.
The abrupt change data refers to data which suddenly appears or is slightly changed with the adjacent data in the acquisition process and is not in accordance with a theoretical model, but actual static friction force is generated at a certain or certain positions due to part processing, assembly and the like, so that the abrupt change data is adopted after processing, and the processed curve is used for smoothing local abrupt change data of the original data as shown in fig. 3; in some embodiments, smoothing the abrupt data by using a differential smoothing algorithm, collecting the abrupt data and the data of two sampling points on the abrupt data respectively, setting smoothing parameters corresponding to three data, obtaining smoothed data after the smoothing process after weighting calculation by the smoothing parameters, and replacing the abrupt data, when the abrupt data appears at a starting end or a final end, removing the abrupt data, wherein in a preferred embodiment, assuming that the current sampling point is p0, the first two sampling points are p1 and p2 respectively, the current output data is f0, the last output data is f1, and the last output data is f2, wherein the smoothing parameters are set by using the differential smoothing algorithm: b < 0 >, b < 1 >, b < 2 >, a < 1 >, a < 2 >, and the smoothing parameters are obtained by software analysis and fitting, and specific numerical values can be adjusted according to actual requirements, and are not described in detail herein.
The current output data f0 is calculated by the following formula:
f0 = b[0] * p0 + b[1]* p1 + b[2] * p2- a[1]* f1 - a[2] * f[2]。
The specific idea of mutation data processing is as follows: all data are associated with front and back data, the data of the current point is the largest in proportion during processing, but adjacent points can also affect the data value of the current point, namely if oversized/undersized points appear, mutation is obvious, the mutation points are error points, a mode of smoothing the error points by utilizing the adjacent points adopts the condition that some mutation is actually generated, and smoothing processing is carried out, so that moment is not mutated in the whole travel, in the embodiment, in order to improve the calculation efficiency, only the data of the first two sampling points of the mutation data are collected, in other embodiments, in order to improve the calculation accuracy, the data of a plurality of sampling points adjacent to the mutation data can be collected, or algorithm parameters are adjusted, and are not repeated, because the algorithm needs to participate in calculation of the front and back adjacent points, and the first few points cannot obtain the complete front adjacent points, so that the calculation is finally needed to be abandoned.
In step S4, the abrupt change region refers to region data that has an excessive change with the adjacent region, and in the processing process, the abrupt change region is extracted separately to perform fitting, and in some embodiments, when the abrupt change data is processed, according to practical situations, other filtering algorithms, such as median filtering, arithmetic average filtering, etc., or other algorithms, such as prediction algorithms, etc., may be further selected, so that the smoothness of the final data may be improved, and a curve may be better fitted.
The abrupt change region refers to region data which has overlarge change with the adjacent region, the data is inconsistent with a theoretical model, but the actual static friction force is generated in the region suddenly due to the fact that a certain stroke is coupled with other joints/components or other anomalies exist in the stroke, the abrupt change region is singly extracted and fitted in the processing process for fitting reality, as shown in fig. 4, the value suddenly decreases near 4000 points, the data trend obviously changes, and if all the data are forcedly fitted into a curve, errors at all positions are relatively large, so that the adverse effect on the actual application is generated. Therefore, the whole body is divided into two parts for fitting in the fitting process, so that the fitting is more accurate and practical.
And fitting the data processed by each sectional travel to a curve by using a polynomial. The fitting process can change polynomial degree, or other fitting methods, such as least square method, logarithmic fitting, etc., are selected to ensure that the fitting method is more practical.
It should be understood that although the present disclosure describes embodiments, not every embodiment is provided with a separate embodiment, and that this description is for clarity only, and that the skilled artisan should recognize that the embodiments may be combined as appropriate to form other embodiments that will be understood by those skilled in the art.
The above list of detailed descriptions is only specific to practical embodiments of the present invention, and they are not intended to limit the scope of the present invention, and all equivalent embodiments or modifications that do not depart from the spirit of the present invention should be included in the scope of the present invention.
