CN117103283B - Feedback control method and device for multifunctional mechanical arm - Google Patents
Feedback control method and device for multifunctional mechanical arm Download PDFInfo
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- 238000007621 cluster analysis Methods 0.000 claims abstract description 15
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/161—Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
Abstract
The utility model provides a feedback control method and device of multi-functional arm, firstly obtain arm joint appearance data sequence when multi-functional arm work, decompose the arm joint appearance data sequence and handle, obtain joint average appearance data sequence and joint tremble data sequence, the characteristic cluster analysis of the joint tremble is tremble to the dimension collection of the joint, confirm joint tremble time sequence and joint tremble frequency sequence according to joint tremble point position, time alignment is carried out to joint tremble time sequence and joint tremble frequency sequence, obtain arm joint tremble eigenvalue, correct arm joint tremble eigenvalue as feedback signal and shake the proportional gain of proportional gain to the arm joint, can accomplish multi-functional arm's feedback control through shake proportional gain correction to multi-functional arm joint, can improve the control performance of arm when unstable control parameter exists in the arm work.
Description
Technical Field
The application relates to the technical field of mechanical arms, in particular to a feedback control method and device of a multifunctional mechanical arm.
Background
The mechanical arm is a multifunctional automatic tool, is generally composed of a series of joints, can simulate the arm structure of a human or animal, can rotate or move each joint, can perform various tasks through programming, can work in an unsupervised or semi-automatic mode, is suitable for various application fields due to the fact that the mechanical arm can improve production efficiency, accuracy and safety, is suitable for industrial manufacturing, medical care and scientific research, and therefore becomes an integral part of automatic production.
The feedback control of the multifunctional mechanical arm is a control method, and is used for monitoring and adjusting the motion and the behavior of the multifunctional mechanical arm, the feedback control of the multifunctional mechanical arm can cope with various different tasks and working environments, the condition that the mechanical arm can adapt to changes when the task is executed is ensured, the precision, the stability and the reliability are improved, the feedback control is very important for tasks needing high precision and high reliability, such as medical operation, precision machining, laboratory research, precision assembly and the like, the adaptability of the mechanical arm can be improved, the mechanical arm can be subjected to various tasks under different conditions, unstable control parameters can influence the adjustment of the vibration proportional gain of the mechanical arm joint when the mechanical arm works, and therefore the efficiency and the precision of the mechanical arm work are reduced, so that the vibration proportional gain of the multifunctional mechanical arm joint is required to be corrected, the feedback control of the mechanical arm is realized, and when the unstable control parameters exist in the mechanical arm work, the control performance of the mechanical arm is reduced.
Disclosure of Invention
The application provides a feedback control method and device of a multifunctional mechanical arm, which are used for solving the technical problem that the control performance of the mechanical arm is reduced when unstable control parameters exist in the operation of the mechanical arm.
In order to solve the technical problems, the application adopts the following technical scheme:
in a first aspect, the present application provides a feedback control method for a multifunctional mechanical arm, including the following steps:
acquiring a joint pose data sequence of the mechanical arm when the multifunctional mechanical arm works, and decomposing the joint pose data sequence of the mechanical arm to obtain an average joint pose data sequence and a joint tremor data sequence;
performing interpolation processing on the joint tremor data sequence to obtain a reconstructed tremor data sequence, and embedding the joint average pose data sequence into the reconstructed tremor data sequence to obtain a joint tremor dimension set;
performing joint tremor characterization cluster analysis on the joint tremor dimension set to obtain tremor identification indication, determining joint tremor offset according to the tremor identification indication, and projecting the joint tremor offset to the mechanical arm joint pose data sequence to obtain joint tremor points;
Determining a joint tremor time sequence and a joint tremor frequency sequence according to the joint tremor points, and performing time alignment on the joint tremor time sequence and the joint tremor frequency sequence to obtain a mechanical arm joint tremor characteristic value;
and correcting the vibration proportional gain of the mechanical arm joint by taking the vibration characteristic value of the mechanical arm joint as a feedback signal, so as to realize the feedback control of the multifunctional mechanical arm.
In some embodiments, the decomposing the mechanical arm joint pose data sequence to obtain a joint average pose data sequence and a joint tremor data sequence specifically includes:
uniformly processing the joint pose data sequence of the mechanical arm to obtain a joint average pose data sequence;
and filtering the joint average pose data sequence according to the mechanical arm joint pose data sequence to obtain a joint tremor data sequence.
In some embodiments, performing interpolation processing on the joint tremor data sequence to obtain a reconstructed tremor data sequence specifically includes:
abnormal removal is carried out on the joint tremor data sequence in a preset joint tremor interval to obtain a joint tremor removal abnormal data sequence;
determining missing data position points according to the joint tremor deisodata sequence;
And interpolating the missing data position points to obtain a reconstructed tremor data sequence.
