CN114083533A - Data processing method and device based on mechanical arm - Google Patents
Data processing method and device based on mechanical arm Download PDFInfo
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- CN114083533A CN114083533A CN202111320039.8A CN202111320039A CN114083533A CN 114083533 A CN114083533 A CN 114083533A CN 202111320039 A CN202111320039 A CN 202111320039A CN 114083533 A CN114083533 A CN 114083533A
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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
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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
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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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
- B25J9/1694—Programme controls characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
- B25J9/1697—Vision controlled systems
Abstract
The invention discloses a data processing method and a data processing device based on a mechanical arm, wherein the method comprises the following steps: acquiring image information of a target object; determining a target track information set according to target object image information and a preset track planning rule; determining a control instruction set according to the target track information set; the control instruction set comprises a plurality of target control instructions; the target control instruction is used for instructing adjustment control of the robot arm. Therefore, the method and the device can determine the target track information from the target object image information by using the track planning rule, and then process the target track information to obtain the target control instruction for indicating the adjustment control of the mechanical arm, thereby being beneficial to realizing the smooth control of the mechanical arm and improving the control efficiency of the mechanical arm.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a data processing method and device based on a mechanical arm.
Background
In the control process of the mechanical arm, because of the limitation of the port opening authority, the smooth control of the mechanical arm is generally difficult to realize. Therefore, it is important to provide a data processing method and apparatus based on a robot arm to achieve smooth control of the robot arm, thereby improving the control efficiency of the robot arm.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a data processing method and device based on a mechanical arm, which can determine target track information from target object image information by using a track planning rule, and then process the target track information to obtain a target control instruction for instructing adjustment and control of the mechanical arm, thereby facilitating smooth control of the mechanical arm and improving the control efficiency of the mechanical arm.
In order to solve the technical problem, a first aspect of the embodiments of the present invention discloses a data processing method based on a robot arm, where the method includes:
acquiring image information of a target object;
determining a target track information set according to the target object image information and a preset track planning rule;
determining a control instruction set according to the target track information set; the control instruction set comprises a plurality of target control instructions; the target control instruction is used for indicating the adjustment control of the mechanical arm.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining a target trajectory information set according to the target object image information and a preset trajectory planning rule includes:
according to the image information of the target object, determining gravity center coordinate information corresponding to the target object;
determining initial attitude information of the mechanical arm according to the gravity center coordinate information; the initial posture information of the mechanical arm is used for configuring the initial posture of the mechanical arm;
and determining a target track information set according to the initial attitude information of the mechanical arm and a preset track planning model.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining, according to the image information of the target object, barycentric coordinate information corresponding to the target object includes:
processing the target object image information according to a preset target detection rule to obtain a target area;
processing the target area according to a preset feature extraction rule to obtain a pixel coordinate information set; the pixel coordinate information comprises at least 2 pixel coordinate information;
and calculating the pixel coordinate information set to obtain gravity center coordinate information corresponding to the target object.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the initial posture information of the mechanical arm includes initial posture information of a camera and initial posture information of a joint angle;
according to the gravity center coordinate information, determining initial attitude information of the mechanical arm, including:
acquiring initial coordinate information and mechanical arm structure information of a mechanical arm;
calculating the gravity center coordinate information and the mechanical arm initial coordinate information to obtain the camera initial attitude information;
and calculating the initial attitude information of the camera and the structural information of the mechanical arm to obtain the initial attitude information of the joint angle.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the trajectory planning model includes a first planning model and a second planning model;
determining a target track information set according to the mechanical arm initial attitude information and a preset track planning model, wherein the determining comprises the following steps:
calculating the initial attitude information of the mechanical arm to obtain initial point information;
acquiring a target point information set; the target point information set comprises L pieces of target point information; l is a positive integer greater than or equal to 2;
calculating and processing initial point information and the target point information set by using the first planning model to obtain an initial track information set; the initial track information set comprises the L pieces of initial track information;
determining running time information according to the initial track information set;
and processing the running time information by using the second planning model to obtain a target track information set.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining a control instruction set according to the target track information set includes:
determining a target control model set according to the target track information set; the target control model set comprises a plurality of target control models;
determining attitude position information according to the target object image information and a preset attitude analysis model;
and processing the attitude and position information by using the target control model set to obtain a control instruction set.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the determining a target control model set according to the target trajectory information set includes:
for any target track information, matching track characteristic information corresponding to the target track information with model characteristic information corresponding to all control models to be selected in a preset control model set to obtain a matching result; the track characteristic information comprises M track information elements; m is an odd positive integer; the model feature information comprises N model information elements; n is an odd positive integer; track element information corresponding to a track information element at the middle position in the track characteristic information is matched with track element information corresponding to a track information element at the last position; track element information corresponding to a track information element at a second position in sequence in the track characteristic information is matched with track element information corresponding to a track information element at the last position;
and when the matching result shows that target model characteristic information matched with the track characteristic information corresponding to the target track information exists in the control model set to be selected, determining the control model to be selected corresponding to the target model characteristic information as a target control model.