Claims (10)
1. The automatic acquisition method of the actual moment of the joint of the surgical robot is characterized by comprising the following steps of: the method comprises the following steps:
Step S1: acquiring a positive limit position and a negative limit position of a movement stroke of a surgical robot joint, recording a motor stroke for controlling the surgical robot joint to move between the positive limit position and the negative limit position as a test stroke, and equally dividing the test stroke into a group of sectional strokes; when the motor is respectively positioned at the starting position or the ending position of the test stroke, the surgical robot joint correspondingly moves to the positive limit position or the negative limit position respectively;
Step S2: the motor is controlled to be switched to be in a CSP mode, the sectional strokes are sequentially operated from the initial position, whether the surgical robot joint is in a stable state or not is judged in real time, the current moment of the motor in the stable state of the surgical robot joint is collected and recorded as the stable moment operated in the sectional strokes, and the stable moment of the motor on all the sectional strokes in the whole test stroke is obtained after the final position of the test stroke is reached;
Step S3: the motor is controlled to be switched to be in a CST mode, the motor is repeatedly controlled to run the sectional strokes from the initial position, the initial moment of the motor is set to be the stable moment of the current sectional stroke measured in the step S2 before each sectional stroke runs, the unit moment is continuously increased on the basis of the stable moment according to the running direction of the motor on the test stroke until the joint position changes, and the difference value between the current moment of the motor and the unit moment is recorded as a critical moment;
step S4: and (3) fitting the critical moment after the step (S3), and simultaneously correcting the abrupt change data to obtain the processed output moment data.
2. The automatic acquisition method of the actual moment of the surgical robot joint according to claim 1, characterized in that: in the step S2 and the step S3, before each sectional stroke is operated, the motor first determines whether the motor reaches the end position of the test stroke, and if not, the motor is controlled to operate the current sectional stroke.
3. The automatic acquisition method of the actual moment of the surgical robot joint according to claim 1, characterized in that: in the step S2, the motor is controlled to sequentially run the sectional travel from the end position to reversely drive the surgical robot joint, whether the surgical robot joint is in a stable state is judged in real time, the current moment of the motor in the stable state of the surgical robot joint is collected and recorded as a reverse stable moment running in the sectional travel, and the reverse stable moment and the stable moment are summed and averaged to form a corrected stable moment.
4. The automatic acquisition method of the actual moment of the surgical robot joint according to claim 1, characterized in that: in the step S2, after each of the sectional strokes is finished, the motor is controlled to form a stop state so as to reduce the error of judging whether the surgical robot joint is in a stable state.
5. The automatic acquisition method of the actual moment of the surgical robot joint according to claim 4, wherein: in the step S2, the running speed of the motor is monitored in real time in a pause state, when the running speed is smaller than the pause speed threshold v, pause is finished, the next segment of the segmented travel is carried out,
The calculation formula of the pause speed threshold v is as follows:
v= acc*rec*2bit/360/t；
wherein: acc: system accuracy;
rec: a motor reduction ratio;
bit: encoder bits;
t: the run-length sampling time is segmented.
6. The automatic acquisition method of the actual moment of the surgical robot joint according to claim 1, characterized in that: a procedure for correcting the mutation data is also included between the step S2 and the step S3.
7. The automatic acquisition method of the actual moment of the surgical robot joint according to claim 1, characterized in that: in the step S3, the continuously increased unit torque is the minimum unit torque that can be operated by the motor.
8. The automatic acquisition method of the actual moment of the surgical robot joint according to claim 1, characterized in that: in the step S3, the method further includes a critical moment supplementing process, wherein the critical moment supplementing process includes that the motor is controlled to record critical moment supplementing data after x pulses are added each time on the basis of the critical moment, and a calculation formula of the number x of pulses added each time is as follows:
1≤x≤acc*rec*2bit/360；
Wherein: acc: the system precision is the self-contained data of the system;
rec: a motor reduction ratio;
bit: encoder bits.
