CN114347032B - Control method and system of composite AGV robot - Google Patents
Control method and system of composite AGV robot Download PDFInfo
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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
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- B25J9/1605—Simulation of manipulator lay-out, design, modelling of manipulator
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J5/00—Manipulators mounted on wheels or on carriages
- B25J5/007—Manipulators mounted on wheels or on carriages mounted on wheels
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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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- 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
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- 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
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Abstract
The invention discloses a control method and a system of a composite AGV robot, wherein the method comprises the following steps: acquiring first operation material information of a first composite robot according to a first intelligent detection device; obtaining a loading composite detection model; inputting the first operation material information into the loading composite detection model to generate first loading detection data; acquiring a first driving data set by acquiring path data and detection data of a first preset guiding planning path, wherein the first driving data set comprises a first path data set and a first detection data set; and performing secondary planning on the first driving data set based on the first loading detection data to obtain a second driving data set, and controlling the first composite robot. The technical problems that in the prior art, when an AGV composite robot is in operation control, due to the fact that functional units are more, adaptive cooperative control is weak along with material change, and the intelligent degree is low are solved.
Description
Technical Field
The invention relates to the field of intelligent control, in particular to a control method and a system for a composite AGV robot.
Background
AGVs are automatic guided vehicles, and based on the continuous development of intelligent technology and the improvement of manufacturing requirements in factories in recent years, the use performance of AGVs in complex environments is continuously studied as an indispensable transportation device. Compared with a single-function robot, the AGV composite robot is better suitable for complex environments of different production lines in the logistics industry, and is multifunctional in automatic factory such as data management, storage sorting and automatic carrying, and the requirements of the industry are better met.
However, in the prior art, when the AGV composite robot is in operation control, due to the fact that the functional units are more, the adaptive cooperative control is weak along with the change of materials, and the intelligent degree is low.
Disclosure of Invention
Aiming at the defects in the prior art, the embodiment of the application aims to solve the technical problems that the adaptive cooperative control is weak along with the change of materials and the intelligent degree is low because of more functional units when the AGV composite robot is in operation control in the prior art by providing the control method and the control system of the composite AGV robot, and achieves the technical effects that the characteristic analysis and the detection of the materials are carried out through the composite detection model, the driving data is optimized aiming at the cooperative loading detection result output by the composite detection model, and the intelligent control is realized.
In one aspect, an embodiment of the present application provides a method for controlling a composite AGV robot, where the method is applied to a control system of the composite AGV robot, and the system is communicatively connected to a first intelligent detection device, and the method includes: acquiring first operation material information of a first composite robot according to the first intelligent detection device, wherein the first operation material information comprises material attribute information and material geometric information; obtaining a loading composite detection model according to the first composite robot; inputting the first operation material information into the loading composite detection model, and obtaining first output information according to the loading composite detection model; generating first loading detection data according to the first output information; acquiring path data and detection data of a first preset guide planning path to obtain a first driving data set, wherein the first driving data set comprises a first path data set and a first detection data set, and the first path data set and the first detection data set are distributed in a time sequence and are in one-to-one correspondence; performing secondary planning on the first driving data set based on the first loading detection data to obtain a second driving data set; and controlling the first composite robot according to the second driving data set.
On the other hand, the application also provides a control system of the composite AGV robot, which comprises: the first obtaining unit is used for obtaining first operation material information of the first composite robot according to the first intelligent detection device, wherein the first operation material information comprises material attribute information and material geometric information; the second obtaining unit is used for obtaining a loading composite detection model according to the first composite robot; the first input unit is used for inputting the first operation material information into the loading composite detection model, and obtaining first output information according to the loading composite detection model; the first generation unit is used for generating first loading detection data according to the first output information; the third obtaining unit is used for obtaining a first driving data set by collecting path data and detection data of a first preset guide planning path, wherein the first driving data set comprises a first path data set and a first detection data set, and the first path data set and the first detection data set are distributed in a time sequence and are in one-to-one correspondence; a fourth obtaining unit configured to perform quadratic programming on the first driving data set based on the first loading detection data, to obtain a second driving data set; and the first control unit is used for controlling the first composite robot according to the second driving data set.
In a third aspect, an embodiment of the present application provides a control system for a composite AGV robot, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method of any one of the first aspects when executing the program.