The second aspect of the embodiment of the invention discloses a data processing device based on a mechanical arm, which comprises:
the acquisition module is used for acquiring image information of a target object;
the first determining module is used for determining a target track information set according to the target object image information and a preset track planning rule;
the second determining module is used for determining a control instruction set according to the target track information set; the control instruction set comprises a plurality of target control instructions; the target control instruction is used for indicating the adjustment control of the mechanical arm.
As one such optional implementation manner, in the second aspect of the embodiment of the present invention, the first determining module includes a first determining sub-module, a second determining sub-module, and a third determining sub-module, where:
the first determining submodule is used for determining gravity center coordinate information corresponding to the target object according to the target object image information;
the second determining submodule is used for determining initial attitude information of the mechanical arm according to the gravity coordinate information; the initial posture information of the mechanical arm is used for configuring the initial posture of the mechanical arm;
and the third determining submodule is used for determining a target track information set according to the initial attitude information of the mechanical arm and a preset track planning model.
As an alternative implementation manner, in the second aspect of the embodiment of the present invention, the specific manner of determining, by the first determining submodule, the barycentric coordinate information corresponding to the target object according to the target object image information is as follows:
processing the target object image information according to a preset target detection rule to obtain a target area;
processing the target area according to a preset feature extraction rule to obtain a pixel coordinate information set; the pixel coordinate information comprises at least 2 pixel coordinate information;
and calculating the pixel coordinate information set to obtain gravity center coordinate information corresponding to the target object.
As one such optional implementation, in the second aspect of the embodiment of the present invention, the initial posture information of the robot arm includes initial posture information of a camera and initial posture information of a joint angle;
the specific way for determining the initial posture information of the mechanical arm by the second determining submodule according to the gravity center coordinate information is as follows:
acquiring initial coordinate information and mechanical arm structure information of a mechanical arm;
calculating the gravity center coordinate information and the mechanical arm initial coordinate information to obtain the camera initial attitude information;
and calculating the initial attitude information of the camera and the structural information of the mechanical arm to obtain the initial attitude information of the joint angle.
As one such optional implementation, in the second aspect of the embodiment of the present invention, the trajectory planning model includes a first planning model and a second planning model;
the third determining submodule determines a target track information set according to the initial posture information of the mechanical arm and a preset track planning model in the following specific mode:
calculating the initial attitude information of the mechanical arm to obtain initial point information;
acquiring a target point information set; the target point information set comprises L pieces of target point information; l is a positive integer greater than or equal to 2;
calculating and processing initial point information and the target point information set by using the first planning model to obtain an initial track information set; the initial track information set comprises the L pieces of initial track information;
determining running time information according to the initial track information set;
and processing the running time information by using the second planning model to obtain a target track information set.
As an optional implementation manner, in a second aspect of the embodiment of the present invention, the specific manner of determining, by the second determining module, the control instruction set according to the target track information set is as follows:
determining a target control model set according to the target track information set; the target control model set comprises a plurality of target control models;
determining attitude position information according to the target object image information and a preset attitude analysis model;
and processing the attitude and position information by using the target control model set to obtain a control instruction set.
As a specific implementation manner of this optional implementation manner, in the second aspect of the embodiment of the present invention, the specific manner of determining, by the second determining module, the target control model set according to the target trajectory information set is as follows:
for any target track information, matching track characteristic information corresponding to the target track information with model characteristic information corresponding to all control models to be selected in a preset control model set to obtain a matching result; the track characteristic information comprises M track information elements; m is an odd positive integer; the model feature information comprises N model information elements; n is an odd positive integer; track element information corresponding to a track information element at the middle position in the track characteristic information is matched with track element information corresponding to a track information element at the last position; track element information corresponding to a track information element at a second position in sequence in the track characteristic information is matched with track element information corresponding to a track information element at the last position;
and when the matching result shows that target model characteristic information matched with the track characteristic information corresponding to the target track information exists in the control model set to be selected, determining the control model to be selected corresponding to the target model characteristic information as a target control model.