In some embodiments, embedding the joint average pose data sequence into the reconstructed tremor data sequence, the obtaining the joint tremor dimension set specifically includes:
acquiring a starting time point of the joint average pose data sequence;
acquiring a starting time point of the reconstructed tremor data sequence;
aligning the joint average pose data sequence and the reconstructed tremor data sequence according to an initial time point to obtain a joint pose alignment data sequence;
and performing difference extraction on the joint pose alignment data sequence to obtain a joint tremor dimension set.
In some embodiments, performing joint tremor characterization cluster analysis on the joint tremor dimension set to obtain a tremor identification indication specifically includes:
acquiring joint tremor dimension data representing clusters and obeying a cluster distribution function of the clusters;
acquiring a critical value for determining whether the joint tremor dimension data obeys a cluster distribution function in the characterization cluster;
determining a parameter vector representing the cluster distribution function according to the cluster distribution function;
presetting a judging section of a clustering distribution function for receiving the joint tremor dimension data;
Determining a vibration identification sign according to the cluster distribution function, a critical value of the cluster distribution function, a parameter vector representing the cluster distribution function and a judging section of the cluster distribution function, wherein the vibration identification sign is determined by the following formula, namely:
wherein,representing the +.o. in the dimension set for joint tremor>Individual joint tremor data->A fibrillation recognition indication determined after performing a characterized cluster analysis,/->Represents a dimension set of joint tremor, comprising +.>The data of the individual joint tremor,，/>represents the +.>Clustering distribution function of individual joint tremor data, +.>Data representing the tremor dimension in a set of tremor dimensions>Obeying a cluster distribution function->，/>Representing data of tremor dimensions in a set of tremor dimensions for a joint tremorDifferentiation of the cluster distribution function is followed, +.>Representing the probability of data of joint tremor outside the cluster distribution function, +.>Data acceptance clustering obeying cluster distribution function representing joint tremor dimension，/>Indicating whether the dimension data of the joint tremor is subject to the cluster distribution function +.>Critical value of>Non-acceptance of clustering and non-compliance of clustering distribution function for representing dimension data of joint tremors>，/>Representing a cluster distribution function parameter vector.
In some embodiments, projecting the joint tremor offset to the mechanical arm joint pose data sequence, the obtaining a joint tremor point specifically includes:
Determining the joint tremor offset and the time interval of the mechanical arm joint pose data sequence;
time alignment is carried out on the joint tremor offset and the mechanical arm joint pose data sequence;
extracting all the vibration offset values of the joint vibration offset over a preset time;
and taking all the extracted vibration offset values at preset time as joint vibration points at corresponding time in the mechanical arm joint pose data sequence.
In some embodiments, the correcting the vibration proportional gain of the mechanical arm joint by using the vibration characteristic value of the mechanical arm joint as a feedback signal, and implementing the feedback control of the multifunctional mechanical arm specifically includes:
determining a standard mechanical arm joint vibration characteristic value;
when the vibration characteristic value of the mechanical arm joint is larger than the vibration characteristic value of the standard mechanical arm joint, increasing the proportional gain;
when the vibration characteristic value of the mechanical arm joint is smaller than the vibration characteristic value of the standard mechanical arm joint, reducing the proportional gain;
and the feedback control is performed on the multifunctional mechanical arm by increasing and decreasing the proportional gain.
In a second aspect, the present application provides a feedback control device of a multifunctional mechanical arm, including a mechanical arm joint pose control unit, the mechanical arm joint pose control unit includes:
The mechanical arm joint pose data determining module is used for acquiring a mechanical arm joint pose data sequence when the multifunctional mechanical arm works, and decomposing the mechanical arm joint pose data sequence to obtain a joint average pose data sequence and a joint tremor data sequence;
the joint tremor dimension set determining module is used for carrying out interpolation processing on the joint tremor data sequence to obtain a reconstructed tremor data sequence, and embedding the joint average pose data sequence into the reconstructed tremor data sequence to obtain a joint tremor dimension set;
the joint tremor point position determining module is used for carrying out joint tremor characterization cluster analysis on the joint tremor dimension set to obtain tremor identification indication, determining joint tremor offset according to the tremor identification indication, and projecting the joint tremor offset to the mechanical arm joint pose data sequence to obtain joint tremor points;
the mechanical arm joint tremor characteristic value determining module is used for determining a joint tremor time sequence and a joint tremor frequency sequence according to the joint tremor points, and performing time alignment on the joint tremor time sequence and the joint tremor frequency sequence to obtain a mechanical arm joint tremor characteristic value;
And the feedback correction module is used for correcting the vibration proportion gain of the mechanical arm joint by taking the vibration characteristic value of the mechanical arm joint as a feedback signal, so as to realize the feedback control of the multifunctional mechanical arm.
In a third aspect, the present application provides a computer device including a memory storing a code and a processor configured to acquire the code and perform the feedback control method of the multifunctional mechanical arm described above.
In a fourth aspect, the present application provides a computer readable storage medium storing a computer program which, when executed by a processor, implements the feedback control method of a multifunctional mechanical arm described above.