One or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
the method comprises the steps of analyzing geometric information and material attribute information of a first composite robot according to a first intelligent detection device to obtain first operation material information, constructing a loading composite detection model according to equipment information of the first composite robot, inputting the operation material information obtained through detection into the loading composite model, outputting composite detection results according to the loading composite detection model to generate first loading detection data, further, analyzing paths and detection areas based on a historical preset path plan to obtain a first driving data set of the first composite robot, planning the first driving according to the first loading detection data to obtain a second driving data set, and controlling the first composite robot based on the second driving data set.
The foregoing description is only an overview of the present application, and is intended to be implemented in accordance with the teachings of the present application in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present application more readily apparent.
Drawings
Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of a method for controlling a composite AGV robot according to an embodiment of the application;
FIG. 2 is a schematic flow chart of a method for controlling a composite AGV robot to obtain a loading composite detection model according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of a method for controlling a composite AGV robot to obtain a third driving data set according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a control system of a composite AGV robot according to an embodiment of the application;
fig. 5 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Detailed Description
The embodiment of the application solves the technical problems of weak adaptive cooperative control and low intelligent degree along with the change of materials in the operation control of the AGV composite robot in the prior art by providing the control method and the control system of the composite AGV robot, and achieves the technical effects of analyzing and detecting the characteristics of the materials through the composite detection model, optimizing driving data aiming at the cooperative loading detection result output by the composite detection model, and further realizing intelligent control.
Hereinafter, exemplary embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are only some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited by the example embodiments described herein.
Summary of the application
The compound robot can replace manual work to safely finish dangerous operation under severe environment, improves the labor condition of workers, thereby avoiding negligence and loss caused by manual operation fatigue, and the functional units are more based on the compound robot when in actual use control, so that the compound robot can be rapidly adapted to more complex working environments. However, for different characteristics of materials, the cooperative processing of functional units is not accurate enough, and the adaptation degree of the change of the attribute of the materials is weak, so that the composite AGV robot can be assembled and carried for outputting interactive information according to the characteristics of the materials by using the control method of the composite AGV robot, and the pertinence and the intelligence of control are improved.
Aiming at the technical problems, the technical scheme provided by the application has the following overall thought:
the application provides a control method and a system of a composite AGV robot, wherein the method comprises the following steps: according to the method, geometrical information and material attribute information of a first composite robot are analyzed according to a first intelligent detection device connected in a system communication mode to obtain first operation material information, a loading composite detection model is built according to equipment information of the first composite robot, the operation material information obtained through detection is input into the loading composite model, composite detection results are output according to the loading composite detection model, first loading detection data are generated, further, analysis of paths and detection areas is conducted on the basis of historical preset path planning, a first driving data set of the first composite robot is obtained, the first driving planning is conducted according to the first loading detection data, a second driving data set is obtained, and the first composite robot is controlled on the basis of the second driving data set.
In order to better understand the above technical solutions, the following detailed description will refer to the accompanying drawings and specific embodiments.
Example 1
As shown in fig. 1, an embodiment of the present application provides a control method of a composite AGV robot, where the method is applied to a control system of the composite AGV robot, and the system is communicatively connected to a first data acquisition device, and the method includes:
step S100: acquiring first operation material information of a first composite robot according to the first intelligent detection device, wherein the first operation material information comprises material attribute information and material geometric information;
specifically, the first intelligent detection device is a device formed by a machine vision detection unit, a data processing unit and a data transmission unit, the machine vision detection unit is used for collecting images of the working materials of the composite robot, and the data processing unit is used for carrying out feature recognition analysis on the collected images, so that recognition analysis data are transmitted to the system according to the data transmission unit. The first composite robot is a composite robot controlled in real time, and the type and model of the first composite robot are different, and the data controlled by the central control processor of the first composite robot are different.
Further, based on the first operation material information obtained by the first intelligent detection device, material attribute identification and material geometric data identification are performed, namely, the material attribute is identified, so that the first composite robot can conveniently position the mechanical arm and set parameters of the material; the loading of the first compound robot can be identified by identifying the geometric data, so that the loading can be accurately controlled.
Step S200: obtaining a loading composite detection model according to the first composite robot;
further, as shown in fig. 2, according to the first composite robot, a loading composite detection model is obtained, and step S200 of the embodiment of the present application further includes:
step S210: acquiring first mechanical arm operation information according to the first composite robot;
step S220: training a data model according to the first mechanical arm operation information to obtain a first mechanical arm control model, wherein the first mechanical arm control model is obtained by training a training material characteristic set and a mechanical arm control parameter set until convergence;
step S230: obtaining a first carrying and loading detection model;
step S240: and connecting the first carrying loading detection model based on the first mechanical arm control model, and constructing the loading composite detection model, wherein the first mechanical arm control model and the first carrying loading detection model realize data interaction.