The invention discloses a data processing device based on a mechanical arm in a third aspect, which comprises:
a memory storing executable program code;
a processor coupled with the memory;
the processor calls the executable program code stored in the memory to execute part or all of the steps in the robot-based data processing method disclosed in the first aspect of the embodiments of the present invention.
In a fourth aspect of the present invention, a computer storage medium is disclosed, where the computer storage medium stores computer instructions, and when the computer instructions are called, the computer instructions are used to perform some or all of the steps in the data processing method based on a robot arm disclosed in the first aspect of the embodiments of the present invention.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
in the embodiment of the invention, the image information of a target object is obtained; determining a target track information set according to target object image information and a preset track planning rule; determining a control instruction set according to the target track information set; the control instruction set comprises a plurality of target control instructions; the target control instruction is used for instructing adjustment control of the robot arm. Therefore, the method and the device can determine the target track information from the target object image information by using the track planning rule, and then process the target track information to obtain the target control instruction for indicating the adjustment control of the mechanical arm, thereby being beneficial to realizing the smooth control of the mechanical arm and improving the control efficiency of the mechanical arm.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a data processing method based on a robot according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart diagram of another robot-based data processing method disclosed in the embodiments of the present invention;
FIG. 3 is a schematic structural diagram of a data processing apparatus based on a robot arm according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of another robot-based data processing apparatus according to an embodiment of the present disclosure;
FIG. 5 is a schematic structural diagram of another robot-based data processing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or apparatus that comprises a list of steps or elements is not limited to those listed but may alternatively include other steps or elements not listed or inherent to such process, method, product, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The invention discloses a data processing method and device based on a mechanical arm, which can determine target track information from target object image information by utilizing a track planning rule, and then process the target track information to obtain a target control instruction for indicating the adjustment control of the mechanical arm, thereby being beneficial to realizing the smooth control of the mechanical arm and improving the control efficiency of the mechanical arm. The following are detailed below.
Example one
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a data processing method based on a robot according to an embodiment of the present invention. The data processing method based on the robot arm depicted in fig. 1 is applied to a data processing system, such as a local server or a cloud server for data processing based on the robot arm, and the embodiment of the present invention is not limited thereto. As shown in fig. 1, the robot-arm-based data processing method may include the operations of:
101. and acquiring image information of the target object.
102. And determining a target track information set according to the target object image information and a preset track planning rule.
103. And determining a control instruction set according to the target track information set.
In an embodiment of the present invention, the control instruction set includes a plurality of target control instructions.
In an embodiment of the present invention, the target control instruction is used to instruct adjustment control of the robot arm.
Optionally, the target object image information includes a plurality of target object images.
Optionally, the target object image is acquired by a camera located at the end of the mechanical arm.
Optionally, the robot arm includes a plurality of control units.
Optionally, the number of the control units is consistent with the number of the target control commands.
Therefore, the data processing method based on the mechanical arm, which is described by the embodiment of the invention, can determine the target track information from the target object image information by using the track planning rule, and then process the target track information to obtain the target control instruction for instructing the adjustment and control of the mechanical arm, so that the smooth control of the mechanical arm can be realized, and the control efficiency of the mechanical arm can be improved.
In an optional embodiment, the determining, in the step 102, a target trajectory information set according to the target object image information and a preset trajectory planning rule includes:
according to the image information of the target object, determining gravity center coordinate information corresponding to the target object;
determining initial attitude information of the mechanical arm according to the gravity center coordinate information; the initial posture information of the mechanical arm is used for configuring the initial posture of the mechanical arm;
and determining a target track information set according to the initial attitude information of the mechanical arm and a preset track planning model.
Optionally, the barycentric coordinate information includes three coordinate position information of the barycenter corresponding to the target object.
Optionally, the initial posture information of the mechanical arm includes a plurality of initial position information.
Optionally, the number of the initial position information is consistent with the number corresponding to the control unit.
Therefore, the data processing method based on the mechanical arm can process the image information of the target object to obtain the barycentric coordinate information corresponding to the target object, then determine the initial posture information of the mechanical arm for configuring the initial posture of the mechanical arm, and determine the target track information through the track planning model, so that the smooth control of the mechanical arm is favorably realized, and the control efficiency of the mechanical arm is improved.
In another optional embodiment, the determining, according to the image information of the target object, barycentric coordinate information corresponding to the target object includes:
processing the image information of the target object according to a preset target detection rule to obtain a target area;
processing the target area according to a preset feature extraction rule to obtain a pixel coordinate information set; the pixel coordinate information includes at least 2 pixel coordinate information;
and calculating the pixel coordinate information set to obtain the gravity center coordinate information corresponding to the target object.