9. The automatic acquisition system of the actual moment of the joint of the surgical robot is characterized in that: comprising
The motor stroke acquisition unit is used for acquiring a positive limit position and a negative limit position of a movement stroke of the surgical robot joint, recording the motor stroke for controlling the surgical robot joint to move between the positive limit position and the negative limit position as a test stroke, and equally dividing the test stroke into a group of sectional strokes; when the motor is respectively positioned at the starting position or the ending position of the test stroke, the surgical robot joint correspondingly moves to the positive limit position or the negative limit position respectively;
The stable moment acquisition unit is used for controlling the motor to be switched to be in a CSP mode, sequentially running the sectional strokes from the initial position, judging whether the surgical robot joint is in a stable state in real time, acquiring the current moment of the motor in the stable state of the surgical robot joint, recording the current moment as the stable moment running in the sectional strokes, and acquiring the stable moment of the motor on all the sectional strokes in the whole test stroke after reaching the end position of the test stroke;
the critical moment acquisition unit is used for controlling the motor to be switched to be in a CST mode, repeatedly controlling the motor to sequentially run the sectional strokes from the initial position, setting the initial moment of the motor as the stable moment of the current sectional stroke measured in the step S2 before each sectional stroke runs, continuously increasing the unit moment on the basis of the stable moment according to the running direction of the motor on the test stroke until the joint position changes, and recording the difference value between the current moment of the motor and the unit moment as the critical moment;
And the moment data processing unit is used for fitting the critical moment after the step S3 and correcting the abrupt change data at the same time to obtain the processed output moment data.
10. Surgical robot, including surgical robot joint, and control the motor of surgical robot joint motion, its characterized in that: output torque data obtained by the automatic acquisition method of the actual torque of the surgical robot joint according to any one of claims 1 to 8 is preset in the controller of the motor so as to control the motor to output the torque at the current position in the corresponding running direction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410453128.7A CN118046421B (en) | 2024-04-16 | 2024-04-16 | Automatic acquisition method and system for actual moment of joint of surgical robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410453128.7A CN118046421B (en) | 2024-04-16 | 2024-04-16 | Automatic acquisition method and system for actual moment of joint of surgical robot |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118046421A true CN118046421A (en) | 2024-05-17 |
| CN118046421B CN118046421B (en) | 2024-06-21 |
Family
ID=91050412
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410453128.7A Active CN118046421B (en) | 2024-04-16 | 2024-04-16 | Automatic acquisition method and system for actual moment of joint of surgical robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118046421B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4741218A (en) * | 1983-03-09 | 1988-05-03 | Kuka Schweissanlagen + Roboter Gmbh | Manipulator drive with slip-eliminating adjustment |
| US20100324699A1 (en) * | 2005-03-31 | 2010-12-23 | Massachusetts Institute Of Technology | Model-Based Neuromechanical Controller for a Robotic Leg |
| CN102378669A (en) * | 2009-01-30 | 2012-03-14 | 麻省理工学院 | Model-based neuromechanical controller for a robotic leg |
| CN104869969A (en) * | 2012-09-17 | 2015-08-26 | 哈佛大学校长及研究员协会 | Soft exosuit for assistance with human motion |
| CN105263448A (en) * | 2013-05-31 | 2016-01-20 | 哈佛大学校长及研究员协会 | Soft exosuit for assistance with human motion |
| CN105992554A (en) * | 2013-12-09 | 2016-10-05 | 哈佛大学校长及研究员协会 | Assistive flexible suits, flexible suit systems, and methods for making and control thereof to assist human mobility |
| US20170049587A1 (en) * | 2005-03-31 | 2017-02-23 | Massachusetts Institute Of Technology | Model-based neuromechanical controller for a robotic leg |
| CN110559082A (en) * | 2019-09-10 | 2019-12-13 | 深圳市精锋医疗科技有限公司 | surgical robot and control method and control device for mechanical arm of surgical robot |
| CN111243746A (en) * | 2020-01-20 | 2020-06-05 | 上海奥朋医疗科技有限公司 | Operation simulation method and system of vascular intervention operation robot |
| CN113143465A (en) * | 2021-03-30 | 2021-07-23 | 杭州键嘉机器人有限公司 | Mechanical arm dragging, guiding and positioning method based on joint torque |