Specifically, by performing equipment analysis on the first composite robot, a cooperative mechanical arm and a cooperative work table are determined, and further model training is performed according to loading and bearing operations of the cooperative mechanical arm and the cooperative work table, so that the loading composite model is obtained. The loading composite model comprises a first mechanical arm control model and a first carrying loading detection model, and information interaction between the first mechanical arm control model and the first carrying loading detection model is realized.
Through carrying out data acquisition to the arm operation of first combined robot to history operation material characteristic and control parameter, because combined robot disposes the control parameter of arm according to the information of material parcel when logistics trade carries out logistics sorting, consequently, carry out multiunit data study as training data set based on history material characteristic set and arm control parameter set in the history operation data, thereby can carry out the training of logic model according to double-deck data set, the output can be according to material attribute and the model of geometrical information just arm self-adaptation control, first arm control model can improve the discernment accuracy based on mathematical model.
The first carrying and loading detection model is used for carrying out data acquisition and analysis according to the bearing of the first composite robot, carrying out data migration based on the data identified in the first mechanical arm control model, and realizing the bearing identification of the robot according to migration data, such as space data, quality data and the like of a bearing object. The method achieves construction of a composite model based on data interaction between the first mechanical arm control model and the first carrying loading detection model, and improves model identification efficiency.
Step S300: inputting the first operation material information into the loading composite detection model, and obtaining first output information according to the loading composite detection model;
step S400: generating first loading detection data according to the first output information;
specifically, the first operation material information is input into the loading composite detection model, and because the loading composite detection model is obtained through data interaction of two data models, and the control task of the first composite robot has priority, the loading composite detection model is compared with the priority, the first operation material information is input into the first mechanical arm control model, and the mechanical control model can recognize mechanical arm control data according to the material characteristics input in real time, so that output data such as positioning data, moment data, displacement data and the like are obtained. Further, the execution state of the data output by the first mechanical arm control model is used as a trigger to perform carrying material updating detection on the first carrying loading detection model, so that first output information output by the first carrying loading detection model is obtained, wherein the first output information is information output by the loading composite detection model, the first loading detection data is generated, namely, the first composite robot mechanical arm is operated, the detection data of the operation platform are cooperated, and the effective operation control for materials is further realized according to the fact that the first carrying detection data is data after space division based on the three-dimensional space structure of the first composite robot.
Step S500: acquiring path data and detection data of a first preset guide planning path to obtain a first driving data set, wherein the first driving data set comprises a first path data set and a first detection data set, and the first path data set and the first detection data set are distributed in a time sequence and are in one-to-one correspondence;
specifically, the first preset guiding planning path is a loading and carrying path based on a working line of a logistics factory, and the robots are prevented from colliding in the carrying process due to path planning and route setting of the multiple combined robots in the executing process. The first path data set is preset path data of the first storage robot in the process of positioning automatic guiding operation, and is data ensuring no deviation of the direction, such as displacement, front wheel and rear wheel steering, weighing and speed shifting and the like; the first detection data set is based on the distribution condition of detection areas of the sensing device, such as the size, the area, the angle and the like of the warning area and the reminding area distribution area, in the carrying path of the first composite robot, so that safe operation and obstacle avoidance identification can be effectively ensured.
By collecting the path data and the detection data of the first preset guiding planning path, the identification points in the preset guiding path can be analyzed, the route and the operation function module are positioned, the planning of the original driving data of the first composite robot is realized, and therefore driving adaptability adjustment can be realized according to different bearing material characteristics.
Step S600: performing secondary planning on the first driving data set based on the first loading detection data to obtain a second driving data set;
step S700: and controlling the first composite robot according to the second driving data set.
Specifically, the first loading detection data is the data output by the loading composite detection model, so that the accuracy and the instantaneity are higher; the first driving data set is an original driving data set of the first composite robot; and performing secondary planning on the first driving data set based on the first loading detection data so as to obtain the second driving data set, for example, taking the result space overflow geometric data of the first loading detection data as an example, performing secondary planning on the detection distribution area data in the first driving data set, and preventing faults caused by composite robot handling. And then the first composite robot is controlled according to the second driving data set, so that the material characteristic analysis and detection are realized through the composite detection model, driving data are optimized aiming at the collaborative loading detection result output by the composite detection model, and the technical effect of intelligent control is realized.