In this optional embodiment, as an optional implementation, the specific manner of processing the target image information according to the preset target detection rule to obtain the target area is as follows:
processing the image information of the target object according to a preset characteristic threshold value to obtain a binary image;
searching the binary image by using a preset search window frame and search step length information to determine a standby area and the number of standby characteristic points corresponding to the standby area;
judging whether the number of the standby characteristic points corresponding to the standby area is greater than or equal to a preset threshold value of the number of the characteristic points to obtain a threshold judgment result;
and when the threshold judgment result shows that the number of the standby characteristic points corresponding to the standby area is greater than or equal to the preset characteristic point number threshold, determining the standby area as the target area.
Optionally, the search step information is used to instruct the search window frame to move on the binary image.
In this optional embodiment, as another optional implementation, the specific way of processing the target region according to the preset feature extraction rule to obtain the pixel coordinate information set is as follows:
carrying out edge detection processing on the target area to obtain an edge image of the target object;
performing linear detection processing on the edge image of the target object to obtain linear section information;
and fitting the straight line segment information to obtain a pixel coordinate information set.
Optionally, the edge detection processing includes gaussian filtering processing, and/or gradient amplitude and direction calculation processing, and/or non-maximum suppression processing, and/or dual-threshold screening strong and weak edge processing, and/or boundary tracking processing, which is not limited in the embodiment of the present invention.
Optionally, the above-mentioned line detection processing is implemented based on Hough transform.
Therefore, the data processing method based on the mechanical arm, which is described by the embodiment of the invention, can be implemented by processing the image information of the target object by using the target detection rule to obtain the target area, determining the coordinate information of a plurality of pixels by using the feature extraction rule, and further determining the barycentric coordinate information corresponding to the target object, thereby providing an implementation path for determining the barycentric coordinate information, being beneficial to realizing the smooth control of the mechanical arm and improving the control efficiency of the mechanical arm.
In yet another optional embodiment, the initial pose information of the mechanical arm includes initial pose information of a camera and initial pose information of a joint angle;
the above-mentioned according to barycentric coordinate information, confirm the initial attitude information of arm, include:
acquiring initial coordinate information and mechanical arm structure information of a mechanical arm;
calculating and processing the gravity center coordinate information and the mechanical arm initial coordinate information to obtain initial camera attitude information;
and calculating the initial attitude information of the camera and the structural information of the mechanical arm to obtain the initial attitude information of the joint angle.
Optionally, the initial coordinate information of the mechanical arm includes a plurality of pieces of joint initial coordinate information and a plurality of pieces of basic position information.
Optionally, the number of pieces of joint initial coordinate information is greater than or equal to the number of pieces of control unit information.
Optionally, the basic position information includes pitch angle information between a camera at the end of the mechanical arm and the target object, and/or distance information between the camera at the end of the mechanical arm and the target object, which is not limited in the embodiment of the present invention.
Therefore, the data processing method based on the mechanical arm described in the embodiment of the invention can determine and obtain the initial attitude information of the camera through the calculation processing of the barycentric coordinate information and the initial coordinate information of the mechanical arm, and determine and obtain the initial attitude information of the joint angle by utilizing the structural information of the mechanical arm, so that the smooth control of the mechanical arm can be realized, and the control efficiency of the mechanical arm can be improved.
In yet another alternative embodiment, the trajectory planning model includes a first planning model and a second planning model;
the determining a target trajectory information set according to the initial posture information of the mechanical arm and the preset trajectory planning model includes:
calculating the initial attitude information of the mechanical arm to obtain initial point information;
acquiring a target point information set; the target point information set comprises L pieces of target point information; l is a positive integer greater than or equal to 2;
calculating and processing the initial point information and the target point information set by using a first planning model to obtain an initial track information set; the initial track information set comprises L pieces of initial track information;
determining running time information according to the initial track information set;
and processing the running time information by using a second planning model to obtain a target track information set.
In this optional embodiment, as an optional implementation manner, the specific manner of obtaining the initial trajectory information set by performing calculation processing on the initial point information and the target point information set by using the first planning model is as follows:
and for any two information points, carrying out track design on the two information points by using a first planning model to obtain initial track information corresponding to the two information points.
Optionally, the two information points include initial point information and target point information, or any two target point information, which is not limited in the embodiment of the present invention.
Preferably, the first programming model is a third-order B-spline interpolation-based programming model.
In this optional embodiment, as another optional implementation, the specific implementation manner of determining the running time information according to the initial trajectory information set is as follows:
for any initial track information, calculating initial time information corresponding to the initial track information;
and summing all the initial time information to obtain the running time information.