The technical scheme provided by the embodiment of the application has the following beneficial effects:
according to the feedback control method and device for the multifunctional mechanical arm, when the multifunctional mechanical arm works, a mechanical arm joint pose data sequence is obtained, the mechanical arm joint pose data sequence is subjected to decomposition processing to obtain a joint average pose data sequence and a joint tremor data sequence, the joint tremor data sequence is subjected to interpolation processing to obtain a reconstructed tremor data sequence, the joint average pose data sequence is embedded into the reconstructed tremor data sequence to obtain a joint tremor dimension set, joint tremor characterization clustering analysis is performed on the joint tremor dimension set to obtain tremor identification indication, a joint tremor offset is determined according to the tremor identification indication, the joint tremor offset is projected to the mechanical arm joint pose data sequence to obtain joint tremor points, a joint tremor time sequence and a joint tremor time sequence are determined according to the joint tremor points, the joint tremor time sequence and the joint tremor frequency sequence are subjected to time alignment to obtain a mechanical arm joint tremor feature value, and the mechanical arm joint tremor feature value is used as a feedback signal to correct the mechanical arm joint tremor joint tremor proportion gain, and the feedback control of the multifunctional mechanical arm is realized.
In addition, according to the characteristic value of the joint vibration of the mechanical arm, the availability and the analysis capacity of the joint pose data of the mechanical arm can be improved, the vibration behavior of the mechanical arm can be better controlled, so that higher quality and more accurate task execution are realized, furthermore, the characteristic value of the joint vibration of the mechanical arm is used as a feedback signal to adjust the proportional gain of the joint vibration of the mechanical arm, so that vibration is restrained or compensated to the greatest extent, the response speed and stability of the operation of the mechanical arm are balanced, the motion control performance of the mechanical arm is improved, and the control performance of the mechanical arm is improved when unstable control parameters exist in the operation of the mechanical arm.
Drawings
FIG. 1 is an exemplary flow chart of a method of feedback control of a multi-function robotic arm according to some embodiments of the present application;
FIG. 2 is a schematic diagram of exemplary hardware and/or software of a robotic arm joint pose control unit according to some embodiments of the present application;
Fig. 3 is a schematic structural diagram of a computer device for implementing a feedback control method of a multifunctional mechanical arm according to some embodiments of the present application.
Detailed Description
The method comprises the steps of firstly acquiring a mechanical arm joint pose data sequence when a multifunctional mechanical arm works, carrying out decomposition processing on the mechanical arm joint pose data sequence to obtain a joint average pose data sequence and a joint tremble data sequence, carrying out joint tremble characterization cluster analysis on a joint tremble dimension set, determining a joint tremble time sequence and a joint tremble frequency sequence according to joint tremble points, carrying out time alignment on the joint tremble time sequence and the joint tremble frequency sequence to obtain a mechanical arm joint tremble characteristic value, correcting mechanical arm joint tremble proportional gain by taking the mechanical arm joint tremble characteristic value as a feedback signal, realizing feedback control of the multifunctional mechanical arm, and improving control performance of the mechanical arm when unstable control parameters exist in the mechanical arm work.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments. Referring to fig. 1, which is an exemplary flowchart of a feedback control method of a multi-function mechanical arm according to some embodiments of the present application, the feedback control method 100 of the multi-function mechanical arm mainly includes the following steps:
In step 101, a joint pose data sequence of the mechanical arm is obtained when the multifunctional mechanical arm works, and the joint pose data sequence of the mechanical arm is decomposed to obtain a joint average pose data sequence and a joint tremor data sequence.
In particular, when the multifunctional mechanical arm works, the data sequence of the joint pose of the mechanical arm can be read from the data storage unit of the visual sensor of the mechanical arm.
In some embodiments, the decomposing the joint pose data sequence of the mechanical arm to obtain the joint average pose data sequence and the joint tremor data sequence may be implemented by the following steps:
uniformly processing the joint pose data sequence of the mechanical arm to obtain a joint average pose data sequence;
and filtering the joint average pose data sequence according to the mechanical arm joint pose data sequence to obtain a joint tremor data sequence.
When the mechanical arm joint pose data sequence is implemented, joint pose data corresponding to each second in the motion process are processed uniformly, the mechanical arm joint pose data sequence is formed by all joint pose data in the complete motion process, the average value of each motion process in all the mechanical arm joint pose data sequence is calculated, the average values of each motion process in all the mechanical arm joint pose data sequence are arranged according to time sequence, a joint average pose data sequence is obtained, the joint average pose data sequence is filtered according to the mechanical arm joint pose data sequence, and the average pose data sequence is subtracted from the mechanical arm joint pose data sequence, so that a joint tremble data sequence is obtained.
It should be noted that, the manipulator joint pose data sequence in the present application includes information such as a joint rotation angle, a joint diastole position, a joint pose and the like corresponding to each time point in the running time of the manipulator executing the instruction, and the degree of completion of the manipulator joint on the instruction information is different due to different influences of various unstable control parameters, and the manipulator joint pose data sequence is decomposed, so that the average state of the pose of the manipulator joint and the micro offset relative to the average pose can be better understood.
In step 102, interpolation processing is performed on the joint tremor data sequence to obtain a reconstructed tremor data sequence, and the joint average pose data sequence is embedded into the reconstructed tremor data sequence to obtain a joint tremor dimension set.