Further, the step S230 of the embodiment of the present application further includes:
step S231: acquiring first bearing space data of the first composite robot;
step S232: constructing a three-dimensional space model based on the first bearing space data, wherein the three-dimensional space model is used for carrying out bearing space detection on the first composite robot;
step S233: and obtaining the first carrying loading detection model based on the three-dimensional space model.
Specifically, the process of constructing the first handling loading detection model is as follows:
the model analysis is carried out on the first composite robot, the three-dimensional space model construction is carried out by taking the bearing table of the first composite robot as a plane, namely, space data is constructed in three-dimensional space by taking side data of the bearing table of the first composite robot as a basis, so as to obtain a three-dimensional space model, and since the collision detection of the first composite robot takes initial collision as a premise in operation, the analysis of the bearing space data is carried out on the first composite robot according to the three-dimensional space model, and the comparison is carried out on the basis of the three-dimensional space model constructed by the first composite robot and the real-time bearing space detection, so as to construct the first carrying loading detection model which can carry out loading space overflow detection according to real-time input data, so as to output the first loading detection data
Further, according to the output information of the first carrying and loading detection model, the carrying space data of the robot are determined, and the operation of the first mechanical arm control model is stopped and restrained by judging the carrying weight limit of the first composite robot, so that the data interaction and accurate identification of the first carrying and loading detection model and the first mechanical arm control model are achieved.
Further, the step S300 of the embodiment of the present application further includes inputting the first operation material information into the loading composite detection model, and obtaining first output information according to the loading composite detection model:
step S310: inputting the first operation material information into the loading composite detection model, and obtaining a first loading and unloading control parameter according to the first mechanical arm control model in the loading composite detection model;
step S320: executing material loading operation according to the first loading and unloading control parameters to obtain first loading output information;
step S330: and inputting the first loading output information into the first carrying loading detection model for space analysis to obtain the first loading detection data.
Specifically, the first operation material information is input into the loading composite detection model, and the mechanical arm control data is identified for the material characteristics input in real time according to the first mechanical arm control model of the loading composite detection model, so that the first loading and unloading control parameters, such as positioning data, moment data, displacement data and the like, are obtained. Further, the first loading and unloading control parameter output by the first mechanical arm control model is used as a trigger to perform carrying material updating detection on the first carrying and loading detection model, so that first output information output by the first carrying and loading detection model is obtained, wherein the first output information is information output by the loading composite detection model, first loading detection data is generated, namely, the first composite mechanical arm is operated, the first loading detection data is cooperated with detection data of a bearing operation table, according to comparison data results after space overflow detection is performed on the basis of a three-dimensional space structure of the first composite mechanical arm, for example, a simulated three-dimensional space constructed by a platform is overflowed due to material geometric characteristics during space bearing, so that path and detection area secondary planning is performed through overflow output, and therefore, based on model information interaction, the first loading detection data is output as a later data updating condition, and the operation safety is improved.
Further, after the second driving data set is obtained by performing the quadratic programming on the first driving data set based on the first loading detection data set, step S600 of the embodiment of the present application further includes:
step S610a: generating first safety auxiliary data according to the second driving data group;
step S620a: according to a first connection instruction, connecting a safety auxiliary module of the first composite robot;
step S630a: obtaining a configuration auxiliary partition of the security auxiliary module;
step S640a: and updating data of the configuration auxiliary partition of the safety auxiliary module of the first composite robot according to the first safety auxiliary data.
Specifically, the second driving data set is optimized data obtained after the first driving data set is subjected to secondary planning based on first loading detection data, and the optimized data comprises a second path data set and a second detection data set; the first safety auxiliary data are corresponding early warning adjustment data generated according to the optimized second driving data set; the safety auxiliary module is a module for preventing the robot from faults or the police, the police and the emergency stop of personnel passing through in the composite robot.
After the path of the second driving data set is optimized and the detection area is optimized, the early warning module of the first composite robot is subjected to adaptive adjustment, so that the first composite robot can adaptively adjust early warning data of the first composite robot during operation, and an adaptive result is achieved. Therefore, all the configuration auxiliary partitions of the safety auxiliary module are determined, analysis and marking are carried out on the correlation between each partition and the material bearing, so that the relevant auxiliary partition is determined as an adjustment basis, and then the marked partition of the first composite robot in the safety auxiliary module is adaptively updated according to the first safety auxiliary data, so that the adjustment by the adaptation module is realized, and the operation safety early warning is ensured to be accurately controlled.