In this optional embodiment, as another optional implementation, the specific implementation manner of processing the runtime information by using the second planning model to obtain the target trajectory information set is as follows:
optimizing the initial track information set by using a second planning model to obtain a standby track information set; the track set comprises a plurality of standby track information sets;
determining a standby running time set according to the track set; the standby running time set comprises a plurality of pieces of standby running time information;
processing the standby running time set and the running time information according to a preset preferred termination condition to determine a target running time;
and determining the track information set corresponding to the target running time as a target track information set.
Optionally, the track information set includes a standby track information set or an initial track information set, which is not limited in the embodiment of the present invention.
Optionally, the target track information set includes a plurality of target track information.
Preferably, the second planning model is a planning model based on an improved genetic algorithm.
Optionally, the second planning model includes a binary-based chromosome code, and/or an initial population, and/or a selection operator, and/or a crossover operator, and/or a mutation operator, which is not limited in the embodiments of the present invention.
Optionally, the initial population is obtained by calculating the mean variance of the individual fitness and the global fitness, sorting the mean variances from small to large, and selecting the first K individuals.
Optionally, K is a positive integer.
Optionally, the crossover operator is determined based on the average distribution density and the fitness variance of the population.
Therefore, the data processing method based on the mechanical arm described in the embodiment of the invention can determine the target track information by processing the initial attitude information and the target point information of the mechanical arm, and is more favorable for realizing smooth control of the mechanical arm, thereby improving the control efficiency of the mechanical arm.
Example two
Referring to fig. 2, fig. 2 is a schematic flow chart illustrating another data processing method based on a robot according to an embodiment of the present disclosure. The data processing method based on the robot arm depicted in fig. 2 is applied to a data processing system, such as a local server or a cloud server for data processing based on the robot arm, and the embodiment of the present invention is not limited thereto. As shown in fig. 2, the robot-arm-based data processing method may include the operations of:
201. and acquiring image information of the target object.
202. And determining a target track information set according to the target object image information and a preset track planning rule.
In the embodiment of the present invention, for specific technical details and technical noun explanations of step 201 to step 202, reference may be made to the detailed description of step 101 to step 102 in the first embodiment, and details are not repeated in the embodiment of the present invention.
203. And determining a target control model set according to the target track information set.
In an embodiment of the present invention, the target control model set includes a plurality of target control models.
204. And determining attitude position information according to the image information of the target object and a preset attitude analysis model.
205. And processing the attitude and position information by using the target control model set to obtain a control instruction set.
Optionally, the posture analysis model includes an analysis model based on deep learning, and/or an analysis model based on a neural network, and/or an analysis model based on a jacobian matrix, which is not limited in the embodiment of the present invention.
Optionally, the attitude and position information includes displacement information, and/or angle information, and/or linear velocity information, and/or angular velocity information, and/or acceleration information, which is not limited in the embodiment of the present invention.
Optionally, the number corresponding to the target control model is consistent with the number corresponding to the target trajectory information.
Optionally, the target control model includes a fuzzy PID-based control model, and/or a synovial control algorithm-based control model, and/or a neural network-based control algorithm, and/or a state observer-based control model, and/or an impedance control algorithm-based control model, which is not limited in the embodiments of the present invention.
Therefore, the data processing method based on the mechanical arm, which is described in the embodiment of the invention, can determine the target track information from the target object image information by using the track planning rule, then process the target track information to obtain the target control model, process the target object image information by using the attitude analysis model to determine the attitude position information, and then process the attitude position information by using the target control model to obtain the target control instruction for instructing the adjustment and control of the mechanical arm, so that the smooth control of the mechanical arm is favorably realized, and the control efficiency of the mechanical arm is improved.
In an optional embodiment, the determining the target control model set according to the target trajectory information set in step 203 includes:
for any target track information, matching track characteristic information corresponding to the target track information with model characteristic information corresponding to all control models to be selected in a preset control model set to obtain a matching result; the track characteristic information comprises M track information elements; m is an odd positive integer; the model feature information comprises N model information elements; n is an odd positive integer; track element information corresponding to a track information element at the middle position in the track characteristic information is matched with track element information corresponding to a track information element at the last position; track element information corresponding to a track information element at a second position in the sequence in the track characteristic information is matched with track element information corresponding to a track information element at the last position;
and when the matching result indicates that target model characteristic information matched with the track characteristic information corresponding to the target track information exists in the control model set to be selected, determining the control model to be selected corresponding to the target model characteristic information as the target control model.
Optionally, the track characteristic information includes track number information, and/or track name information, and/or track priority information, which is not limited in the embodiment of the present invention.