In some embodiments, the interpolation processing is performed on the joint tremor data sequence, so as to obtain a reconstructed tremor data sequence, which may be implemented by the following steps:
abnormal removal is carried out on the joint tremor data sequence in a preset joint tremor interval to obtain a joint tremor removal abnormal data sequence;
determining missing data position points according to the joint tremor deisodata sequence;
and interpolating the missing data position points to obtain a reconstructed tremor data sequence.
When the method is specifically implemented, after the joint pose data sequence of the mechanical arm is decomposed, abnormal data exists in the joint tremor data sequence, normal operation data of the mechanical arm is obtained according to the normal working state of the mechanical arm, a preset joint tremor interval is used for carrying out abnormal removal on the joint tremor data sequence, the data in the joint tremor data sequence are compared with the preset joint tremor interval one by one, if the data in the joint tremor data sequence is outside the preset joint tremor interval, the reserved data is abandoned, if the data in the joint tremor data sequence is within the preset joint tremor interval, the reserved data is reserved, the joint tremor data sequence is traversed, all reserved data is used as joint tremor data sequences, missing data at corresponding time points exist in the joint tremor and data sequences, positions of the missing data at the corresponding time points are used as missing data position points, interpolation is carried out on the data of the missing data position points, and a reconstructed tremor data sequence is obtained after completion, wherein interpolation is carried out on the data of the missing data position points by the following formulas:
wherein,is->Data after interpolation of the location points of the missing data, < > >Is->Data preceding the missing data location, < +.>Is->Data following the missing data location points.
In some embodiments, embedding the joint average pose data sequence into the reconstructed tremor data sequence to obtain a joint tremor dimension set may be implemented by:
acquiring a starting time point of the joint average pose data sequence;
acquiring a starting time point of the reconstructed tremor data sequence;
aligning the joint average pose data sequence and the reconstructed tremor data sequence according to an initial time point to obtain a joint pose alignment data sequence;
and performing difference extraction on the joint pose alignment data sequence to obtain a joint tremor dimension set.
When the mechanical arm starts to work, a starting time point of a joint pose sequence of the mechanical arm is taken as a starting time point of a joint average pose data sequence and a reconstructed tremor data sequence, the joint average pose data sequence and the reconstructed tremor data sequence are aligned according to real time points, two rows of data with the same time starting points are obtained, the fact that the data in the joint average pose data sequence and the data in the reconstructed tremor data sequence in the same position of the two rows of data with the same time starting points are consistent is ensured, the data with the same time starting points in the two rows of data are taken as the joint pose alignment data sequence, the data of the reconstructed tremor data sequence and the data of the joint average pose data sequence in the joint pose alignment data sequence in the same time point are differed, then absolute values are taken, the obtained results are taken as the tremor dimension data of the joints until the tremor dimension data of the joints corresponding to all time points in the joint pose alignment data sequence are obtained, and the tremor dimension data of the joints form a tremor dimension set of the joints.
It should be noted that, in the application, interpolation processing is performed on the joint tremor data sequence, so that the integrity of the joint tremor data sequence can be better recovered, and the joint tremor dimension set can be obtained by embedding the joint average pose data sequence into the reconstruction data sequence, so that the degree of the joint tremor of the mechanical arm can be displayed more carefully.
And 103, performing joint tremor characterization cluster analysis on the joint tremor dimension set to obtain tremor identification indication, determining joint tremor offset according to the tremor identification indication, and projecting the joint tremor offset to the mechanical arm joint pose data sequence to obtain joint tremor points.
In some embodiments, the joint tremor characterization cluster analysis is performed on the joint tremor dimension set to obtain a tremor identification indication, which may be implemented by the following steps:
acquiring joint tremor dimension data representing clusters and obeying a cluster distribution function of the clusters;
acquiring a critical value for determining whether the joint tremor dimension data obeys a cluster distribution function in the characterization cluster;
determining a parameter vector representing the cluster distribution function according to the cluster distribution function;
presetting a judging section of a clustering distribution function for receiving the joint tremor dimension data;
And determining the vibration identification indication according to the cluster distribution function, the critical value of the cluster distribution function, the parameter vector representing the cluster distribution function and the judgment interval of the cluster distribution function.