| CN116488513A (en) * | 2023-04-28 | 2023-07-25 | 北京东土科技股份有限公司 | Stopping method and stopping device for control motor |
| CN116635799A (en) * | 2020-12-23 | 2023-08-22 | 欧姆龙株式会社 | Simulators and Simulators |
-
2024
- 2024-04-16 CN CN202410453128.7A patent/CN118046421B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4741218A (en) * | 1983-03-09 | 1988-05-03 | Kuka Schweissanlagen + Roboter Gmbh | Manipulator drive with slip-eliminating adjustment |
| US20100324699A1 (en) * | 2005-03-31 | 2010-12-23 | Massachusetts Institute Of Technology | Model-Based Neuromechanical Controller for a Robotic Leg |
| US20170049587A1 (en) * | 2005-03-31 | 2017-02-23 | Massachusetts Institute Of Technology | Model-based neuromechanical controller for a robotic leg |
| CN102378669A (en) * | 2009-01-30 | 2012-03-14 | 麻省理工学院 | Model-based neuromechanical controller for a robotic leg |
| CN104869969A (en) * | 2012-09-17 | 2015-08-26 | 哈佛大学校长及研究员协会 | Soft exosuit for assistance with human motion |
| CN105263448A (en) * | 2013-05-31 | 2016-01-20 | 哈佛大学校长及研究员协会 | Soft exosuit for assistance with human motion |
| CN105992554A (en) * | 2013-12-09 | 2016-10-05 | 哈佛大学校长及研究员协会 | Assistive flexible suits, flexible suit systems, and methods for making and control thereof to assist human mobility |
| CN110559082A (en) * | 2019-09-10 | 2019-12-13 | 深圳市精锋医疗科技有限公司 | surgical robot and control method and control device for mechanical arm of surgical robot |
| CN111243746A (en) * | 2020-01-20 | 2020-06-05 | 上海奥朋医疗科技有限公司 | Operation simulation method and system of vascular intervention operation robot |
| CN116635799A (en) * | 2020-12-23 | 2023-08-22 | 欧姆龙株式会社 | Simulators and Simulators |
| CN113143465A (en) * | 2021-03-30 | 2021-07-23 | 杭州键嘉机器人有限公司 | Mechanical arm dragging, guiding and positioning method based on joint torque |
| CN116488513A (en) * | 2023-04-28 | 2023-07-25 | 北京东土科技股份有限公司 | Stopping method and stopping device for control motor |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118046421B (en) | 2024-06-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109249394B (en) | Robot control method and system based on admittance control algorithm | |
| US12202141B2 (en) | Method of supporting adjustment of parameter set of robot, a non-transitory computer-readable storage medium, and information processing device | |
| US20190291270A1 (en) | Controller, machine learning device, and system | |
| JP2017074647A (en) | Robot system comprising function for calculating position and orientation of sensor | |
| US11059142B2 (en) | Controller, machine learning device, and system | |
| CN108860293B (en) | Steering control method and steering control device | |
| CN111067538B (en) | Method and system for evaluating upper limb movement function based on force and position information | |
| CN110142762B (en) | Robot joint position control method and device and robot | |
| CN113442143B (en) | Mechanical arm motion control method and device, controller and storage medium | |
| CN118046421B (en) | Automatic acquisition method and system for actual moment of joint of surgical robot | |
| CN114536346A (en) | Mechanical arm accurate path planning method based on man-machine cooperation and visual detection | |
| CN116423522B (en) | A zero-force control method for robot dragging teaching with adaptive friction compensation | |
| CN114800529B (en) | An error compensation method for industrial robots based on incremental learning of fixed-length memory windows | |
| CN109507879B (en) | Control device and machine learning device | |
| CN119779640A (en) | A device and method for detecting the response time of a curved screen of an automobile | |
| CN113910247A (en) | End-trajectory control method and system for industrial robot considering joint gap evolution | |
| CN113733158A (en) | Mechanical arm reducer performance testing method and system | |
| CN113143465A (en) | Mechanical arm dragging, guiding and positioning method based on joint torque | |
| CN116038693B (en) | A method for adjusting and optimizing servo control parameters of multi-axis robot joints | |
| CN114748101B (en) | Ultrasonic scanning control method, system and computer readable storage medium | |
| JPH11202914A (en) | Industrial robot and its fault detecting method, and recording medium where fault detecting program for industrial robot is recorded | |
| JP3122399B2 (en) | INDUSTRIAL ROBOT, FAULT DETECTION METHOD, AND RECORDING MEDIUM CONTAINING INDUSTRIAL ROBOT FAULT DETECTION PROGRAM | |
| JP2688207B2 (en) | Robot control device | |
| CN118163117B (en) | Method, system, device, medium, and program product for driving robot joint | |
| CN113927604B (en) | Industrial robot control self-checking method, system and terminal based on 5G communication |
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 |