Optionally, M is a positive integer greater than or equal to 7.
Optionally, M is an odd number.
Optionally, the track characteristic information is in the form of a1-a 2-A3-A3-a 2-b, where a1, a2, A3, a, and b are track element information corresponding to track information elements.
Alternatively, a consists of a1 and a 2. Further, a is in the form of A2-A1-A1-A2-A2.
Optionally, b is comprised of a2 and A3. Further, b is in the form of A2-A3-A3-A2-A2.
Optionally, a1 is track number information.
Optionally, a2 is track name information.
Optionally, a3 is track priority information.
Therefore, the data processing method based on the mechanical arm described in the embodiment of the invention can determine the target control model by matching the track characteristic information and the model characteristic information, provides an implementation path for determining the target control model, and is more beneficial to implementing smooth control on the mechanical arm, thereby improving the control efficiency of the mechanical arm.
EXAMPLE III
Referring to fig. 3, fig. 3 is a schematic structural diagram of a data processing apparatus based on a robot arm according to an embodiment of the present invention. The apparatus described in fig. 3 can be applied to a data processing system, such as a local server or a cloud server for robot-based data processing, and the embodiments of the present invention are not limited thereto.
As shown in fig. 3, the apparatus may include:
an obtaining module 301, configured to obtain image information of a target object;
a first determining module 302, configured to determine a target trajectory information set according to target object image information and a preset trajectory planning rule;
a second determining module 303, configured to determine a control instruction set according to the target trajectory information set; the control instruction set comprises a plurality of target control instructions; the target control instruction is used for instructing adjustment control of the robot arm.
It can be seen that, by implementing the data processing device based on the mechanical arm described in fig. 3, the target trajectory information can be determined from the target object image information by using the trajectory planning rule, and then the target trajectory information is processed to obtain a target control instruction for instructing adjustment and control of the mechanical arm, which is beneficial to smooth control of the mechanical arm, so that the control efficiency of the mechanical arm is improved.
In another alternative embodiment, as shown in fig. 4, the first determination module 302 includes a first determination submodule 3021, a second determination submodule 3022, and a third determination submodule 3023, wherein:
the first determining submodule 3021 is configured to determine, according to the image information of the target object, barycentric coordinate information corresponding to the target object;
the second determining submodule 3022 is configured to determine initial posture information of the mechanical arm according to the barycentric coordinate information; the initial posture information of the mechanical arm is used for configuring the initial posture of the mechanical arm;
the third determining submodule 3023 is configured to determine a target trajectory information set according to the initial posture information of the mechanical arm and a preset trajectory planning model.
It can be seen that, by implementing the data processing device based on the mechanical arm described in fig. 4, image information of the target object can be processed to obtain barycentric coordinate information corresponding to the target object, initial posture information of the mechanical arm for configuring an initial posture of the mechanical arm is determined, and target trajectory information is determined through a trajectory planning model, which is beneficial to smooth control of the mechanical arm, so that control efficiency of the mechanical arm is improved.
In yet another alternative embodiment, as shown in fig. 4, the specific way of determining the barycentric coordinate information corresponding to the target object by the first determining submodule 3021 according to the image information of the target object is as follows:
processing the image information of the target object according to a preset target detection rule to obtain a target area;
processing the target area according to a preset feature extraction rule to obtain a pixel coordinate information set; the pixel coordinate information includes at least 2 pixel coordinate information;
and calculating the pixel coordinate information set to obtain the gravity center coordinate information corresponding to the target object.
It can be seen that, by implementing the data processing device based on the mechanical arm described in fig. 4, the target detection rule can be utilized to process the image information of the target object to obtain the target area, and then the feature extraction rule is utilized to determine the coordinate information of a plurality of pixels, so as to determine and obtain the barycentric coordinate information corresponding to the target object, thereby providing an implementation path for determining the barycentric coordinate information, facilitating the realization of smooth control over the mechanical arm, and improving the control efficiency of the mechanical arm.
In yet another alternative embodiment, as shown in fig. 4, the robot arm initial pose information includes camera initial pose information and joint angle initial pose information;
the specific way of determining the initial posture information of the mechanical arm by the second determining submodule 3022 according to the barycentric coordinate information is as follows:
acquiring initial coordinate information and mechanical arm structure information of a mechanical arm;
calculating and processing the gravity center coordinate information and the mechanical arm initial coordinate information to obtain initial camera attitude information;
and calculating the initial attitude information of the camera and the structural information of the mechanical arm to obtain the initial attitude information of the joint angle.