In particular, the joint tremor data in the joint tremor dimension set represents different joint tremor characterizations, and the joint tremor data representing various characterizations are selected as the characterization of the joint tremor according to the different joint tremor characterizations, such asAll joint tremor data in the interval belong to the first category of characterization, +.>All the joint tremor data in the interval represent a second type of representation, and the like, joint tremor data representing each representation are obtained, then a cluster distribution function is obtained according to the property of the distribution function, maximum likelihood estimation is carried out on joint tremor dimension data in the cluster distribution function, then the critical value obeying each type of representation cluster distribution function in the joint tremor dimension data is obtained, the parameter vector representing the cluster distribution function is determined according to the cluster distribution function, the judgment interval of the cluster distribution function representing the cluster is accepted according to the representation preset joint tremor dimension data representing the joint tremor dimension data in the cluster distribution function, and then the tremor identification indication is determined, wherein the tremor identification indication is determined by the following formula:
Wherein,representing the +.o. in the dimension set for joint tremor>Individual joint tremor data->A fibrillation recognition indication determined after performing a characterized cluster analysis,/->Represents a dimension set of joint tremor, comprising +.>The data of the individual joint tremor,，/>represents the +.>Clustering distribution function of individual joint tremor data, +.>Data representing the tremor dimension in a set of tremor dimensions>Obeying a cluster distribution function->，/>Representing data of tremor dimensions in a set of tremor dimensions for a joint tremorDifferentiation of the cluster distribution function is followed, +.>Representing the probability of data of joint tremor outside the cluster distribution function, +.>Data acceptance clustering obeying cluster distribution function representing joint tremor dimension，/>Indicating whether the dimension data of the joint tremor is subject to the cluster distribution function +.>Critical value of>Non-acceptance of clustering and non-compliance of clustering distribution function for representing dimension data of joint tremors>，/>Representing a cluster distribution function parameter vector.
It should be noted that, the clustering distribution function parameter vector is used to describe the distribution situation among different categories in the data set, each characterization cluster can be performed after the joint tremor dimension set is subjected to joint tremor characterization analysis, the directional analysis of joint tremors is facilitated later, a specific distribution interval is provided for each clustered joint tremor characterization after the joint tremor dimension set is subjected to characterization cluster analysis, the average value of the joint tremor data in each characterization specific distribution interval is calculated, the joint tremor characterization average value of each interval is obtained, and the joint tremor characterization average value of each interval is used as the tremor identification indication of the interval.
Specifically, when the method is implemented, the difference is made according to the vibration identification indication and the average pose data of the corresponding section in the average position data sequence of the mechanical arm joint, and the result obtained by the difference is used as the joint vibration offset, wherein the joint vibration offset represents the offset from the average pose in the joint vibration process, and the joint vibration offset better represents the smoothness degree of the mechanical arm joint motion and the offset degree compared with the expected track.
In some embodiments, the projecting the joint tremor offset to the mechanical arm joint pose data sequence may be implemented by:
determining the joint tremor offset and the time interval of the mechanical arm joint pose data sequence;
time alignment is carried out on the joint tremor offset and the mechanical arm joint pose data sequence;
extracting all the vibration offset values of the joint vibration offset over a preset time;
and taking all the extracted vibration offset values at preset time as joint vibration points at corresponding time in the mechanical arm joint pose data sequence.
Specifically, when the mechanical arm starts to work, the starting time is used as the starting time of the joint vibration offset and the mechanical arm joint pose data sequence, the joint vibration offset and the mechanical arm joint pose data sequence are started according to the same starting time, data points with 0.5s as a time interval are arranged, time alignment is completed, the middle time of the time interval is used as the preset time, and the joint vibration offset value corresponding to the preset time is selected as the joint vibration point position on the same time point in the mechanical arm joint pose data sequence.
It should be noted that, determining the joint tremor point location, by aligning the data at the start time, the complexity of subsequent data processing and analysis can be reduced, which is beneficial to evaluating the influence of tremor on the motion of the mechanical arm, analyzing the time sequence property of tremor and showing the tremor degree at the corresponding time point when the joint tremor occurs in the operation of the mechanical arm.
In step 104, a joint tremor time sequence and a joint tremor frequency sequence are determined according to the joint tremor points, and the joint tremor time sequence and the joint tremor frequency sequence are aligned in time to obtain a mechanical arm joint tremor characteristic value.
Specifically, when the method is implemented, the time frequency decomposition is carried out on the joint trembling points, the corresponding time points are arranged in the joint pose sequence of the mechanical arm, the time of occurrence of the joint trembling is represented, 2s is taken as a time interval, namely the mechanical arm working time is divided into non-overlapping time windows, the number of the joint trembling points occurring in the time windows is counted for each time window, the trembling frequency is counted as the trembling frequency of the window, the window is moved, the trembling frequency is counted time step by time step until the whole time range is covered, the joint trembling condition in the time period is recorded at the central time point of each window, the joint trembling time sequence is formed, and the joint trembling degree in the time period, namely the absolute value of the difference value between the joint trembling offset and the average pose of the mechanical arm joint at the time point is recorded at the central time point of each time window as the joint trembling frequency, so that the joint trembling frequency sequence is formed.