Further, step S600 of the embodiment of the present application further includes S650:
step S651: when the first composite robot triggers the early warning information, receiving the first early warning information;
step S652: determining a first safety auxiliary partition according to the first early warning information;
step S653: judging whether to trigger a first switching feature based on the first security auxiliary partition;
step S654: and if the first switching feature is triggered, switching the first replacing robot to execute the transferring operation according to the first switching instruction.
Specifically, when the first composite robot triggers the early warning information, the working state of the first composite robot is in an abnormal state, and in order to ensure normal operation of the assembly line, the first replacement robot is used for carrying out transfer operation on the first composite robot by adopting a trigger switching instruction.
The first early warning information is an early warning signal triggered by the first composite robot; the first safety auxiliary partition is an early warning block corresponding to the first early warning information after analysis, so that block positioning is performed according to the first early warning information, and fault content is determined; the first switching feature is a switching feature preset in advance, for example, the operation time for recovering the fault content to be normal is longer or the early warning is complex, if the first safety auxiliary partition triggers the first switching feature, the transfer operation is performed. And if the first switching feature is not triggered by the safety auxiliary partition, acquiring a first adjustment prompt for self-control adjustment.
When the first safety auxiliary partition triggers the switching feature, namely the marked partition, the switching condition is met, standby state inquiry is conducted based on a first inquiry command, adaptive robot screening is conducted according to the material feature, for example, robots of different types are allocated to conduct data file migration, so that transfer operation is conducted on the first replacement robot, further the second driving data set can be migrated, transfer configuration is conducted on the first replacement robot, operation flexibility is improved, and efficiency and automation are guaranteed.
Further, as shown in fig. 3, step S600 of the embodiment of the present application further includes:
step S610b: obtaining a first planning change degree according to the first loading detection data, wherein the first planning degree is the change complexity of quadratic programming;
step S620b: analyzing the guide path change nodes of the first composite robot according to the first planning change degree to determine multiple types of path nodes;
step S630b: dividing detection areas of the first composite robot in various path nodes according to the multi-class path nodes to generate multi-class node detection areas;
step S640b: and optimizing the second driving data set according to the multi-class node detection areas to obtain a third driving data set.
Specifically, a second planning change complexity analysis is performed on the first loading detection data to obtain a first planning change degree, wherein the change complexity analysis can determine the first planning change degree in a multi-dimensional manner through a data planning association quantity, a data change threshold value and computer calculation complexity. The multi-type path nodes are main change nodes when the multi-type path nodes are guiding paths, and comprise deceleration nodes, acceleration nodes, turning nodes and the like, and are classified based on different path nodes, such as speed change nodes, turning change nodes, stopping operation nodes and the like, so that detection areas of the first composite robot can be classified according to different types of path nodes, detection data in the second driving data set are optimized according to multi-type node detection areas generated after the classification, the third driving data set is obtained, and control accuracy of the composite robot in operation is improved.
Further, each type of division of the multiple types of node detection areas is different, for example, when the acceleration node and the deceleration node are changed linearly, the coverage area and the coverage layer of the detection areas are optimized, so that the robot collision caused by the speed change is prevented; or the radius, the angle increase and the like of the detection area of the steering node are optimized, so that the control accuracy of the composite robot in anti-collision and safety is further improved.
Compared with the prior art, the invention has the following beneficial effects:
1. the method comprises the steps of analyzing geometric information and material attribute information of a first composite robot according to a first intelligent detection device to obtain first operation material information, constructing a loading composite detection model according to equipment information of the first composite robot, inputting the operation material information obtained through detection into the loading composite model, outputting composite detection results according to the loading composite detection model to generate first loading detection data, further, analyzing paths and detection areas based on a historical preset path plan to obtain a first driving data set of the first composite robot, planning the first driving according to the first loading detection data to obtain a second driving data set, and controlling the first composite robot based on the second driving data set.
2. The first intersection recommended information is output as the first level in the first recommended information by adopting the hot compress feature extraction and the hot compress part intersection calculation according to the two dimensions of life and work of a user, so that the layering of the output of the first recommended information is improved, and effective information is provided for user interaction decision.
2. And the method adopts analysis and marking aiming at the relevance between each partition and the material bearing, thereby determining the relevant auxiliary partition as an adjustment basis, and realizing the adaptive updating of the marked partition of the first composite robot in the safety auxiliary module according to the first safety auxiliary data, so that the adjustment by the adaptive module is realized, and the operation safety early warning accurate control is ensured.