It can be seen that, by implementing the data processing device based on the mechanical arm described in fig. 4, the initial attitude information of the camera can be determined and obtained through calculation processing of the barycentric coordinate information and the initial coordinate information of the mechanical arm, and the initial attitude information of the joint angle can be determined and obtained by using the structural information of the mechanical arm, which is more beneficial to realizing smooth control of the mechanical arm, thereby improving the control efficiency of the mechanical arm.
In yet another alternative embodiment, as shown in FIG. 4, the trajectory planning model includes a first planning model and a second planning model;
the third determining submodule 3023 determines, according to the initial posture information of the mechanical arm and the preset trajectory planning model, a specific manner of the target trajectory information set is as follows:
calculating the initial attitude information of the mechanical arm to obtain initial point information;
acquiring a target point information set; the target point information set comprises L pieces of target point information; l is a positive integer greater than or equal to 2;
calculating and processing the initial point information and the target point information set by using a first planning model to obtain an initial track information set; the initial track information set comprises L pieces of initial track information;
determining running time information according to the initial track information set;
and processing the running time information by using a second planning model to obtain a target track information set.
Therefore, by implementing the data processing device based on the mechanical arm described in fig. 4, the target track information can be determined by processing the initial posture information and the target point information of the mechanical arm, which is more beneficial to realizing smooth control of the mechanical arm, thereby improving the control efficiency of the mechanical arm.
In yet another alternative embodiment, as shown in fig. 4, the specific way for the second determining module 303 to determine the control instruction set according to the target track information set is as follows:
determining a target control model set according to the target track information set; the target control model set comprises a plurality of target control models;
determining attitude position information according to the image information of the target object and a preset attitude analysis model;
and processing the attitude and position information by using the target control model set to obtain a control instruction set.
It can be seen that, by implementing the data processing device based on the mechanical arm described in fig. 4, the target trajectory information can be determined from the target object image information by using the trajectory planning rule, then the target trajectory information is processed to obtain the target control model, the target object image information is processed by using the attitude analysis model to determine the attitude position information, and then the attitude position information is processed by using the target control model to obtain the target control instruction for instructing to adjust and control the mechanical arm, which is beneficial to realizing the smooth control of the mechanical arm, thereby improving the control efficiency of the mechanical arm.
In yet another alternative embodiment, as shown in fig. 4, the specific way for the second determining module 303 to determine the target control model set according to the target trajectory information set is as follows:
for any target track information, matching track characteristic information corresponding to the target track information with model characteristic information corresponding to all control models to be selected in a preset control model set to obtain a matching result; the track characteristic information comprises M track information elements; m is an odd positive integer; the model feature information comprises N model information elements; n is an odd positive integer; track element information corresponding to a track information element at the middle position in the track characteristic information is matched with track element information corresponding to a track information element at the last position; track element information corresponding to a track information element at a second position in the sequence in the track characteristic information is matched with track element information corresponding to a track information element at the last position;
and when the matching result indicates that target model characteristic information matched with the track characteristic information corresponding to the target track information exists in the control model set to be selected, determining the control model to be selected corresponding to the target model characteristic information as the target control model.
It can be seen that, by implementing the data processing device based on the robot arm described in fig. 4, the target control model can be determined by matching the trajectory characteristic information and the model characteristic information, and an implementation path for determining the target control model is provided, which is more beneficial to implementing smooth control on the robot arm, thereby improving the control efficiency of the robot arm.
Example four
Referring to fig. 5, fig. 5 is a schematic structural diagram of another robot-based data processing apparatus according to an embodiment of the present disclosure. The apparatus depicted in fig. 5 can be applied to a data processing system, such as a local server or a cloud server for robot-based data processing, and the embodiments of the present invention are not limited thereto. As shown in fig. 5, the apparatus may include:
a memory 401 storing executable program code;
a processor 402 coupled with the memory 401;
the processor 402 invokes executable program code stored in the memory 401 for performing the steps in the robot arm-based data processing method described in embodiment one or embodiment two.
EXAMPLE five
The embodiment of the invention discloses a computer-readable storage medium which stores a computer program for electronic data exchange, wherein the computer program enables a computer to execute the steps in the data processing method based on the mechanical arm described in the first embodiment or the second embodiment.
EXAMPLE six
An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute the steps in the robot arm-based data processing method described in the first or second embodiment.
The above-described embodiments of the apparatus are merely illustrative, and the modules described as separate parts may or may not be physically separate, and the parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above detailed description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. Based on such understanding, the above technical solutions may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, where the storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc-Read-Only Memory (CD-ROM), or other disk memories, CD-ROMs, or other magnetic disks, A tape memory, or any other medium readable by a computer that can be used to carry or store data.