In some embodiments, the time alignment of the joint tremor time sequence and the joint tremor frequency sequence may be implemented by the following steps:
acquisition of the dimension set of joint tremorIndividual joint tremor data->；
Acquiring average pose data in all time windows in an average pose data sequence of a mechanical arm joint；
Acquiring average pose data of mechanical arm joints in time window；
Determining the first time windowIndividual joint tremor offset +.>；
Determining the joint tremor dimension setTremor frequency corresponding to individual joint tremor data>，；
According to the dimension set of joint tremorIndividual joint tremor data->Average pose data in all time windows in average pose data sequence of mechanical arm joints/>Mean pose data of mechanical arm joints in time windowFirst->Individual joint tremor offset +.>Degree of joint tremor dimension set>Tremor frequency corresponding to individual joint tremor data>Determining a vibration characteristic value of the mechanical arm joint, wherein the vibration characteristic value of the mechanical arm joint is determined by the following formula, namely:
wherein,representing the characteristic value of the joint tremor of the mechanical arm, +.>Represents a quantization factor for the frequency of joint tremor, The difference degree of the average pose of the mechanical arm joint and the joint tremor offset in all time windows is represented,mean pose data of the joints of the mechanical arm and the first +.>Individual joint tremor offsetThe difference in the amount of the two components,sum of tremor frequency for the dimension set of joint tremor, +.>The +.f. in the joint tremor dimension set in the tremor frequency sum of the joint tremor dimension set>Yaw rate of individual joint tremor data.
In the present application, the joint tremor frequency quantization factorIs the frequency of the mechanical arm joint vibration in unit time, the +.>Individual joint tremor offset +.>After the joint tremor offset is divided by time windows through traversing the joint tremor offset, the corresponding value of the joint tremor offset in one time window is time aligned according to the joint tremor offset and the average pose data sequence of the mechanical arm joint at the same starting time, and then divided by taking 2s as the time window, so as to obtain the absolute value of the difference value between the joint tremor offset data and the average pose of the mechanical arm joint at the central time point of each time window in each time window as the joint tremor frequency, and further determine the first moment in the joint tremor dimension set >Tremor frequency corresponding to individual joint tremor data>Wherein, there is +.>And each.
It should be noted that, each data point in the joint tremor time sequence represents the frequency of the joint tremor in the corresponding time window, so that the monitoring of the tremor degree of the mechanical arm can be more effectively performed, the availability and analysis capability of the joint pose data of the mechanical arm can be improved by time aligning the joint tremor sequence and generating the joint tremor characteristic value of the mechanical arm, and the tremor behavior of the mechanical arm can be better controlled, so that higher quality and more accurate task execution can be realized.
In step 105, the characteristic value of the vibration of the mechanical arm joint is used as a feedback signal to correct the vibration proportion gain of the mechanical arm joint, so as to realize the feedback control of the multifunctional mechanical arm.
In some embodiments, the mechanical arm joint vibration characteristic value is used as a feedback signal to correct the mechanical arm joint vibration proportional gain, and the feedback control of the multifunctional mechanical arm can be realized by adopting the following steps:
determining a standard mechanical arm joint vibration characteristic value;
when the vibration characteristic value of the mechanical arm joint is larger than the vibration characteristic value of the standard mechanical arm joint, increasing the proportional gain;
When the vibration characteristic value of the mechanical arm joint is smaller than the vibration characteristic value of the standard mechanical arm joint, reducing the proportional gain;
and the feedback control is performed on the multifunctional mechanical arm by increasing or decreasing the proportional gain.
When the mechanical arm joint vibration characteristic value is smaller than the standard mechanical arm joint vibration characteristic value, the proportional gain is reduced through the manual change controller, so that excessive response and instability of control parameters are avoided.
It should be noted that, comparing the standard joint vibration characteristic value with the mechanical arm joint vibration characteristic value and then adjusting the proportional gain in the application is for better controlling and optimizing the performance and working behavior of the mechanical arm, increasing the proportional gain can result in faster response speed and stronger control force, so as to compensate vibration faster, reducing the proportional gain can slow down the response speed of the controller, and is helpful for reducing instability of oscillation or control parameters, adjusting the mechanical arm joint vibration proportional gain by taking the mechanical arm joint vibration characteristic value as a feedback signal, so as to inhibit or compensate vibration to the greatest extent, and balancing the response speed and stability of the operation of the mechanical arm, thereby improving the motion control performance of the mechanical arm.
In addition, in another aspect of the present application, in some embodiments, the present application provides a feedback control device of a multifunctional mechanical arm, where the device includes a mechanical arm joint pose control unit, referring to fig. 2, which is a schematic diagram of exemplary hardware and/or software of the mechanical arm joint pose control unit according to some embodiments of the present application, where the mechanical arm joint pose control unit 200 includes: the mechanical arm joint pose data obtaining module 201, the joint tremor dimension set determining module 202, the joint tremor point location determining module 203, the mechanical arm joint tremor characteristic value determining module 204 and the feedback correction module 205 are respectively described as follows:
the mechanical arm joint pose data acquisition module 201 is mainly used for acquiring mechanical arm joint pose sequence data of a multifunctional mechanical arm when in operation, and decomposing the mechanical arm joint pose sequence data to obtain joint average pose sequence data and joint tremor sequence data;
the joint tremor dimension set determining module 202, where the joint tremor dimension set determining module 202 is mainly configured to perform interpolation processing on the joint tremor sequence data to obtain reconstructed tremor sequence data, and embed the joint average pose sequence data into the reconstructed tremor sequence data to obtain a joint tremor dimension set;
The joint tremor point location determining module 203, where the joint tremor point location determining module 203 is mainly configured to perform joint tremor characterization cluster analysis on the joint tremor dimension set to obtain a tremor identification indication, determine a joint tremor offset according to the tremor identification indication, and project the joint tremor offset to the mechanical arm joint pose sequence data to obtain a joint tremor point location;
the mechanical arm joint tremor characteristic value determining module 204, where the mechanical arm joint tremor characteristic value determining module 204 is mainly configured to determine a joint tremor time sequence and a mechanical arm joint tremor frequency sequence according to the joint tremor point location, and time align the joint tremor time sequence and the joint tremor frequency sequence to obtain a mechanical arm joint tremor characteristic value;
the feedback correction module 205, in this application, the feedback correction module 205 is mainly configured to correct the vibration proportional gain of the mechanical arm joint by using the vibration characteristic value of the mechanical arm joint as a feedback signal, so as to implement feedback control of the multifunctional mechanical arm.