Example two
Based on the same inventive concept as the control method of the composite AGV robot in the foregoing embodiment, the present invention further provides a control system of the composite AGV robot, as shown in FIG. 4, where the system includes:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain first operation material information of a first composite robot according to a first intelligent detection device, where the first operation material information includes material attribute information and material geometry information;
A second obtaining unit 12, where the second obtaining unit 12 is configured to obtain a loading composite detection model according to the first composite robot;
a first input unit 13, where the first input unit 13 is configured to input the first working material information into the loading composite detection model, and obtain first output information according to the loading composite detection model;
a first generating unit 14, where the first generating unit 14 is configured to generate first loading detection data according to the first output information;
a third obtaining unit 15, where the third obtaining unit 15 is configured to obtain a first driving data set by collecting path data and probe data of a first preset guiding planned path, where the first driving data set includes a first path data set and a first probe data set, and the first path data set and the first probe data set are distributed in a time sequence and are in a one-to-one correspondence;
a fourth obtaining unit 16, where the fourth obtaining unit 16 is configured to perform quadratic programming on the first driving data set based on the first loading detection data to obtain a second driving data set;
a first control unit 17, wherein the first control unit 17 is configured to control the first compound robot according to the second driving data set.
Further, the system further comprises:
a fifth obtaining unit, configured to obtain first mechanical arm operation information according to the first composite robot;
the sixth obtaining unit is used for training a data model according to the first mechanical arm operation information to obtain a first mechanical arm control model, wherein the first mechanical arm control model is obtained by training a training material characteristic set and a mechanical arm control parameter set until convergence;
a seventh obtaining unit for obtaining a first handling loading detection model;
the first construction unit is used for connecting the first carrying loading detection model based on the first mechanical arm control model and constructing the loading composite detection model, wherein the first mechanical arm control model and the first carrying loading detection model realize data interaction.
Further, the system further comprises:
an eighth obtaining unit, configured to obtain first bearing space data of the first composite robot;
the second construction unit is used for constructing a three-dimensional space model based on the first bearing space data, wherein the three-dimensional space model is used for carrying out bearing space detection on the first composite robot;
A ninth obtaining unit configured to obtain the first conveyance loading detection model based on the three-dimensional space model.
Further, the system further comprises:
a tenth obtaining unit, configured to input the first working material information into the loading composite detection model, and obtain a first loading and unloading control parameter according to the first mechanical arm control model in the loading composite detection model;
an eleventh obtaining unit configured to obtain first loading output information based on performing a material loading operation according to the first loading and unloading control parameter;
a twelfth obtaining unit, configured to obtain a first migration node according to the first data analysis result;
and the second input unit is used for inputting the first loading output information into the first carrying loading detection model for space analysis to obtain the first loading detection data.
Further, the system further comprises:
a second generation unit for generating first security assistance data from the second drive data set;
The first connecting unit is used for connecting the safety auxiliary module of the first composite robot according to a first connecting instruction;
a thirteenth obtaining unit configured to obtain a configuration auxiliary partition of the security auxiliary module;
and the first updating unit is used for updating data of the configuration auxiliary partition of the safety auxiliary module of the first composite robot according to the first safety auxiliary data.
Further, the system further comprises:
the first triggering unit is used for receiving first early warning information when the first composite robot triggers the early warning information;
the first determining unit is used for determining a first safety auxiliary partition according to the first early warning information;
a first determination unit to determine whether to trigger a first switching feature based on the first security auxiliary partition;
and the first switching unit is used for switching the first replacing robot to execute transfer operation according to the first switching instruction if the first switching characteristic is triggered.
Further, the system further comprises:
A fourteenth obtaining unit, configured to obtain a first planning change degree according to the first loading detection data, where the first planning degree is a change complexity of quadratic programming;
the second determining unit is used for analyzing the guide path change node of the first composite robot according to the first planning change degree and determining multiple types of path nodes;
the third generation unit is used for dividing the detection areas of the first composite robot in various path nodes according to the multi-class path nodes to generate multi-class node detection areas;
a fifteenth obtaining unit, configured to optimize the second driving data set according to the multi-class node detection area, and obtain a third driving data set.
The various modifications and specific examples of the control method of a composite AGV robot in the first embodiment of fig. 1 are equally applicable to the control system of a composite AGV robot in this embodiment, and those skilled in the art will be aware of the implementation method of the control system of a composite AGV robot in this embodiment through the foregoing detailed description of the control method of a composite AGV robot, so that the description will not be repeated here for brevity.
Example III
An electronic device of an embodiment of the present application is described below with reference to fig. 5.