Finally, it should be noted that: the data processing method and apparatus based on a robot disclosed in the embodiments of the present invention are only disclosed as preferred embodiments of the present invention, which are only used for illustrating the technical solutions of the present invention, and are not limited thereto; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for robotic-arm-based data processing, the method comprising:
acquiring image information of a target object;
determining a target track information set according to the target object image information and a preset track planning rule;
determining a control instruction set according to the target track information set; the control instruction set comprises a plurality of target control instructions; the target control instruction is used for indicating the adjustment control of the mechanical arm.
2. The data processing method based on the mechanical arm according to claim 1, wherein the determining a target trajectory information set according to the target object image information and a preset trajectory planning rule comprises:
according to the image information of the target object, determining gravity center coordinate information corresponding to the target object;
determining initial attitude information of the mechanical arm according to the gravity center coordinate information; the initial posture information of the mechanical arm is used for configuring the initial posture of the mechanical arm;
and determining a target track information set according to the initial attitude information of the mechanical arm and a preset track planning model.
3. The data processing method based on the mechanical arm as claimed in claim 2, wherein the determining of the barycentric coordinate information corresponding to the target object according to the target object image information comprises:
processing the target object image information according to a preset target detection rule to obtain a target area;
processing the target area according to a preset feature extraction rule to obtain a pixel coordinate information set; the pixel coordinate information comprises at least 2 pixel coordinate information;
and calculating the pixel coordinate information set to obtain gravity center coordinate information corresponding to the target object.
4. The robot arm-based data processing method of claim 2, wherein the robot arm initial posture information includes camera initial posture information and joint angle initial posture information;
according to the gravity center coordinate information, determining initial attitude information of the mechanical arm, including:
acquiring initial coordinate information and mechanical arm structure information of a mechanical arm;
calculating the gravity center coordinate information and the mechanical arm initial coordinate information to obtain the camera initial attitude information;
and calculating the initial attitude information of the camera and the structural information of the mechanical arm to obtain the initial attitude information of the joint angle.
5. The robotic arm-based data processing method of claim 2, wherein the trajectory planning model comprises a first planning model and a second planning model;
determining a target track information set according to the mechanical arm initial attitude information and a preset track planning model, wherein the determining comprises the following steps:
calculating the initial attitude information of the mechanical arm to obtain initial point information;
acquiring a target point information set; the target point information set comprises L pieces of target point information; l is a positive integer greater than or equal to 2;
calculating and processing initial point information and the target point information set by using the first planning model to obtain an initial track information set; the initial track information set comprises the L pieces of initial track information;
determining running time information according to the initial track information set;
and processing the running time information by using the second planning model to obtain a target track information set.
6. The method for processing data based on a mechanical arm according to claim 1, wherein the determining a set of control instructions according to the set of target trajectory information comprises:
determining a target control model set according to the target track information set; the target control model set comprises a plurality of target control models;
determining attitude position information according to the target object image information and a preset attitude analysis model;
and processing the attitude and position information by using the target control model set to obtain a control instruction set.
7. The robotic arm-based data processing method of claim 6, wherein said determining a set of target control models from said set of target trajectory information comprises:
for any target track information, matching track characteristic information corresponding to the target track information with model characteristic information corresponding to all control models to be selected in a preset control model set to obtain a matching result; the track characteristic information comprises M track information elements; m is an odd positive integer; the model feature information comprises N model information elements; n is an odd positive integer; track element information corresponding to a track information element at the middle position in the track characteristic information is matched with track element information corresponding to a track information element at the last position; track element information corresponding to a track information element at a second position in sequence in the track characteristic information is matched with track element information corresponding to a track information element at the last position;
and when the matching result shows that target model characteristic information matched with the track characteristic information corresponding to the target track information exists in the control model set to be selected, determining the control model to be selected corresponding to the target model characteristic information as a target control model.
8. A robotic arm based data processing apparatus, the apparatus comprising:
the acquisition module is used for acquiring image information of a target object;
the first determining module is used for determining a target track information set according to the target object image information and a preset track planning rule;
the second determining module is used for determining a control instruction set according to the target track information set; the control instruction set comprises a plurality of target control instructions; the target control instruction is used for indicating the adjustment control of the mechanical arm.
9. A robotic arm based data processing apparatus, the apparatus comprising:
a memory storing executable program code;
a processor coupled with the memory;
the processor invokes the executable program code stored in the memory to perform the robotic arm-based data processing method of any of claims 1-7.
10. A computer-storable medium that stores computer instructions that, when invoked, perform a robotic arm based data processing method according to any of claims 1-7.
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