In addition, the application also provides a computer device, which comprises a memory and a processor, wherein the memory stores codes, and the processor is configured to acquire the codes and execute the feedback control method of the multifunctional mechanical arm.
In some embodiments, reference is made to fig. 3, which is a schematic structural diagram of a computer device implementing a feedback control method of a multifunctional mechanical arm according to some embodiments of the present application. The feedback control method of the multifunctional manipulator in the above-described embodiment may be implemented by a computer device shown in fig. 3, which includes at least one processor 301, a communication bus 302, a memory 303, and at least one communication interface 304.
The processor 301 may be a general purpose central processing unit (central processing unit, CPU), application Specific Integrated Circuit (ASIC) or execution of one or more feedback control methods for controlling the multi-function robotic arm of the present application.
Communication bus 302 may include a path to transfer information between the above components.
The Memory 303 may be, but is not limited to, a read-only Memory (ROM) or other type of static storage device that can store static information and instructions, a random access Memory (random access Memory, RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only Memory (electrically erasable programmable read-only Memory, EEPROM), a compact disc (compact disc read-only Memory) or other optical disk storage, a compact disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory 303 may be stand alone and be coupled to the processor 301 via the communication bus 302. Memory 303 may also be integrated with processor 301.
The memory 303 is used for storing program codes for executing the embodiments of the present application, and the processor 301 controls the execution. The processor 301 is configured to execute program code stored in the memory 303. One or more software modules may be included in the program code. The manipulator joint pose sequence data in the above embodiments may be implemented by one or more software modules in the processor 301 and the program code in the memory 303.
Communication interface 304, using any transceiver-like device for communicating with other devices or communication networks, such as ethernet, radio access network (radio access network, RAN), wireless local area network (wireless local area networks, WLAN), etc.
In a specific implementation, as an embodiment, a computer device may include a plurality of processors, where each of the processors may be a single-core (single-CPU) processor or may be a multi-core (multi-CPU) processor. A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).
The computer device may be a general purpose computer device or a special purpose computer device. In particular implementations, the computer device may be a desktop, laptop, web server, palmtop (personal digital assistant, PDA), mobile handset, tablet, wireless terminal device, communication device, or embedded device. Embodiments of the present application are not limited in the type of computer device.
In addition, the application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program realizes the feedback control method of the multifunctional mechanical arm when being executed by a processor.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the invention. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (10)
1. The feedback control method of the multifunctional mechanical arm is characterized by comprising the following steps of:
acquiring a joint pose data sequence of the mechanical arm when the multifunctional mechanical arm works, and decomposing the joint pose data sequence of the mechanical arm to obtain an average joint pose data sequence and a joint tremor data sequence;
Performing interpolation processing on the joint tremor data sequence to obtain a reconstructed tremor data sequence, and embedding the joint average pose data sequence into the reconstructed tremor data sequence to obtain a joint tremor dimension set;
performing joint tremor characterization cluster analysis on the joint tremor dimension set to obtain tremor identification indication, determining joint tremor offset according to the tremor identification indication, and projecting the joint tremor offset to the mechanical arm joint pose data sequence to obtain joint tremor points;
determining a joint tremor time sequence and a joint tremor frequency sequence according to the joint tremor points, and performing time alignment on the joint tremor time sequence and the joint tremor frequency sequence to obtain a mechanical arm joint tremor characteristic value;
and correcting the vibration proportional gain of the mechanical arm joint by taking the vibration characteristic value of the mechanical arm joint as a feedback signal, so as to realize the feedback control of the multifunctional mechanical arm.
2. The method of claim 1, wherein the decomposing the mechanical arm joint pose data sequence to obtain a joint average pose data sequence and a joint tremor data sequence specifically comprises:
Uniformly processing the joint pose data sequence of the mechanical arm to obtain a joint average pose data sequence;
and filtering the joint average pose data sequence according to the mechanical arm joint pose data sequence to obtain a joint tremor data sequence.
3. The method of claim 1, wherein interpolating the joint tremor data sequence to obtain a reconstructed tremor data sequence comprises:
abnormal removal is carried out on the joint tremor data sequence in a preset joint tremor interval to obtain a joint tremor removal abnormal data sequence;
determining missing data position points according to the joint tremor deisodata sequence;
and interpolating the missing data position points to obtain a reconstructed tremor data sequence.