Fig. 5 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of a control method of a composite AGV robot as described in the previous examples, the present application also provides a control system of a composite AGV robot, on which a computer program is stored, which when executed by a processor implements the steps of any of the methods of a control system of a composite AGV robot as described above.
Where in FIG. 5, a bus architecture (represented by bus 300), bus 300 may comprise any number of interconnected buses and bridges, with bus 300 linking together various circuits, including one or more processors, represented by processor 302, and memory, represented by memory 304. Bus 300 may also link together various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., as are well known in the art and, therefore, will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e. a transceiver, providing a means for communicating with various other systems over a transmission medium. The processor 302 is responsible for managing the bus 300 and general processing, while the memory 304 may be used to store data used by the processor 302 in performing operations.
The embodiment of the application provides a control method of a composite AGV robot, which is applied to a control system of the composite AGV robot, wherein the system is in communication connection with a first intelligent detection device, and the method comprises the following steps: acquiring first operation material information of a first composite robot according to the first intelligent detection device, wherein the first operation material information comprises material attribute information and material geometric information; obtaining a loading composite detection model according to the first composite robot; inputting the first operation material information into the loading composite detection model, and obtaining first output information according to the loading composite detection model; generating first loading detection data according to the first output information; acquiring path data and detection data of a first preset guide planning path to obtain a first driving data set, wherein the first driving data set comprises a first path data set and a first detection data set, and the first path data set and the first detection data set are distributed in a time sequence and are in one-to-one correspondence; performing secondary planning on the first driving data set based on the first loading detection data to obtain a second driving data set; and controlling the first composite robot according to the second driving data set. The technical problems that in the prior art, when an AGV composite robot is in operation control, due to the fact that functional units are more, adaptive cooperative control is weak along with material change, and the intelligent degree is low are solved, the technical effects that characteristic analysis and detection of materials are achieved through a composite detection model, driving data are optimized according to a cooperative loading detection result output by the composite detection model, and intelligent control is achieved are achieved.
Those of ordinary skill in the art will appreciate that: the first, second, etc. numbers referred to in the present application are merely for convenience of description and are not intended to limit the scope of the embodiments of the present application, nor represent the sequence. "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. The character "/" generally indicates that the context-dependent object is an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any one," or the like, refers to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one of a, b, or c (species ) may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or plural.
In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, produces a flow or function in accordance with embodiments of the present application, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable system. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another, for example, by wired (e.g., coaxial cable, optical fiber, digital Subscriber Line (DSL)), or wireless (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device including one or more servers, data centers, etc. that can be integrated with the available medium. The usable medium may be a magnetic medium (e.g., a floppy Disk, a hard Disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a Solid State Disk (SSD)), or the like.
The various illustrative logical blocks and circuits described in connection with the embodiments of the present application may be implemented or performed with a general purpose processor, a digital signal processor, an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic system, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the general purpose processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing systems, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software unit executed by a processor, or in a combination of the two. The software elements may be stored in RA memory, flash memory, RO memory, EPRO memory, EEPRO memory, registers, hard disk, a removable disk, a CD-RO or any other form of storage medium known in the art. In an example, a storage medium may be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may reside in a terminal. In the alternative, the processor and the storage medium may reside in different components in a terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the application has been described in connection with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary illustrations of the present application as defined in the appended claims and are considered to cover any and all modifications, variations, combinations, or equivalents that 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 to the present application without departing from the scope of the application. Thus, the present application is intended to include such modifications and alterations insofar as they come within the scope of the application or the equivalents thereof.
Claims (8)
1. A control method of a composite AGV robot, the method being applied to a control system of the composite AGV robot, the system being communicatively connected to a first intelligent detection device, the method comprising:
acquiring first operation material information of a first composite robot according to the first intelligent detection device, wherein the first operation material information comprises material attribute information and material geometric information;
obtaining a loading composite detection model according to the first composite robot;
Inputting the first operation material information into the loading composite detection model, and obtaining first output information according to the loading composite detection model;
generating first loading detection data according to the first output information;
acquiring path data and detection data of a first preset guide planning path to obtain a first driving data set, wherein the first driving data set comprises a first path data set and a first detection data set, and the first path data set and the first detection data set are distributed in a time sequence and are in one-to-one correspondence;
performing secondary planning on the first driving data set based on the first loading detection data to obtain a second driving data set;
controlling the first compound robot according to the second driving data set;
wherein the obtaining a loading composite detection model according to the first composite robot includes:
acquiring first mechanical arm operation information according to the first composite robot;
training a data model according to the first mechanical arm operation information to obtain a first mechanical arm control model, wherein the first mechanical arm control model is obtained by training a training material characteristic set and a mechanical arm control parameter set until convergence;
Obtaining a first carrying and loading detection model;
the first carrying loading detection model is connected based on the first mechanical arm control model, and the loading composite detection model is constructed, wherein the first mechanical arm control model and the first carrying loading detection model realize data interaction;
wherein, according to the first compound robot, obtain a first transport loading detection model, include:
acquiring first bearing space data of the first composite robot;
constructing a three-dimensional space model based on the first bearing space data, wherein the three-dimensional space model is used for carrying out bearing space detection on the first composite robot;
and obtaining the first carrying loading detection model based on the three-dimensional space model.