4. The method of claim 1, wherein embedding the joint average pose data sequence into the reconstructed tremor data sequence to obtain a set of joint tremor dimensions comprises:
acquiring a starting time point of the joint average pose data sequence;
acquiring a starting time point of the reconstructed tremor data sequence;
aligning the joint average pose data sequence and the reconstructed tremor data sequence according to an initial time point to obtain a joint pose alignment data sequence;
And performing difference extraction on the joint pose alignment data sequence to obtain a joint tremor dimension set.
5. The method of claim 1, wherein performing joint tremor characterization cluster analysis on the set of joint tremor dimensions to obtain a tremor identification indication comprises:
acquiring joint tremor dimension data representing clusters and obeying a cluster distribution function of the clusters;
acquiring a critical value for determining whether the joint tremor dimension data obeys a cluster distribution function in the characterization cluster;
determining a parameter vector representing the cluster distribution function according to the cluster distribution function;
presetting a judging section of a clustering distribution function for receiving the joint tremor dimension data;
determining a vibration identification indicator according to the cluster distribution function, the critical value of the cluster distribution function, the parameter vector representing the cluster distribution function and the judging section of the cluster distribution function, wherein the vibration identification indicator is determined by the following formula, namely:
wherein,representing the +.o. in the dimension set for joint tremor>Individual joint tremor data->A fibrillation recognition indication determined after performing a characterized cluster analysis,/->Represents a dimension set of joint tremor, comprising +.>The data of the individual joint tremor, ，/>Represents the +.>Clustering distribution function of individual joint tremor data, +.>Data representing the tremor dimension in a set of tremor dimensions>Obeying a cluster distribution function->，/>Representing data of tremor dimensions in a set of tremor dimensions for a joint tremorDifferentiation of the cluster distribution function is followed, +.>Representing the probability of data of joint tremor outside the cluster distribution function, +.>Data acceptance clustering obeying cluster distribution function representing joint tremor dimension，/>Indicating whether the dimension data of the joint tremor is subject to the cluster distribution function +.>Critical value of>Non-acceptance of clustering and non-compliance of clustering distribution function for representing dimension data of joint tremors>，/>Representing a cluster distribution function parameter vector.
6. The method of claim 1, wherein projecting the joint tremor offset to the manipulator joint pose data sequence to obtain a joint tremor point location specifically comprises:
determining the joint tremor offset and the time interval of the mechanical arm joint pose data sequence;
time alignment is carried out on the joint tremor offset and the mechanical arm joint pose data sequence;
extracting all the vibration offset values of the joint vibration offset over a preset time;
And taking all the extracted vibration offset values at preset time as joint vibration points at corresponding time in the mechanical arm joint pose data sequence.
7. The method of claim 1, wherein correcting the arm joint tremor proportional gain using the arm joint tremor characteristic value as a feedback signal, the implementing the feedback control of the multifunctional arm specifically includes:
determining a standard mechanical arm joint vibration characteristic value;
when the vibration characteristic value of the mechanical arm joint is larger than the vibration characteristic value of the standard mechanical arm joint, increasing the proportional gain;
when the vibration characteristic value of the mechanical arm joint is smaller than the vibration characteristic value of the standard mechanical arm joint, reducing the proportional gain;
and the feedback control is performed on the multifunctional mechanical arm by increasing or decreasing the proportional gain.
8. The utility model provides a multi-functional arm's feedback control device which characterized in that, including arm joint position appearance control unit, arm joint position appearance control unit includes:
the mechanical arm joint pose data determining module is used for acquiring a mechanical arm joint pose data sequence when the multifunctional mechanical arm works, and decomposing the mechanical arm joint pose data sequence to obtain a joint average pose data sequence and a joint tremor data sequence;
The joint tremor dimension set determining module is used for carrying out interpolation processing on the joint tremor data sequence to obtain a reconstructed tremor data sequence, and embedding the joint average pose data sequence into the reconstructed tremor data sequence to obtain a joint tremor dimension set;
the joint tremor point position determining module is used for carrying out joint tremor characterization cluster analysis on the joint tremor dimension set to obtain tremor identification indication, determining joint tremor offset according to the tremor identification indication, and projecting the joint tremor offset to the mechanical arm joint pose data sequence to obtain joint tremor points;
the mechanical arm joint tremor characteristic value determining module is used for determining a joint tremor time sequence and a joint tremor frequency sequence according to the joint tremor points, and performing time alignment on the joint tremor time sequence and the joint tremor frequency sequence to obtain a mechanical arm joint tremor characteristic value;
and the feedback correction module is used for correcting the vibration proportion gain of the mechanical arm joint by taking the vibration characteristic value of the mechanical arm joint as a feedback signal, so as to realize the feedback control of the multifunctional mechanical arm.
9. A computer device, characterized in that the computer device comprises a memory storing a code and a processor configured to acquire the code and execute the feedback control method of the multifunctional robot arm according to any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the feedback control method of a multi-function mechanical arm according to any one of claims 1 to 7.
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