2. The method of claim 1, wherein the inputting the first work material information into the loading composite detection model obtains first output information according to the loading composite detection model, the method further comprising:
inputting the first operation material information into the loading composite detection model, and obtaining a first loading and unloading control parameter according to the first mechanical arm control model in the loading composite detection model;
Executing material loading operation according to the first loading and unloading control parameters to obtain first loading output information;
and inputting the first loading output information into the first carrying loading detection model for space analysis to obtain the first loading detection data.
3. The method of claim 1, wherein the second programming the first drive data set based on the first load detection data, after obtaining a second drive data set, the method further comprises:
generating first safety auxiliary data according to the second driving data group;
according to a first connection instruction, connecting a safety auxiliary module of the first composite robot;
obtaining a configuration auxiliary partition of the security auxiliary module;
and updating data of the configuration auxiliary partition of the safety auxiliary module of the first composite robot according to the first safety auxiliary data.
4. A method as claimed in claim 3, wherein the method further comprises:
when the first composite robot triggers the early warning information, receiving the first early warning information;
determining a first safety auxiliary partition according to the first early warning information;
judging whether to trigger a first switching feature based on the first security auxiliary partition;
And if the first switching feature is triggered, switching the first replacing robot to execute the transferring operation according to the first switching feature.
5. The method of claim 1, wherein the method further comprises:
obtaining a first planning change degree according to the first loading detection data, wherein the first planning change degree is the change complexity of quadratic programming;
analyzing the guide path change nodes of the first composite robot according to the first planning change degree to determine multiple types of path nodes;
dividing detection areas of the first composite robot in various path nodes according to the multi-class path nodes to generate multi-class node detection areas;
and optimizing the second driving data set according to the multi-class node detection areas to obtain a third driving data set.
6. A control system for a composite AGV robot, the system comprising:
the first obtaining unit is used for obtaining first operation material information of the first composite robot according to the first intelligent detection device, wherein the first operation material information comprises material attribute information and material geometric information;
The second obtaining unit is used for obtaining a loading composite detection model according to the first composite robot;
the first input unit is used for inputting the first operation material information into the loading composite detection model, and obtaining first output information according to the loading composite detection model;
the first generation unit is used for generating first loading detection data according to the first output information;
the third obtaining unit is used for obtaining a first driving data set by collecting path data and detection data of a first preset guide planning path, wherein the first driving data set comprises a first path data set and a first detection data set, and the first path data set and the first detection data set are distributed in a time sequence and are in one-to-one correspondence;
a fourth obtaining unit configured to perform quadratic programming on the first driving data set based on the first loading detection data, to obtain a second driving data set;
the first control unit is used for controlling the first composite robot according to the second driving data set;
A fifth obtaining unit, configured to obtain first mechanical arm operation information according to the first composite robot;
the sixth obtaining unit is used for training a data model according to the first mechanical arm operation information to obtain a first mechanical arm control model, wherein the first mechanical arm control model is obtained by training a training material characteristic set and a mechanical arm control parameter set until convergence;
a seventh obtaining unit for obtaining a first handling loading detection model;
the first construction unit is used for connecting the first carrying and loading detection model based on the first mechanical arm control model and constructing the loading composite detection model, wherein the first mechanical arm control model and the first carrying and loading detection model realize data interaction;
an eighth obtaining unit, configured to obtain first bearing space data of the first composite robot;
the second construction unit is used for constructing a three-dimensional space model based on the first bearing space data, wherein the three-dimensional space model is used for carrying out bearing space detection on the first composite robot;
A ninth obtaining unit configured to obtain the first conveyance loading detection model based on the three-dimensional space model.
7. An electronic device, comprising: a processor coupled to a memory for storing a program, characterized by causing a system to perform the steps of the method of any one of claims 1 to 5 when said program is executed by said processor.
8. A computer-readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the method according to any of claims 1 to 5.
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